diff --git a/.changes/3.297.2 b/.changes/3.297.2 new file mode 100644 index 0000000000..264e1808d6 --- /dev/null +++ b/.changes/3.297.2 @@ -0,0 +1,17 @@ +[ + { + "type": "api-change", + "category": "Inspector2", + "description": "This release adds ECR container image scanning based on their lastRecordedPullTime." + }, + { + "type": "api-change", + "category": "Connect", + "description": "Update list and string length limits for predefined attributes." + }, + { + "type": "api-change", + "category": "SageMaker", + "description": "Amazon SageMaker Automatic Model Tuning now provides an API to programmatically delete tuning jobs." + } +] diff --git a/CHANGELOG.md b/CHANGELOG.md index 69bfc8828b..9a9ca93b57 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,11 @@ # CHANGELOG +## next release + +* `Aws\Inspector2` - This release adds ECR container image scanning based on their lastRecordedPullTime. +* `Aws\Connect` - Update list and string length limits for predefined attributes. +* `Aws\SageMaker` - Amazon SageMaker Automatic Model Tuning now provides an API to programmatically delete tuning jobs. + ## 3.297.1 - 2024-01-25 * `Aws\S3` - Fixes warning in S3 client when region is not provided in constructor diff --git a/src/SageMaker/SageMakerClient.php b/src/SageMaker/SageMakerClient.php index 94559951d5..95065f0bf2 100644 --- a/src/SageMaker/SageMakerClient.php +++ b/src/SageMaker/SageMakerClient.php @@ -171,6 +171,8 @@ * @method \GuzzleHttp\Promise\Promise deleteHubContentAsync(array $args = []) * @method \Aws\Result deleteHumanTaskUi(array $args = []) * @method \GuzzleHttp\Promise\Promise deleteHumanTaskUiAsync(array $args = []) + * @method \Aws\Result deleteHyperParameterTuningJob(array $args = []) + * @method \GuzzleHttp\Promise\Promise deleteHyperParameterTuningJobAsync(array $args = []) * @method \Aws\Result deleteImage(array $args = []) * @method \GuzzleHttp\Promise\Promise deleteImageAsync(array $args = []) * @method \Aws\Result deleteImageVersion(array $args = []) diff --git a/src/data/connect/2017-08-08/api-2.json b/src/data/connect/2017-08-08/api-2.json index fcf379598e..3752722d62 100644 --- a/src/data/connect/2017-08-08/api-2.json +++ b/src/data/connect/2017-08-08/api-2.json @@ -11460,7 +11460,7 @@ }, "PredefinedAttributeName":{ "type":"string", - "max":128, + "max":64, "min":1 }, "PredefinedAttributeSearchConditionList":{ @@ -11481,13 +11481,13 @@ }, "PredefinedAttributeStringValue":{ "type":"string", - "max":128, + "max":64, "min":1 }, "PredefinedAttributeStringValuesList":{ "type":"list", "member":{"shape":"PredefinedAttributeStringValue"}, - "max":75, + "max":128, "min":1 }, "PredefinedAttributeSummary":{ diff --git a/src/data/connect/2017-08-08/api-2.json.php b/src/data/connect/2017-08-08/api-2.json.php index 6a998e3d3e..9c9c87220f 100644 --- a/src/data/connect/2017-08-08/api-2.json.php +++ b/src/data/connect/2017-08-08/api-2.json.php @@ -1,3 +1,3 @@ '2.0', 'metadata' => [ 'apiVersion' => '2017-08-08', 'endpointPrefix' => 'connect', 'jsonVersion' => '1.1', 'protocol' => 'rest-json', 'serviceAbbreviation' => 'Amazon Connect', 'serviceFullName' => 'Amazon Connect Service', 'serviceId' => 'Connect', 'signatureVersion' => 'v4', 'signingName' => 'connect', 'uid' => 'connect-2017-08-08', ], 'operations' => [ 'ActivateEvaluationForm' => [ 'name' => 'ActivateEvaluationForm', 'http' => [ 'method' => 'POST', 'requestUri' => '/evaluation-forms/{InstanceId}/{EvaluationFormId}/activate', ], 'input' => [ 'shape' => 'ActivateEvaluationFormRequest', ], 'output' => [ 'shape' => 'ActivateEvaluationFormResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceConflictException', ], ], ], 'AssociateAnalyticsDataSet' => [ 'name' => 'AssociateAnalyticsDataSet', 'http' => [ 'method' => 'PUT', 'requestUri' => '/analytics-data/instance/{InstanceId}/association', ], 'input' => [ 'shape' => 'AssociateAnalyticsDataSetRequest', ], 'output' => [ 'shape' => 'AssociateAnalyticsDataSetResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'AssociateApprovedOrigin' => [ 'name' => 'AssociateApprovedOrigin', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/approved-origin', ], 'input' => [ 'shape' => 'AssociateApprovedOriginRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateBot' => [ 'name' => 'AssociateBot', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/bot', ], 'input' => [ 'shape' => 'AssociateBotRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateDefaultVocabulary' => [ 'name' => 'AssociateDefaultVocabulary', 'http' => [ 'method' => 'PUT', 'requestUri' => '/default-vocabulary/{InstanceId}/{LanguageCode}', ], 'input' => [ 'shape' => 'AssociateDefaultVocabularyRequest', ], 'output' => [ 'shape' => 'AssociateDefaultVocabularyResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'AssociateFlow' => [ 'name' => 'AssociateFlow', 'http' => [ 'method' => 'PUT', 'requestUri' => '/flow-associations/{InstanceId}', ], 'input' => [ 'shape' => 'AssociateFlowRequest', ], 'output' => [ 'shape' => 'AssociateFlowResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateInstanceStorageConfig' => [ 'name' => 'AssociateInstanceStorageConfig', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/storage-config', ], 'input' => [ 'shape' => 'AssociateInstanceStorageConfigRequest', ], 'output' => [ 'shape' => 'AssociateInstanceStorageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateLambdaFunction' => [ 'name' => 'AssociateLambdaFunction', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/lambda-function', ], 'input' => [ 'shape' => 'AssociateLambdaFunctionRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateLexBot' => [ 'name' => 'AssociateLexBot', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/lex-bot', ], 'input' => [ 'shape' => 'AssociateLexBotRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociatePhoneNumberContactFlow' => [ 'name' => 'AssociatePhoneNumberContactFlow', 'http' => [ 'method' => 'PUT', 'requestUri' => '/phone-number/{PhoneNumberId}/contact-flow', ], 'input' => [ 'shape' => 'AssociatePhoneNumberContactFlowRequest', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'AssociateQueueQuickConnects' => [ 'name' => 'AssociateQueueQuickConnects', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/associate-quick-connects', ], 'input' => [ 'shape' => 'AssociateQueueQuickConnectsRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'AssociateRoutingProfileQueues' => [ 'name' => 'AssociateRoutingProfileQueues', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/associate-queues', ], 'input' => [ 'shape' => 'AssociateRoutingProfileQueuesRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'AssociateSecurityKey' => [ 'name' => 'AssociateSecurityKey', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/security-key', ], 'input' => [ 'shape' => 'AssociateSecurityKeyRequest', ], 'output' => [ 'shape' => 'AssociateSecurityKeyResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateTrafficDistributionGroupUser' => [ 'name' => 'AssociateTrafficDistributionGroupUser', 'http' => [ 'method' => 'PUT', 'requestUri' => '/traffic-distribution-group/{TrafficDistributionGroupId}/user', ], 'input' => [ 'shape' => 'AssociateTrafficDistributionGroupUserRequest', ], 'output' => [ 'shape' => 'AssociateTrafficDistributionGroupUserResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], ], 'idempotent' => true, ], 'AssociateUserProficiencies' => [ 'name' => 'AssociateUserProficiencies', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/associate-proficiencies', ], 'input' => [ 'shape' => 'AssociateUserProficienciesRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'BatchAssociateAnalyticsDataSet' => [ 'name' => 'BatchAssociateAnalyticsDataSet', 'http' => [ 'method' => 'PUT', 'requestUri' => '/analytics-data/instance/{InstanceId}/associations', ], 'input' => [ 'shape' => 'BatchAssociateAnalyticsDataSetRequest', ], 'output' => [ 'shape' => 'BatchAssociateAnalyticsDataSetResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'BatchDisassociateAnalyticsDataSet' => [ 'name' => 'BatchDisassociateAnalyticsDataSet', 'http' => [ 'method' => 'POST', 'requestUri' => '/analytics-data/instance/{InstanceId}/associations', ], 'input' => [ 'shape' => 'BatchDisassociateAnalyticsDataSetRequest', ], 'output' => [ 'shape' => 'BatchDisassociateAnalyticsDataSetResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'BatchGetFlowAssociation' => [ 'name' => 'BatchGetFlowAssociation', 'http' => [ 'method' => 'POST', 'requestUri' => '/flow-associations-batch/{InstanceId}', ], 'input' => [ 'shape' => 'BatchGetFlowAssociationRequest', ], 'output' => [ 'shape' => 'BatchGetFlowAssociationResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'BatchPutContact' => [ 'name' => 'BatchPutContact', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/batch/{InstanceId}', ], 'input' => [ 'shape' => 'BatchPutContactRequest', ], 'output' => [ 'shape' => 'BatchPutContactResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'IdempotencyException', ], ], 'idempotent' => true, ], 'ClaimPhoneNumber' => [ 'name' => 'ClaimPhoneNumber', 'http' => [ 'method' => 'POST', 'requestUri' => '/phone-number/claim', ], 'input' => [ 'shape' => 'ClaimPhoneNumberRequest', ], 'output' => [ 'shape' => 'ClaimPhoneNumberResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'CreateAgentStatus' => [ 'name' => 'CreateAgentStatus', 'http' => [ 'method' => 'PUT', 'requestUri' => '/agent-status/{InstanceId}', ], 'input' => [ 'shape' => 'CreateAgentStatusRequest', ], 'output' => [ 'shape' => 'CreateAgentStatusResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateContactFlow' => [ 'name' => 'CreateContactFlow', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact-flows/{InstanceId}', ], 'input' => [ 'shape' => 'CreateContactFlowRequest', ], 'output' => [ 'shape' => 'CreateContactFlowResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidContactFlowException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateContactFlowModule' => [ 'name' => 'CreateContactFlowModule', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact-flow-modules/{InstanceId}', ], 'input' => [ 'shape' => 'CreateContactFlowModuleRequest', ], 'output' => [ 'shape' => 'CreateContactFlowModuleResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidContactFlowModuleException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateEvaluationForm' => [ 'name' => 'CreateEvaluationForm', 'http' => [ 'method' => 'PUT', 'requestUri' => '/evaluation-forms/{InstanceId}', ], 'input' => [ 'shape' => 'CreateEvaluationFormRequest', ], 'output' => [ 'shape' => 'CreateEvaluationFormResponse', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ResourceConflictException', ], ], 'idempotent' => true, ], 'CreateHoursOfOperation' => [ 'name' => 'CreateHoursOfOperation', 'http' => [ 'method' => 'PUT', 'requestUri' => '/hours-of-operations/{InstanceId}', ], 'input' => [ 'shape' => 'CreateHoursOfOperationRequest', ], 'output' => [ 'shape' => 'CreateHoursOfOperationResponse', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateInstance' => [ 'name' => 'CreateInstance', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance', ], 'input' => [ 'shape' => 'CreateInstanceRequest', ], 'output' => [ 'shape' => 'CreateInstanceResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateIntegrationAssociation' => [ 'name' => 'CreateIntegrationAssociation', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/integration-associations', ], 'input' => [ 'shape' => 'CreateIntegrationAssociationRequest', ], 'output' => [ 'shape' => 'CreateIntegrationAssociationResponse', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'CreateParticipant' => [ 'name' => 'CreateParticipant', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/create-participant', ], 'input' => [ 'shape' => 'CreateParticipantRequest', ], 'output' => [ 'shape' => 'CreateParticipantResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'CreatePersistentContactAssociation' => [ 'name' => 'CreatePersistentContactAssociation', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/persistent-contact-association/{InstanceId}/{InitialContactId}', ], 'input' => [ 'shape' => 'CreatePersistentContactAssociationRequest', ], 'output' => [ 'shape' => 'CreatePersistentContactAssociationResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreatePredefinedAttribute' => [ 'name' => 'CreatePredefinedAttribute', 'http' => [ 'method' => 'PUT', 'requestUri' => '/predefined-attributes/{InstanceId}', ], 'input' => [ 'shape' => 'CreatePredefinedAttributeRequest', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreatePrompt' => [ 'name' => 'CreatePrompt', 'http' => [ 'method' => 'PUT', 'requestUri' => '/prompts/{InstanceId}', ], 'input' => [ 'shape' => 'CreatePromptRequest', ], 'output' => [ 'shape' => 'CreatePromptResponse', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateQueue' => [ 'name' => 'CreateQueue', 'http' => [ 'method' => 'PUT', 'requestUri' => '/queues/{InstanceId}', ], 'input' => [ 'shape' => 'CreateQueueRequest', ], 'output' => [ 'shape' => 'CreateQueueResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateQuickConnect' => [ 'name' => 'CreateQuickConnect', 'http' => [ 'method' => 'PUT', 'requestUri' => '/quick-connects/{InstanceId}', ], 'input' => [ 'shape' => 'CreateQuickConnectRequest', ], 'output' => [ 'shape' => 'CreateQuickConnectResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateRoutingProfile' => [ 'name' => 'CreateRoutingProfile', 'http' => [ 'method' => 'PUT', 'requestUri' => '/routing-profiles/{InstanceId}', ], 'input' => [ 'shape' => 'CreateRoutingProfileRequest', ], 'output' => [ 'shape' => 'CreateRoutingProfileResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateRule' => [ 'name' => 'CreateRule', 'http' => [ 'method' => 'POST', 'requestUri' => '/rules/{InstanceId}', ], 'input' => [ 'shape' => 'CreateRuleRequest', ], 'output' => [ 'shape' => 'CreateRuleResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'ServiceQuotaExceededException', ], ], ], 'CreateSecurityProfile' => [ 'name' => 'CreateSecurityProfile', 'http' => [ 'method' => 'PUT', 'requestUri' => '/security-profiles/{InstanceId}', ], 'input' => [ 'shape' => 'CreateSecurityProfileRequest', ], 'output' => [ 'shape' => 'CreateSecurityProfileResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateTaskTemplate' => [ 'name' => 'CreateTaskTemplate', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/task/template', ], 'input' => [ 'shape' => 'CreateTaskTemplateRequest', ], 'output' => [ 'shape' => 'CreateTaskTemplateResponse', ], 'errors' => [ [ 'shape' => 'PropertyValidationException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateTrafficDistributionGroup' => [ 'name' => 'CreateTrafficDistributionGroup', 'http' => [ 'method' => 'PUT', 'requestUri' => '/traffic-distribution-group', ], 'input' => [ 'shape' => 'CreateTrafficDistributionGroupRequest', ], 'output' => [ 'shape' => 'CreateTrafficDistributionGroupResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'ResourceNotReadyException', ], ], ], 'CreateUseCase' => [ 'name' => 'CreateUseCase', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/integration-associations/{IntegrationAssociationId}/use-cases', ], 'input' => [ 'shape' => 'CreateUseCaseRequest', ], 'output' => [ 'shape' => 'CreateUseCaseResponse', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'CreateUser' => [ 'name' => 'CreateUser', 'http' => [ 'method' => 'PUT', 'requestUri' => '/users/{InstanceId}', ], 'input' => [ 'shape' => 'CreateUserRequest', ], 'output' => [ 'shape' => 'CreateUserResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateUserHierarchyGroup' => [ 'name' => 'CreateUserHierarchyGroup', 'http' => [ 'method' => 'PUT', 'requestUri' => '/user-hierarchy-groups/{InstanceId}', ], 'input' => [ 'shape' => 'CreateUserHierarchyGroupRequest', ], 'output' => [ 'shape' => 'CreateUserHierarchyGroupResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateView' => [ 'name' => 'CreateView', 'http' => [ 'method' => 'PUT', 'requestUri' => '/views/{InstanceId}', ], 'input' => [ 'shape' => 'CreateViewRequest', ], 'output' => [ 'shape' => 'CreateViewResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'ResourceInUseException', ], ], 'idempotent' => true, ], 'CreateViewVersion' => [ 'name' => 'CreateViewVersion', 'http' => [ 'method' => 'PUT', 'requestUri' => '/views/{InstanceId}/{ViewId}/versions', ], 'input' => [ 'shape' => 'CreateViewVersionRequest', ], 'output' => [ 'shape' => 'CreateViewVersionResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ResourceInUseException', ], ], 'idempotent' => true, ], 'CreateVocabulary' => [ 'name' => 'CreateVocabulary', 'http' => [ 'method' => 'POST', 'requestUri' => '/vocabulary/{InstanceId}', ], 'input' => [ 'shape' => 'CreateVocabularyRequest', ], 'output' => [ 'shape' => 'CreateVocabularyResponse', ], 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'method' => 'DELETE', 'requestUri' => '/contact-flow-modules/{InstanceId}/{ContactFlowModuleId}', ], 'input' => [ 'shape' => 'DeleteContactFlowModuleRequest', ], 'output' => [ 'shape' => 'DeleteContactFlowModuleResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'DeleteEvaluationForm' => [ 'name' => 'DeleteEvaluationForm', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/evaluation-forms/{InstanceId}/{EvaluationFormId}', ], 'input' => [ 'shape' => 'DeleteEvaluationFormRequest', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceConflictException', ], ], 'idempotent' => true, ], 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'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'DeleteRoutingProfile' => [ 'name' => 'DeleteRoutingProfile', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}', ], 'input' => [ 'shape' => 'DeleteRoutingProfileRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceInUseException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'DeleteRule' => [ 'name' => 'DeleteRule', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/rules/{InstanceId}/{RuleId}', ], 'input' => [ 'shape' => 'DeleteRuleRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 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'input' => [ 'shape' => 'DeleteUseCaseRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'DeleteUser' => [ 'name' => 'DeleteUser', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/users/{InstanceId}/{UserId}', ], 'input' => [ 'shape' => 'DeleteUserRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'DeleteUserHierarchyGroup' => [ 'name' => 'DeleteUserHierarchyGroup', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/user-hierarchy-groups/{InstanceId}/{HierarchyGroupId}', ], 'input' => [ 'shape' => 'DeleteUserHierarchyGroupRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 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'output' => [ 'shape' => 'ListLexBotsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListPhoneNumbers' => [ 'name' => 'ListPhoneNumbers', 'http' => [ 'method' => 'GET', 'requestUri' => '/phone-numbers-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListPhoneNumbersRequest', ], 'output' => [ 'shape' => 'ListPhoneNumbersResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListPhoneNumbersV2' => [ 'name' => 'ListPhoneNumbersV2', 'http' => [ 'method' => 'POST', 'requestUri' => '/phone-number/list', ], 'input' => [ 'shape' => 'ListPhoneNumbersV2Request', ], 'output' => [ 'shape' => 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'output' => [ 'shape' => 'SendChatIntegrationEventResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'StartChatContact' => [ 'name' => 'StartChatContact', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/chat', ], 'input' => [ 'shape' => 'StartChatContactRequest', ], 'output' => [ 'shape' => 'StartChatContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'LimitExceededException', ], ], ], 'StartContactEvaluation' => [ 'name' => 'StartContactEvaluation', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact-evaluations/{InstanceId}', ], 'input' => [ 'shape' => 'StartContactEvaluationRequest', ], 'output' => [ 'shape' 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=> 'InternalServiceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'TransferContact' => [ 'name' => 'TransferContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/transfer', ], 'input' => [ 'shape' => 'TransferContactRequest', ], 'output' => [ 'shape' => 'TransferContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UntagContact' => [ 'name' => 'UntagContact', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/contact/tags/{InstanceId}/{ContactId}', ], 'input' => [ 'shape' => 'UntagContactRequest', ], 'output' => [ 'shape' => 'UntagContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], 'idempotent' => true, ], 'UntagResource' => [ 'name' => 'UntagResource', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/tags/{resourceArn}', ], 'input' => [ 'shape' => 'UntagResourceRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'UpdateAgentStatus' => [ 'name' => 'UpdateAgentStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/agent-status/{InstanceId}/{AgentStatusId}', ], 'input' => [ 'shape' => 'UpdateAgentStatusRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContact' => [ 'name' => 'UpdateContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contacts/{InstanceId}/{ContactId}', ], 'input' => [ 'shape' => 'UpdateContactRequest', ], 'output' => [ 'shape' => 'UpdateContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'UpdateContactAttributes' => [ 'name' => 'UpdateContactAttributes', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/attributes', ], 'input' => [ 'shape' => 'UpdateContactAttributesRequest', ], 'output' => [ 'shape' => 'UpdateContactAttributesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactEvaluation' => [ 'name' => 'UpdateContactEvaluation', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-evaluations/{InstanceId}/{EvaluationId}', ], 'input' => [ 'shape' => 'UpdateContactEvaluationRequest', ], 'output' => [ 'shape' => 'UpdateContactEvaluationResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceConflictException', ], ], ], 'UpdateContactFlowContent' => [ 'name' => 'UpdateContactFlowContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flows/{InstanceId}/{ContactFlowId}/content', ], 'input' => [ 'shape' => 'UpdateContactFlowContentRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowContentResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidContactFlowException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactFlowMetadata' => [ 'name' => 'UpdateContactFlowMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flows/{InstanceId}/{ContactFlowId}/metadata', ], 'input' => [ 'shape' => 'UpdateContactFlowMetadataRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowMetadataResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactFlowModuleContent' => [ 'name' => 'UpdateContactFlowModuleContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flow-modules/{InstanceId}/{ContactFlowModuleId}/content', ], 'input' => [ 'shape' => 'UpdateContactFlowModuleContentRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowModuleContentResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidContactFlowModuleException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactFlowModuleMetadata' => [ 'name' => 'UpdateContactFlowModuleMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flow-modules/{InstanceId}/{ContactFlowModuleId}/metadata', ], 'input' => [ 'shape' => 'UpdateContactFlowModuleMetadataRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowModuleMetadataResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactFlowName' => [ 'name' => 'UpdateContactFlowName', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flows/{InstanceId}/{ContactFlowId}/name', ], 'input' => [ 'shape' => 'UpdateContactFlowNameRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowNameResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactRoutingData' => [ 'name' => 'UpdateContactRoutingData', 'http' => [ 'method' => 'POST', 'requestUri' => '/contacts/{InstanceId}/{ContactId}/routing-data', ], 'input' => [ 'shape' => 'UpdateContactRoutingDataRequest', ], 'output' => [ 'shape' => 'UpdateContactRoutingDataResponse', ], 'errors' => [ [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'UpdateContactSchedule' => [ 'name' => 'UpdateContactSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/schedule', ], 'input' => [ 'shape' => 'UpdateContactScheduleRequest', ], 'output' => [ 'shape' => 'UpdateContactScheduleResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateEvaluationForm' => [ 'name' => 'UpdateEvaluationForm', 'http' => [ 'method' => 'PUT', 'requestUri' => '/evaluation-forms/{InstanceId}/{EvaluationFormId}', ], 'input' => [ 'shape' => 'UpdateEvaluationFormRequest', ], 'output' => [ 'shape' => 'UpdateEvaluationFormResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ResourceConflictException', ], ], 'idempotent' => true, ], 'UpdateHoursOfOperation' => [ 'name' => 'UpdateHoursOfOperation', 'http' => [ 'method' => 'POST', 'requestUri' => '/hours-of-operations/{InstanceId}/{HoursOfOperationId}', ], 'input' => [ 'shape' => 'UpdateHoursOfOperationRequest', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateInstanceAttribute' => [ 'name' => 'UpdateInstanceAttribute', 'http' => [ 'method' => 'POST', 'requestUri' => '/instance/{InstanceId}/attribute/{AttributeType}', ], 'input' => [ 'shape' => 'UpdateInstanceAttributeRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'UpdateInstanceStorageConfig' => [ 'name' => 'UpdateInstanceStorageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/instance/{InstanceId}/storage-config/{AssociationId}', ], 'input' => [ 'shape' => 'UpdateInstanceStorageConfigRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'UpdateParticipantRoleConfig' => [ 'name' => 'UpdateParticipantRoleConfig', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/participant-role-config/{InstanceId}/{ContactId}', ], 'input' => [ 'shape' => 'UpdateParticipantRoleConfigRequest', ], 'output' => [ 'shape' => 'UpdateParticipantRoleConfigResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdatePhoneNumber' => [ 'name' => 'UpdatePhoneNumber', 'http' => [ 'method' => 'PUT', 'requestUri' => '/phone-number/{PhoneNumberId}', ], 'input' => [ 'shape' => 'UpdatePhoneNumberRequest', ], 'output' => [ 'shape' => 'UpdatePhoneNumberResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceInUseException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'UpdatePhoneNumberMetadata' => [ 'name' => 'UpdatePhoneNumberMetadata', 'http' => [ 'method' => 'PUT', 'requestUri' => '/phone-number/{PhoneNumberId}/metadata', ], 'input' => [ 'shape' => 'UpdatePhoneNumberMetadataRequest', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceInUseException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdatePredefinedAttribute' => [ 'name' => 'UpdatePredefinedAttribute', 'http' => [ 'method' => 'POST', 'requestUri' => '/predefined-attributes/{InstanceId}/{Name}', ], 'input' => [ 'shape' => 'UpdatePredefinedAttributeRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdatePrompt' => [ 'name' => 'UpdatePrompt', 'http' => [ 'method' => 'POST', 'requestUri' => '/prompts/{InstanceId}/{PromptId}', ], 'input' => [ 'shape' => 'UpdatePromptRequest', ], 'output' => [ 'shape' => 'UpdatePromptResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueHoursOfOperation' => [ 'name' => 'UpdateQueueHoursOfOperation', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/hours-of-operation', ], 'input' => [ 'shape' => 'UpdateQueueHoursOfOperationRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueMaxContacts' => [ 'name' => 'UpdateQueueMaxContacts', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/max-contacts', ], 'input' => [ 'shape' => 'UpdateQueueMaxContactsRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueName' => [ 'name' => 'UpdateQueueName', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/name', ], 'input' => [ 'shape' => 'UpdateQueueNameRequest', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueOutboundCallerConfig' => [ 'name' => 'UpdateQueueOutboundCallerConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/outbound-caller-config', ], 'input' => [ 'shape' => 'UpdateQueueOutboundCallerConfigRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueStatus' => [ 'name' => 'UpdateQueueStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/status', ], 'input' => [ 'shape' => 'UpdateQueueStatusRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQuickConnectConfig' => [ 'name' => 'UpdateQuickConnectConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/quick-connects/{InstanceId}/{QuickConnectId}/config', ], 'input' => [ 'shape' => 'UpdateQuickConnectConfigRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQuickConnectName' => [ 'name' => 'UpdateQuickConnectName', 'http' => [ 'method' => 'POST', 'requestUri' => '/quick-connects/{InstanceId}/{QuickConnectId}/name', ], 'input' => [ 'shape' => 'UpdateQuickConnectNameRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileAgentAvailabilityTimer' => [ 'name' => 'UpdateRoutingProfileAgentAvailabilityTimer', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/agent-availability-timer', ], 'input' => [ 'shape' => 'UpdateRoutingProfileAgentAvailabilityTimerRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileConcurrency' => [ 'name' => 'UpdateRoutingProfileConcurrency', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/concurrency', ], 'input' => [ 'shape' => 'UpdateRoutingProfileConcurrencyRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileDefaultOutboundQueue' => [ 'name' => 'UpdateRoutingProfileDefaultOutboundQueue', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/default-outbound-queue', ], 'input' => [ 'shape' => 'UpdateRoutingProfileDefaultOutboundQueueRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileName' => [ 'name' => 'UpdateRoutingProfileName', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/name', ], 'input' => [ 'shape' => 'UpdateRoutingProfileNameRequest', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileQueues' => [ 'name' => 'UpdateRoutingProfileQueues', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/queues', ], 'input' => [ 'shape' => 'UpdateRoutingProfileQueuesRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRule' => [ 'name' => 'UpdateRule', 'http' => [ 'method' => 'PUT', 'requestUri' => '/rules/{InstanceId}/{RuleId}', ], 'input' => [ 'shape' => 'UpdateRuleRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceConflictException', ], ], ], 'UpdateSecurityProfile' => [ 'name' => 'UpdateSecurityProfile', 'http' => [ 'method' => 'POST', 'requestUri' => '/security-profiles/{InstanceId}/{SecurityProfileId}', ], 'input' => [ 'shape' => 'UpdateSecurityProfileRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateTaskTemplate' => [ 'name' => 'UpdateTaskTemplate', 'http' => [ 'method' => 'POST', 'requestUri' => '/instance/{InstanceId}/task/template/{TaskTemplateId}', ], 'input' => [ 'shape' => 'UpdateTaskTemplateRequest', ], 'output' => [ 'shape' => 'UpdateTaskTemplateResponse', ], 'errors' => [ [ 'shape' => 'PropertyValidationException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateTrafficDistribution' => [ 'name' => 'UpdateTrafficDistribution', 'http' => [ 'method' => 'PUT', 'requestUri' => '/traffic-distribution/{Id}', ], 'input' => [ 'shape' => 'UpdateTrafficDistributionRequest', ], 'output' => [ 'shape' => 'UpdateTrafficDistributionResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserHierarchy' => [ 'name' => 'UpdateUserHierarchy', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/hierarchy', ], 'input' => [ 'shape' => 'UpdateUserHierarchyRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserHierarchyGroupName' => [ 'name' => 'UpdateUserHierarchyGroupName', 'http' => [ 'method' => 'POST', 'requestUri' => '/user-hierarchy-groups/{InstanceId}/{HierarchyGroupId}/name', ], 'input' => [ 'shape' => 'UpdateUserHierarchyGroupNameRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserHierarchyStructure' => [ 'name' => 'UpdateUserHierarchyStructure', 'http' => [ 'method' => 'POST', 'requestUri' => '/user-hierarchy-structure/{InstanceId}', ], 'input' => [ 'shape' => 'UpdateUserHierarchyStructureRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceInUseException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserIdentityInfo' => [ 'name' => 'UpdateUserIdentityInfo', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/identity-info', ], 'input' => [ 'shape' => 'UpdateUserIdentityInfoRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserPhoneConfig' => [ 'name' => 'UpdateUserPhoneConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/phone-config', ], 'input' => [ 'shape' => 'UpdateUserPhoneConfigRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserProficiencies' => [ 'name' => 'UpdateUserProficiencies', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/proficiencies', ], 'input' => [ 'shape' => 'UpdateUserProficienciesRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserRoutingProfile' => [ 'name' => 'UpdateUserRoutingProfile', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/routing-profile', ], 'input' => [ 'shape' => 'UpdateUserRoutingProfileRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserSecurityProfiles' => [ 'name' => 'UpdateUserSecurityProfiles', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/security-profiles', ], 'input' => [ 'shape' => 'UpdateUserSecurityProfilesRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateViewContent' => [ 'name' => 'UpdateViewContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/views/{InstanceId}/{ViewId}', ], 'input' => [ 'shape' => 'UpdateViewContentRequest', ], 'output' => [ 'shape' => 'UpdateViewContentResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'ResourceInUseException', ], ], ], 'UpdateViewMetadata' => [ 'name' => 'UpdateViewMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/views/{InstanceId}/{ViewId}/metadata', ], 'input' => [ 'shape' => 'UpdateViewMetadataRequest', ], 'output' => [ 'shape' => 'UpdateViewMetadataResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceInUseException', ], ], ], ], 'shapes' => [ 'ARN' => [ 'type' => 'string', ], 'AWSAccountId' => [ 'type' => 'string', ], 'AccessDeniedException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 403, ], 'exception' => true, ], 'ActionSummaries' => [ 'type' => 'list', 'member' => [ 'shape' => 'ActionSummary', ], ], 'ActionSummary' => [ 'type' => 'structure', 'required' => [ 'ActionType', ], 'members' => [ 'ActionType' => [ 'shape' => 'ActionType', ], ], ], 'ActionType' => [ 'type' => 'string', 'enum' => [ 'CREATE_TASK', 'ASSIGN_CONTACT_CATEGORY', 'GENERATE_EVENTBRIDGE_EVENT', 'SEND_NOTIFICATION', 'CREATE_CASE', 'UPDATE_CASE', 'END_ASSOCIATED_TASKS', ], ], 'ActivateEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', 'EvaluationFormVersion', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], ], ], 'ActivateEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormId', 'EvaluationFormArn', 'EvaluationFormVersion', ], 'members' => [ 'EvaluationFormId' => [ 'shape' => 'ResourceId', ], 'EvaluationFormArn' => [ 'shape' => 'ARN', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], ], ], 'AfterContactWorkTimeLimit' => [ 'type' => 'integer', 'min' => 0, ], 'AgentAvailabilityTimer' => [ 'type' => 'string', 'enum' => [ 'TIME_SINCE_LAST_ACTIVITY', 'TIME_SINCE_LAST_INBOUND', ], ], 'AgentConfig' => [ 'type' => 'structure', 'required' => [ 'Distributions', ], 'members' => [ 'Distributions' => [ 'shape' => 'DistributionList', ], ], ], 'AgentContactReference' => [ 'type' => 'structure', 'members' => [ 'ContactId' => [ 'shape' => 'ContactId', ], 'Channel' => [ 'shape' => 'Channel', ], 'InitiationMethod' => [ 'shape' => 'ContactInitiationMethod', ], 'AgentContactState' => [ 'shape' => 'ContactState', ], 'StateStartTimestamp' => [ 'shape' => 'Timestamp', ], 'ConnectedToAgentTimestamp' => [ 'shape' => 'Timestamp', ], 'Queue' => [ 'shape' => 'QueueReference', ], ], ], 'AgentContactReferenceList' => [ 'type' => 'list', 'member' => [ 'shape' => 'AgentContactReference', ], ], 'AgentFirstName' => [ 'type' => 'string', 'max' => 100, 'min' => 1, 'sensitive' => true, ], 'AgentHierarchyGroups' => [ 'type' => 'structure', 'members' => [ 'L1Ids' => [ 'shape' => 'HierarchyGroupIdList', ], 'L2Ids' => [ 'shape' => 'HierarchyGroupIdList', ], 'L3Ids' => [ 'shape' => 'HierarchyGroupIdList', ], 'L4Ids' => [ 'shape' => 'HierarchyGroupIdList', ], 'L5Ids' => [ 'shape' => 'HierarchyGroupIdList', ], ], ], 'AgentInfo' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'AgentResourceId', ], 'ConnectedToAgentTimestamp' => [ 'shape' => 'timestamp', ], 'AgentPauseDurationInSeconds' => [ 'shape' => 'AgentPauseDurationInSeconds', ], ], ], 'AgentLastName' => [ 'type' => 'string', 'max' => 100, 'min' => 1, 'sensitive' => true, ], 'AgentPauseDurationInSeconds' => [ 'type' => 'integer', 'min' => 0, ], 'AgentResourceId' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'AgentResourceIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'AgentResourceId', ], 'max' => 100, 'min' => 0, ], 'AgentStatus' => [ 'type' => 'structure', 'members' => [ 'AgentStatusARN' => [ 'shape' => 'ARN', ], 'AgentStatusId' => [ 'shape' => 'AgentStatusId', ], 'Name' => [ 'shape' => 'AgentStatusName', ], 'Description' => [ 'shape' => 'AgentStatusDescription', ], 'Type' => [ 'shape' => 'AgentStatusType', ], 'DisplayOrder' => [ 'shape' => 'AgentStatusOrderNumber', ], 'State' => [ 'shape' => 'AgentStatusState', ], 'Tags' => [ 'shape' => 'TagMap', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'AgentStatusDescription' => [ 'type' => 'string', 'max' => 250, 'min' => 1, ], 'AgentStatusId' => [ 'type' => 'string', ], 'AgentStatusName' => [ 'type' => 'string', 'max' => 127, 'min' => 1, ], 'AgentStatusOrderNumber' => [ 'type' => 'integer', 'max' => 50, 'min' => 1, ], 'AgentStatusReference' => [ 'type' => 'structure', 'members' => [ 'StatusStartTimestamp' => [ 'shape' => 'Timestamp', ], 'StatusArn' => [ 'shape' => 'ARN', ], 'StatusName' => [ 'shape' => 'AgentStatusName', ], ], ], 'AgentStatusState' => [ 'type' => 'string', 'enum' => [ 'ENABLED', 'DISABLED', ], ], 'AgentStatusSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'AgentStatusId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'AgentStatusName', ], 'Type' => [ 'shape' => 'AgentStatusType', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'AgentStatusSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'AgentStatusSummary', ], ], 'AgentStatusType' => [ 'type' => 'string', 'enum' => [ 'ROUTABLE', 'CUSTOM', 'OFFLINE', ], ], 'AgentStatusTypes' => [ 'type' => 'list', 'member' => [ 'shape' => 'AgentStatusType', ], 'max' => 3, ], 'AgentUsername' => [ 'type' => 'string', 'max' => 100, 'min' => 1, ], 'AgentsMinOneMaxHundred' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserId', ], 'max' => 100, 'min' => 1, ], 'AliasArn' => [ 'type' => 'string', 'max' => 100, 'min' => 1, ], 'AllowedAccessControlTags' => [ 'type' => 'map', 'key' => [ 'shape' => 'SecurityProfilePolicyKey', ], 'value' => [ 'shape' => 'SecurityProfilePolicyValue', ], 'max' => 2, ], 'AllowedCapabilities' => [ 'type' => 'structure', 'members' => [ 'Customer' => [ 'shape' => 'ParticipantCapabilities', ], 'Agent' => [ 'shape' => 'ParticipantCapabilities', ], ], ], 'AllowedMonitorCapabilities' => [ 'type' => 'list', 'member' => [ 'shape' => 'MonitorCapability', ], 'max' => 2, ], 'AnalyticsDataAssociationResult' => [ 'type' => 'structure', 'members' => [ 'DataSetId' => [ 'shape' => 'DataSetId', ], 'TargetAccountId' => [ 'shape' => 'AWSAccountId', ], 'ResourceShareId' => [ 'shape' => 'String', ], 'ResourceShareArn' => [ 'shape' => 'ARN', ], ], ], 'AnalyticsDataAssociationResults' => [ 'type' => 'list', 'member' => [ 'shape' => 'AnalyticsDataAssociationResult', ], ], 'AnswerMachineDetectionConfig' => [ 'type' => 'structure', 'members' => [ 'EnableAnswerMachineDetection' => [ 'shape' => 'Boolean', ], 'AwaitAnswerMachinePrompt' => [ 'shape' => 'Boolean', ], ], ], 'Application' => [ 'type' => 'structure', 'members' => [ 'Namespace' => [ 'shape' => 'Namespace', ], 'ApplicationPermissions' => [ 'shape' => 'ApplicationPermissions', ], ], ], 'ApplicationPermissions' => [ 'type' => 'list', 'member' => [ 'shape' => 'Permission', ], 'max' => 10, 'min' => 1, ], 'Applications' => [ 'type' => 'list', 'member' => [ 'shape' => 'Application', ], 'max' => 10, ], 'ApproximateTotalCount' => [ 'type' => 'long', ], 'ArtifactId' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'ArtifactStatus' => [ 'type' => 'string', 'enum' => [ 'APPROVED', 'REJECTED', 'IN_PROGRESS', ], ], 'AssignContactCategoryActionDefinition' => [ 'type' => 'structure', 'members' => [], ], 'AssociateAnalyticsDataSetRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'DataSetId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'DataSetId' => [ 'shape' => 'DataSetId', ], 'TargetAccountId' => [ 'shape' => 'AWSAccountId', ], ], ], 'AssociateAnalyticsDataSetResponse' => [ 'type' => 'structure', 'members' => [ 'DataSetId' => [ 'shape' => 'DataSetId', ], 'TargetAccountId' => [ 'shape' => 'AWSAccountId', ], 'ResourceShareId' => [ 'shape' => 'String', ], 'ResourceShareArn' => [ 'shape' => 'ARN', ], ], ], 'AssociateApprovedOriginRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Origin', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Origin' => [ 'shape' => 'Origin', ], ], ], 'AssociateBotRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'LexBot' => [ 'shape' => 'LexBot', ], 'LexV2Bot' => [ 'shape' => 'LexV2Bot', ], ], ], 'AssociateDefaultVocabularyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'LanguageCode', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', 'location' => 'uri', 'locationName' => 'LanguageCode', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', ], ], ], 'AssociateDefaultVocabularyResponse' => [ 'type' => 'structure', 'members' => [], ], 'AssociateFlowRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ResourceId', 'FlowId', 'ResourceType', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ResourceId' => [ 'shape' => 'ARN', ], 'FlowId' => [ 'shape' => 'ARN', ], 'ResourceType' => [ 'shape' => 'FlowAssociationResourceType', ], ], ], 'AssociateFlowResponse' => [ 'type' => 'structure', 'members' => [], ], 'AssociateInstanceStorageConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ResourceType', 'StorageConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ResourceType' => [ 'shape' => 'InstanceStorageResourceType', ], 'StorageConfig' => [ 'shape' => 'InstanceStorageConfig', ], ], ], 'AssociateInstanceStorageConfigResponse' => [ 'type' => 'structure', 'members' => [ 'AssociationId' => [ 'shape' => 'AssociationId', ], ], ], 'AssociateLambdaFunctionRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'FunctionArn', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'FunctionArn' => [ 'shape' => 'FunctionArn', ], ], ], 'AssociateLexBotRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'LexBot', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'LexBot' => [ 'shape' => 'LexBot', ], ], ], 'AssociatePhoneNumberContactFlowRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneNumberId', 'InstanceId', 'ContactFlowId', ], 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', 'location' => 'uri', 'locationName' => 'PhoneNumberId', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], ], ], 'AssociateQueueQuickConnectsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', 'QuickConnectIds', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'QuickConnectIds' => [ 'shape' => 'QuickConnectsList', ], ], ], 'AssociateRoutingProfileQueuesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'QueueConfigs', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'QueueConfigs' => [ 'shape' => 'RoutingProfileQueueConfigList', ], ], ], 'AssociateSecurityKeyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Key', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Key' => [ 'shape' => 'PEM', ], ], ], 'AssociateSecurityKeyResponse' => [ 'type' => 'structure', 'members' => [ 'AssociationId' => [ 'shape' => 'AssociationId', ], ], ], 'AssociateTrafficDistributionGroupUserRequest' => [ 'type' => 'structure', 'required' => [ 'TrafficDistributionGroupId', 'UserId', 'InstanceId', ], 'members' => [ 'TrafficDistributionGroupId' => [ 'shape' => 'TrafficDistributionGroupIdOrArn', 'location' => 'uri', 'locationName' => 'TrafficDistributionGroupId', ], 'UserId' => [ 'shape' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], ], ], 'AssociateTrafficDistributionGroupUserResponse' => [ 'type' => 'structure', 'members' => [], ], 'AssociateUserProficienciesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'UserId', 'UserProficiencies', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'UserProficiencies' => [ 'shape' => 'UserProficiencyList', ], ], ], 'AssociationId' => [ 'type' => 'string', 'max' => 100, 'min' => 1, ], 'AttachmentName' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'AttachmentReference' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ReferenceKey', ], 'Value' => [ 'shape' => 'ReferenceValue', ], 'Status' => [ 'shape' => 'ReferenceStatus', ], ], ], 'Attendee' => [ 'type' => 'structure', 'members' => [ 'AttendeeId' => [ 'shape' => 'AttendeeId', ], 'JoinToken' => [ 'shape' => 'JoinToken', ], ], ], 'AttendeeId' => [ 'type' => 'string', ], 'Attribute' => [ 'type' => 'structure', 'members' => [ 'AttributeType' => [ 'shape' => 'InstanceAttributeType', ], 'Value' => [ 'shape' => 'InstanceAttributeValue', ], ], ], 'AttributeName' => [ 'type' => 'string', 'max' => 32767, 'min' => 1, ], 'AttributeValue' => [ 'type' => 'string', 'max' => 32767, 'min' => 0, ], 'Attributes' => [ 'type' => 'map', 'key' => [ 'shape' => 'AttributeName', ], 'value' => [ 'shape' => 'AttributeValue', ], ], 'AttributesList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Attribute', ], ], 'AudioFeatures' => [ 'type' => 'structure', 'members' => [ 'EchoReduction' => [ 'shape' => 'MeetingFeatureStatus', ], ], ], 'AutoAccept' => [ 'type' => 'boolean', ], 'AvailableNumberSummary' => [ 'type' => 'structure', 'members' => [ 'PhoneNumber' => [ 'shape' => 'PhoneNumber', ], 'PhoneNumberCountryCode' => [ 'shape' => 'PhoneNumberCountryCode', ], 'PhoneNumberType' => [ 'shape' => 'PhoneNumberType', ], ], ], 'AvailableNumbersList' => [ 'type' => 'list', 'member' => [ 'shape' => 'AvailableNumberSummary', ], ], 'AwsRegion' => [ 'type' => 'string', 'max' => 31, 'min' => 8, 'pattern' => '[a-z]{2}(-[a-z]+){1,2}(-[0-9])?', ], 'BatchAssociateAnalyticsDataSetRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'DataSetIds', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'DataSetIds' => [ 'shape' => 'DataSetIds', ], 'TargetAccountId' => [ 'shape' => 'AWSAccountId', ], ], ], 'BatchAssociateAnalyticsDataSetResponse' => [ 'type' => 'structure', 'members' => [ 'Created' => [ 'shape' => 'AnalyticsDataAssociationResults', ], 'Errors' => [ 'shape' => 'ErrorResults', ], ], ], 'BatchDisassociateAnalyticsDataSetRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'DataSetIds', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'DataSetIds' => [ 'shape' => 'DataSetIds', ], 'TargetAccountId' => [ 'shape' => 'AWSAccountId', ], ], ], 'BatchDisassociateAnalyticsDataSetResponse' => [ 'type' => 'structure', 'members' => [ 'Deleted' => [ 'shape' => 'DataSetIds', ], 'Errors' => [ 'shape' => 'ErrorResults', ], ], ], 'BatchGetFlowAssociationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ResourceIds', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ResourceIds' => [ 'shape' => 'resourceArnListMaxLimit100', ], 'ResourceType' => [ 'shape' => 'ListFlowAssociationResourceType', ], ], ], 'BatchGetFlowAssociationResponse' => [ 'type' => 'structure', 'members' => [ 'FlowAssociationSummaryList' => [ 'shape' => 'FlowAssociationSummaryList', ], ], ], 'BatchPutContactRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactDataRequestList', ], 'members' => [ 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactDataRequestList' => [ 'shape' => 'ContactDataRequestList', ], ], ], 'BatchPutContactResponse' => [ 'type' => 'structure', 'members' => [ 'SuccessfulRequestList' => [ 'shape' => 'SuccessfulRequestList', ], 'FailedRequestList' => [ 'shape' => 'FailedRequestList', ], ], ], 'BehaviorType' => [ 'type' => 'string', 'enum' => [ 'ROUTE_CURRENT_CHANNEL_ONLY', 'ROUTE_ANY_CHANNEL', ], ], 'Boolean' => [ 'type' => 'boolean', ], 'BotName' => [ 'type' => 'string', 'max' => 50, ], 'BoxedBoolean' => [ 'type' => 'boolean', ], 'BucketName' => [ 'type' => 'string', 'max' => 128, 'min' => 1, ], 'Campaign' => [ 'type' => 'structure', 'members' => [ 'CampaignId' => [ 'shape' => 'CampaignId', ], ], ], 'CampaignId' => [ 'type' => 'string', 'max' => 100, 'min' => 1, ], 'Channel' => [ 'type' => 'string', 'enum' => [ 'VOICE', 'CHAT', 'TASK', ], ], 'ChannelList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Channel', ], ], 'ChannelToCountMap' => [ 'type' => 'map', 'key' => [ 'shape' => 'Channel', ], 'value' => [ 'shape' => 'IntegerCount', ], ], 'Channels' => [ 'type' => 'list', 'member' => [ 'shape' => 'Channel', ], 'max' => 3, ], 'ChatContent' => [ 'type' => 'string', 'max' => 16384, 'min' => 1, ], 'ChatContentType' => [ 'type' => 'string', 'max' => 100, 'min' => 1, ], 'ChatDurationInMinutes' => [ 'type' => 'integer', 'max' => 10080, 'min' => 60, ], 'ChatEvent' => [ 'type' => 'structure', 'required' => [ 'Type', ], 'members' => [ 'Type' => [ 'shape' => 'ChatEventType', ], 'ContentType' => [ 'shape' => 'ChatContentType', ], 'Content' => [ 'shape' => 'ChatContent', ], ], ], 'ChatEventType' => [ 'type' => 'string', 'enum' => [ 'DISCONNECT', 'MESSAGE', 'EVENT', ], ], 'ChatMessage' => [ 'type' => 'structure', 'required' => [ 'ContentType', 'Content', ], 'members' => [ 'ContentType' => [ 'shape' => 'ChatContentType', ], 'Content' => [ 'shape' => 'ChatContent', ], ], ], 'ChatParticipantRoleConfig' => [ 'type' => 'structure', 'required' => [ 'ParticipantTimerConfigList', ], 'members' => [ 'ParticipantTimerConfigList' => [ 'shape' => 'ParticipantTimerConfigList', ], ], ], 'ChatStreamingConfiguration' => [ 'type' => 'structure', 'required' => [ 'StreamingEndpointArn', ], 'members' => [ 'StreamingEndpointArn' => [ 'shape' => 'ChatStreamingEndpointARN', ], ], ], 'ChatStreamingEndpointARN' => [ 'type' => 'string', 'max' => 350, 'min' => 1, ], 'ClaimPhoneNumberRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneNumber', ], 'members' => [ 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'PhoneNumber' => [ 'shape' => 'PhoneNumber', ], 'PhoneNumberDescription' => [ 'shape' => 'PhoneNumberDescription', ], 'Tags' => [ 'shape' => 'TagMap', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'ClaimPhoneNumberResponse' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', ], 'PhoneNumberArn' => [ 'shape' => 'ARN', ], ], ], 'ClaimedPhoneNumberSummary' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', ], 'PhoneNumberArn' => [ 'shape' => 'ARN', ], 'PhoneNumber' => [ 'shape' => 'PhoneNumber', ], 'PhoneNumberCountryCode' => [ 'shape' => 'PhoneNumberCountryCode', ], 'PhoneNumberType' => [ 'shape' => 'PhoneNumberType', ], 'PhoneNumberDescription' => [ 'shape' => 'PhoneNumberDescription', ], 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'Tags' => [ 'shape' => 'TagMap', ], 'PhoneNumberStatus' => [ 'shape' => 'PhoneNumberStatus', ], 'SourcePhoneNumberArn' => [ 'shape' => 'ARN', ], ], ], 'ClientToken' => [ 'type' => 'string', 'max' => 500, ], 'CommonNameLength127' => [ 'type' => 'string', 'max' => 127, 'min' => 1, ], 'Comparison' => [ 'type' => 'string', 'enum' => [ 'LT', ], ], 'Concurrency' => [ 'type' => 'integer', 'max' => 10, 'min' => 1, ], 'ConflictException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 409, ], 'exception' => true, ], 'ConnectionData' => [ 'type' => 'structure', 'members' => [ 'Attendee' => [ 'shape' => 'Attendee', ], 'Meeting' => [ 'shape' => 'Meeting', ], ], ], 'Contact' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'Id' => [ 'shape' => 'ContactId', ], 'InitialContactId' => [ 'shape' => 'ContactId', ], 'PreviousContactId' => [ 'shape' => 'ContactId', ], 'InitiationMethod' => [ 'shape' => 'ContactInitiationMethod', ], 'Name' => [ 'shape' => 'Name', ], 'Description' => [ 'shape' => 'Description', ], 'Channel' => [ 'shape' => 'Channel', ], 'QueueInfo' => [ 'shape' => 'QueueInfo', ], 'AgentInfo' => [ 'shape' => 'AgentInfo', ], 'InitiationTimestamp' => [ 'shape' => 'timestamp', ], 'DisconnectTimestamp' => [ 'shape' => 'timestamp', ], 'LastUpdateTimestamp' => [ 'shape' => 'timestamp', ], 'LastPausedTimestamp' => [ 'shape' => 'timestamp', ], 'LastResumedTimestamp' => [ 'shape' => 'timestamp', ], 'TotalPauseCount' => [ 'shape' => 'TotalPauseCount', ], 'TotalPauseDurationInSeconds' => [ 'shape' => 'TotalPauseDurationInSeconds', ], 'ScheduledTimestamp' => [ 'shape' => 'timestamp', ], 'RelatedContactId' => [ 'shape' => 'ContactId', ], 'WisdomInfo' => [ 'shape' => 'WisdomInfo', ], 'QueueTimeAdjustmentSeconds' => [ 'shape' => 'QueueTimeAdjustmentSeconds', ], 'QueuePriority' => [ 'shape' => 'QueuePriority', ], 'Tags' => [ 'shape' => 'ContactTagMap', ], ], ], 'ContactAnalysis' => [ 'type' => 'structure', 'members' => [ 'Transcript' => [ 'shape' => 'Transcript', ], ], ], 'ContactDataRequest' => [ 'type' => 'structure', 'members' => [ 'SystemEndpoint' => [ 'shape' => 'Endpoint', ], 'CustomerEndpoint' => [ 'shape' => 'Endpoint', ], 'RequestIdentifier' => [ 'shape' => 'RequestIdentifier', ], 'QueueId' => [ 'shape' => 'QueueId', ], 'Attributes' => [ 'shape' => 'Attributes', ], 'Campaign' => [ 'shape' => 'Campaign', ], ], ], 'ContactDataRequestList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactDataRequest', ], 'max' => 25, 'min' => 1, ], 'ContactFilter' => [ 'type' => 'structure', 'members' => [ 'ContactStates' => [ 'shape' => 'ContactStates', ], ], ], 'ContactFlow' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'Id' => [ 'shape' => 'ContactFlowId', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'Type' => [ 'shape' => 'ContactFlowType', ], 'State' => [ 'shape' => 'ContactFlowState', ], 'Description' => [ 'shape' => 'ContactFlowDescription', ], 'Content' => [ 'shape' => 'ContactFlowContent', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'ContactFlowContent' => [ 'type' => 'string', ], 'ContactFlowDescription' => [ 'type' => 'string', ], 'ContactFlowId' => [ 'type' => 'string', 'max' => 500, ], 'ContactFlowModule' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'Id' => [ 'shape' => 'ContactFlowModuleId', ], 'Name' => [ 'shape' => 'ContactFlowModuleName', ], 'Content' => [ 'shape' => 'ContactFlowModuleContent', ], 'Description' => [ 'shape' => 'ContactFlowModuleDescription', ], 'State' => [ 'shape' => 'ContactFlowModuleState', ], 'Status' => [ 'shape' => 'ContactFlowModuleStatus', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'ContactFlowModuleContent' => [ 'type' => 'string', 'max' => 256000, 'min' => 1, ], 'ContactFlowModuleDescription' => [ 'type' => 'string', 'max' => 500, 'min' => 0, 'pattern' => '.*\\S.*', ], 'ContactFlowModuleId' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'ContactFlowModuleName' => [ 'type' => 'string', 'max' => 127, 'min' => 1, 'pattern' => '.*\\S.*', ], 'ContactFlowModuleState' => [ 'type' => 'string', 'enum' => [ 'ACTIVE', 'ARCHIVED', ], ], 'ContactFlowModuleStatus' => [ 'type' => 'string', 'enum' => [ 'PUBLISHED', 'SAVED', ], ], 'ContactFlowModuleSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ContactFlowModuleId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'ContactFlowModuleName', ], 'State' => [ 'shape' => 'ContactFlowModuleState', ], ], ], 'ContactFlowModulesSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactFlowModuleSummary', ], ], 'ContactFlowName' => [ 'type' => 'string', 'min' => 1, ], 'ContactFlowNotPublishedException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 404, ], 'exception' => true, ], 'ContactFlowState' => [ 'type' => 'string', 'enum' => [ 'ACTIVE', 'ARCHIVED', ], ], 'ContactFlowSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ContactFlowId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'ContactFlowType' => [ 'shape' => 'ContactFlowType', ], 'ContactFlowState' => [ 'shape' => 'ContactFlowState', ], ], ], 'ContactFlowSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactFlowSummary', ], ], 'ContactFlowType' => [ 'type' => 'string', 'enum' => [ 'CONTACT_FLOW', 'CUSTOMER_QUEUE', 'CUSTOMER_HOLD', 'CUSTOMER_WHISPER', 'AGENT_HOLD', 'AGENT_WHISPER', 'OUTBOUND_WHISPER', 'AGENT_TRANSFER', 'QUEUE_TRANSFER', ], ], 'ContactFlowTypes' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactFlowType', ], 'max' => 10, ], 'ContactId' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'ContactInitiationMethod' => [ 'type' => 'string', 'enum' => [ 'INBOUND', 'OUTBOUND', 'TRANSFER', 'QUEUE_TRANSFER', 'CALLBACK', 'API', 'DISCONNECT', 'MONITOR', 'EXTERNAL_OUTBOUND', ], ], 'ContactNotFoundException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 410, ], 'exception' => true, ], 'ContactReferences' => [ 'type' => 'map', 'key' => [ 'shape' => 'ReferenceKey', ], 'value' => [ 'shape' => 'Reference', ], ], 'ContactSearchSummary' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'Id' => [ 'shape' => 'ContactId', ], 'InitialContactId' => [ 'shape' => 'ContactId', ], 'PreviousContactId' => [ 'shape' => 'ContactId', ], 'InitiationMethod' => [ 'shape' => 'ContactInitiationMethod', ], 'Channel' => [ 'shape' => 'Channel', ], 'QueueInfo' => [ 'shape' => 'ContactSearchSummaryQueueInfo', ], 'AgentInfo' => [ 'shape' => 'ContactSearchSummaryAgentInfo', ], 'InitiationTimestamp' => [ 'shape' => 'timestamp', ], 'DisconnectTimestamp' => [ 'shape' => 'timestamp', ], 'ScheduledTimestamp' => [ 'shape' => 'timestamp', ], ], ], 'ContactSearchSummaryAgentInfo' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'AgentResourceId', ], 'ConnectedToAgentTimestamp' => [ 'shape' => 'timestamp', ], ], ], 'ContactSearchSummaryQueueInfo' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'QueueId', ], 'EnqueueTimestamp' => [ 'shape' => 'timestamp', ], ], ], 'ContactState' => [ 'type' => 'string', 'enum' => [ 'INCOMING', 'PENDING', 'CONNECTING', 'CONNECTED', 'CONNECTED_ONHOLD', 'MISSED', 'ERROR', 'ENDED', 'REJECTED', ], ], 'ContactStates' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactState', ], 'max' => 9, ], 'ContactTagKey' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '^(?!aws:)[a-zA-Z+-=._:/]+$', ], 'ContactTagKeys' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactTagKey', ], 'max' => 6, 'min' => 1, ], 'ContactTagMap' => [ 'type' => 'map', 'key' => [ 'shape' => 'ContactTagKey', ], 'value' => [ 'shape' => 'ContactTagValue', ], 'max' => 6, 'min' => 1, ], 'ContactTagValue' => [ 'type' => 'string', 'max' => 256, ], 'Contacts' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactSearchSummary', ], ], 'Content' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'ContentType' => [ 'type' => 'string', 'max' => 255, 'min' => 1, ], 'ControlPlaneTagFilter' => [ 'type' => 'structure', 'members' => [ 'OrConditions' => [ 'shape' => 'TagOrConditionList', ], 'AndConditions' => [ 'shape' => 'TagAndConditionList', ], 'TagCondition' => [ 'shape' => 'TagCondition', ], ], ], 'CreateAgentStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'State', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'AgentStatusName', ], 'Description' => [ 'shape' => 'AgentStatusDescription', ], 'State' => [ 'shape' => 'AgentStatusState', ], 'DisplayOrder' => [ 'shape' => 'AgentStatusOrderNumber', 'box' => true, ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateAgentStatusResponse' => [ 'type' => 'structure', 'members' => [ 'AgentStatusARN' => [ 'shape' => 'ARN', ], 'AgentStatusId' => [ 'shape' => 'AgentStatusId', ], ], ], 'CreateCaseActionDefinition' => [ 'type' => 'structure', 'required' => [ 'Fields', 'TemplateId', ], 'members' => [ 'Fields' => [ 'shape' => 'FieldValues', ], 'TemplateId' => [ 'shape' => 'TemplateId', ], ], ], 'CreateContactFlowModuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'ContactFlowModuleName', ], 'Description' => [ 'shape' => 'ContactFlowModuleDescription', ], 'Content' => [ 'shape' => 'ContactFlowModuleContent', ], 'Tags' => [ 'shape' => 'TagMap', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'CreateContactFlowModuleResponse' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ContactFlowModuleId', ], 'Arn' => [ 'shape' => 'ARN', ], ], ], 'CreateContactFlowRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Type', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'Type' => [ 'shape' => 'ContactFlowType', ], 'Description' => [ 'shape' => 'ContactFlowDescription', ], 'Content' => [ 'shape' => 'ContactFlowContent', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateContactFlowResponse' => [ 'type' => 'structure', 'members' => [ 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'ContactFlowArn' => [ 'shape' => 'ARN', ], ], ], 'CreateEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Title', 'Items', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Title' => [ 'shape' => 'EvaluationFormTitle', ], 'Description' => [ 'shape' => 'EvaluationFormDescription', ], 'Items' => [ 'shape' => 'EvaluationFormItemsList', ], 'ScoringStrategy' => [ 'shape' => 'EvaluationFormScoringStrategy', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'CreateEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormId', 'EvaluationFormArn', ], 'members' => [ 'EvaluationFormId' => [ 'shape' => 'ResourceId', ], 'EvaluationFormArn' => [ 'shape' => 'ARN', ], ], ], 'CreateHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'TimeZone', 'Config', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'HoursOfOperationDescription', ], 'TimeZone' => [ 'shape' => 'TimeZone', ], 'Config' => [ 'shape' => 'HoursOfOperationConfigList', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateHoursOfOperationResponse' => [ 'type' => 'structure', 'members' => [ 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', ], 'HoursOfOperationArn' => [ 'shape' => 'ARN', ], ], ], 'CreateInstanceRequest' => [ 'type' => 'structure', 'required' => [ 'IdentityManagementType', 'InboundCallsEnabled', 'OutboundCallsEnabled', ], 'members' => [ 'ClientToken' => [ 'shape' => 'ClientToken', ], 'IdentityManagementType' => [ 'shape' => 'DirectoryType', ], 'InstanceAlias' => [ 'shape' => 'DirectoryAlias', ], 'DirectoryId' => [ 'shape' => 'DirectoryId', ], 'InboundCallsEnabled' => [ 'shape' => 'InboundCallsEnabled', ], 'OutboundCallsEnabled' => [ 'shape' => 'OutboundCallsEnabled', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateInstanceResponse' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'InstanceId', ], 'Arn' => [ 'shape' => 'ARN', ], ], ], 'CreateIntegrationAssociationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'IntegrationType', 'IntegrationArn', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'IntegrationType' => [ 'shape' => 'IntegrationType', ], 'IntegrationArn' => [ 'shape' => 'ARN', ], 'SourceApplicationUrl' => [ 'shape' => 'URI', ], 'SourceApplicationName' => [ 'shape' => 'SourceApplicationName', ], 'SourceType' => [ 'shape' => 'SourceType', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateIntegrationAssociationResponse' => [ 'type' => 'structure', 'members' => [ 'IntegrationAssociationId' => [ 'shape' => 'IntegrationAssociationId', ], 'IntegrationAssociationArn' => [ 'shape' => 'ARN', ], ], ], 'CreateParticipantRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'ParticipantDetails', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'ParticipantDetails' => [ 'shape' => 'ParticipantDetailsToAdd', ], ], ], 'CreateParticipantResponse' => [ 'type' => 'structure', 'members' => [ 'ParticipantCredentials' => [ 'shape' => 'ParticipantTokenCredentials', ], 'ParticipantId' => [ 'shape' => 'ParticipantId', ], ], ], 'CreatePersistentContactAssociationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'InitialContactId', 'RehydrationType', 'SourceContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'InitialContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'InitialContactId', ], 'RehydrationType' => [ 'shape' => 'RehydrationType', ], 'SourceContactId' => [ 'shape' => 'ContactId', ], 'ClientToken' => [ 'shape' => 'ClientToken', ], ], ], 'CreatePersistentContactAssociationResponse' => [ 'type' => 'structure', 'members' => [ 'ContinuedFromContactId' => [ 'shape' => 'ContactId', ], ], ], 'CreatePredefinedAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Values', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'PredefinedAttributeName', ], 'Values' => [ 'shape' => 'PredefinedAttributeValues', ], ], ], 'CreatePromptRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'S3Uri', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'PromptDescription', ], 'S3Uri' => [ 'shape' => 'S3Uri', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreatePromptResponse' => [ 'type' => 'structure', 'members' => [ 'PromptARN' => [ 'shape' => 'ARN', ], 'PromptId' => [ 'shape' => 'PromptId', ], ], ], 'CreateQueueRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'QueueDescription', ], 'OutboundCallerConfig' => [ 'shape' => 'OutboundCallerConfig', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', ], 'MaxContacts' => [ 'shape' => 'QueueMaxContacts', 'box' => true, ], 'QuickConnectIds' => [ 'shape' => 'QuickConnectsList', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateQueueResponse' => [ 'type' => 'structure', 'members' => [ 'QueueArn' => [ 'shape' => 'ARN', ], 'QueueId' => [ 'shape' => 'QueueId', ], ], ], 'CreateQuickConnectRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'QuickConnectConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'QuickConnectName', ], 'Description' => [ 'shape' => 'QuickConnectDescription', ], 'QuickConnectConfig' => [ 'shape' => 'QuickConnectConfig', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateQuickConnectResponse' => [ 'type' => 'structure', 'members' => [ 'QuickConnectARN' => [ 'shape' => 'ARN', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', ], ], ], 'CreateRoutingProfileRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Description', 'DefaultOutboundQueueId', 'MediaConcurrencies', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'RoutingProfileName', ], 'Description' => [ 'shape' => 'RoutingProfileDescription', ], 'DefaultOutboundQueueId' => [ 'shape' => 'QueueId', ], 'QueueConfigs' => [ 'shape' => 'RoutingProfileQueueConfigList', ], 'MediaConcurrencies' => [ 'shape' => 'MediaConcurrencies', ], 'Tags' => [ 'shape' => 'TagMap', ], 'AgentAvailabilityTimer' => [ 'shape' => 'AgentAvailabilityTimer', ], ], ], 'CreateRoutingProfileResponse' => [ 'type' => 'structure', 'members' => [ 'RoutingProfileArn' => [ 'shape' => 'ARN', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], ], ], 'CreateRuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'TriggerEventSource', 'Function', 'Actions', 'PublishStatus', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'RuleName', ], 'TriggerEventSource' => [ 'shape' => 'RuleTriggerEventSource', ], 'Function' => [ 'shape' => 'RuleFunction', ], 'Actions' => [ 'shape' => 'RuleActions', ], 'PublishStatus' => [ 'shape' => 'RulePublishStatus', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'CreateRuleResponse' => [ 'type' => 'structure', 'required' => [ 'RuleArn', 'RuleId', ], 'members' => [ 'RuleArn' => [ 'shape' => 'ARN', ], 'RuleId' => [ 'shape' => 'RuleId', ], ], ], 'CreateSecurityProfileName' => [ 'type' => 'string', 'max' => 127, 'min' => 1, 'pattern' => '^[ a-zA-Z0-9_@-]+$', ], 'CreateSecurityProfileRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileName', 'InstanceId', ], 'members' => [ 'SecurityProfileName' => [ 'shape' => 'CreateSecurityProfileName', ], 'Description' => [ 'shape' => 'SecurityProfileDescription', ], 'Permissions' => [ 'shape' => 'PermissionsList', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Tags' => [ 'shape' => 'TagMap', ], 'AllowedAccessControlTags' => [ 'shape' => 'AllowedAccessControlTags', ], 'TagRestrictedResources' => [ 'shape' => 'TagRestrictedResourceList', ], 'Applications' => [ 'shape' => 'Applications', ], ], ], 'CreateSecurityProfileResponse' => [ 'type' => 'structure', 'members' => [ 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', ], 'SecurityProfileArn' => [ 'shape' => 'ARN', ], ], ], 'CreateTaskTemplateRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Fields', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'TaskTemplateName', ], 'Description' => [ 'shape' => 'TaskTemplateDescription', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'Constraints' => [ 'shape' => 'TaskTemplateConstraints', ], 'Defaults' => [ 'shape' => 'TaskTemplateDefaults', ], 'Status' => [ 'shape' => 'TaskTemplateStatus', ], 'Fields' => [ 'shape' => 'TaskTemplateFields', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'CreateTaskTemplateResponse' => [ 'type' => 'structure', 'required' => [ 'Id', 'Arn', ], 'members' => [ 'Id' => [ 'shape' => 'TaskTemplateId', ], 'Arn' => [ 'shape' => 'TaskTemplateArn', ], ], ], 'CreateTrafficDistributionGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'InstanceId', ], 'members' => [ 'Name' => [ 'shape' => 'Name128', ], 'Description' => [ 'shape' => 'Description250', ], 'InstanceId' => [ 'shape' => 'InstanceIdOrArn', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateTrafficDistributionGroupResponse' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'TrafficDistributionGroupId', ], 'Arn' => [ 'shape' => 'TrafficDistributionGroupArn', ], ], ], 'CreateUseCaseRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'IntegrationAssociationId', 'UseCaseType', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'IntegrationAssociationId' => [ 'shape' => 'IntegrationAssociationId', 'location' => 'uri', 'locationName' => 'IntegrationAssociationId', ], 'UseCaseType' => [ 'shape' => 'UseCaseType', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateUseCaseResponse' => [ 'type' => 'structure', 'members' => [ 'UseCaseId' => [ 'shape' => 'UseCaseId', ], 'UseCaseArn' => [ 'shape' => 'ARN', ], ], ], 'CreateUserHierarchyGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'InstanceId', ], 'members' => [ 'Name' => [ 'shape' => 'HierarchyGroupName', ], 'ParentGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateUserHierarchyGroupResponse' => [ 'type' => 'structure', 'members' => [ 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'HierarchyGroupArn' => [ 'shape' => 'ARN', ], ], ], 'CreateUserRequest' => [ 'type' => 'structure', 'required' => [ 'Username', 'PhoneConfig', 'SecurityProfileIds', 'RoutingProfileId', 'InstanceId', ], 'members' => [ 'Username' => [ 'shape' => 'AgentUsername', ], 'Password' => [ 'shape' => 'Password', ], 'IdentityInfo' => [ 'shape' => 'UserIdentityInfo', ], 'PhoneConfig' => [ 'shape' => 'UserPhoneConfig', ], 'DirectoryUserId' => [ 'shape' => 'DirectoryUserId', ], 'SecurityProfileIds' => [ 'shape' => 'SecurityProfileIds', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateUserResponse' => [ 'type' => 'structure', 'members' => [ 'UserId' => [ 'shape' => 'UserId', ], 'UserArn' => [ 'shape' => 'ARN', ], ], ], 'CreateViewRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Status', 'Content', 'Name', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ClientToken' => [ 'shape' => 'ViewsClientToken', ], 'Status' => [ 'shape' => 'ViewStatus', ], 'Content' => [ 'shape' => 'ViewInputContent', ], 'Description' => [ 'shape' => 'ViewDescription', ], 'Name' => [ 'shape' => 'ViewName', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateViewResponse' => [ 'type' => 'structure', 'members' => [ 'View' => [ 'shape' => 'View', ], ], ], 'CreateViewVersionRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'VersionDescription' => [ 'shape' => 'ViewDescription', ], 'ViewContentSha256' => [ 'shape' => 'ViewContentSha256', ], ], ], 'CreateViewVersionResponse' => [ 'type' => 'structure', 'members' => [ 'View' => [ 'shape' => 'View', ], ], ], 'CreateVocabularyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'VocabularyName', 'LanguageCode', 'Content', ], 'members' => [ 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'VocabularyName' => [ 'shape' => 'VocabularyName', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], 'Content' => [ 'shape' => 'VocabularyContent', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateVocabularyResponse' => [ 'type' => 'structure', 'required' => [ 'VocabularyArn', 'VocabularyId', 'State', ], 'members' => [ 'VocabularyArn' => [ 'shape' => 'ARN', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', ], 'State' => [ 'shape' => 'VocabularyState', ], ], ], 'Credentials' => [ 'type' => 'structure', 'members' => [ 'AccessToken' => [ 'shape' => 'SecurityToken', ], 'AccessTokenExpiration' => [ 'shape' => 'timestamp', ], 'RefreshToken' => [ 'shape' => 'SecurityToken', ], 'RefreshTokenExpiration' => [ 'shape' => 'timestamp', ], ], 'sensitive' => true, ], 'CrossChannelBehavior' => [ 'type' => 'structure', 'required' => [ 'BehaviorType', ], 'members' => [ 'BehaviorType' => [ 'shape' => 'BehaviorType', ], ], ], 'CurrentMetric' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'CurrentMetricName', ], 'Unit' => [ 'shape' => 'Unit', ], ], ], 'CurrentMetricData' => [ 'type' => 'structure', 'members' => [ 'Metric' => [ 'shape' => 'CurrentMetric', ], 'Value' => [ 'shape' => 'Value', 'box' => true, ], ], ], 'CurrentMetricDataCollections' => [ 'type' => 'list', 'member' => [ 'shape' => 'CurrentMetricData', ], ], 'CurrentMetricName' => [ 'type' => 'string', 'enum' => [ 'AGENTS_ONLINE', 'AGENTS_AVAILABLE', 'AGENTS_ON_CALL', 'AGENTS_NON_PRODUCTIVE', 'AGENTS_AFTER_CONTACT_WORK', 'AGENTS_ERROR', 'AGENTS_STAFFED', 'CONTACTS_IN_QUEUE', 'OLDEST_CONTACT_AGE', 'CONTACTS_SCHEDULED', 'AGENTS_ON_CONTACT', 'SLOTS_ACTIVE', 'SLOTS_AVAILABLE', ], ], 'CurrentMetricResult' => [ 'type' => 'structure', 'members' => [ 'Dimensions' => [ 'shape' => 'Dimensions', ], 'Collections' => [ 'shape' => 'CurrentMetricDataCollections', ], ], ], 'CurrentMetricResults' => [ 'type' => 'list', 'member' => [ 'shape' => 'CurrentMetricResult', ], ], 'CurrentMetricSortCriteria' => [ 'type' => 'structure', 'members' => [ 'SortByMetric' => [ 'shape' => 'CurrentMetricName', ], 'SortOrder' => [ 'shape' => 'SortOrder', ], ], ], 'CurrentMetricSortCriteriaMaxOne' => [ 'type' => 'list', 'member' => [ 'shape' => 'CurrentMetricSortCriteria', ], 'max' => 1, 'min' => 0, ], 'CurrentMetrics' => [ 'type' => 'list', 'member' => [ 'shape' => 'CurrentMetric', ], ], 'DataSetId' => [ 'type' => 'string', 'max' => 255, 'min' => 1, ], 'DataSetIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'DataSetId', ], ], 'DateReference' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ReferenceKey', ], 'Value' => [ 'shape' => 'ReferenceValue', ], ], ], 'DeactivateEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', 'EvaluationFormVersion', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], ], ], 'DeactivateEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormId', 'EvaluationFormArn', 'EvaluationFormVersion', ], 'members' => [ 'EvaluationFormId' => [ 'shape' => 'ResourceId', ], 'EvaluationFormArn' => [ 'shape' => 'ARN', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], ], ], 'DefaultVocabulary' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'LanguageCode', 'VocabularyId', 'VocabularyName', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'LanguageCode' => [ 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=> 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], ], ], 'DeleteViewRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], ], ], 'DeleteViewResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteViewVersionRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', 'ViewVersion', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'ViewVersion' => [ 'shape' => 'ViewVersion', 'location' => 'uri', 'locationName' => 'ViewVersion', ], ], ], 'DeleteViewVersionResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteVocabularyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'VocabularyId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', 'location' => 'uri', 'locationName' => 'VocabularyId', ], ], ], 'DeleteVocabularyResponse' => [ 'type' => 'structure', 'required' => [ 'VocabularyArn', 'VocabularyId', 'State', ], 'members' => [ 'VocabularyArn' => [ 'shape' => 'ARN', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', ], 'State' => [ 'shape' => 'VocabularyState', ], ], ], 'DescribeAgentStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AgentStatusId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AgentStatusId' => [ 'shape' => 'AgentStatusId', 'location' => 'uri', 'locationName' => 'AgentStatusId', ], ], ], 'DescribeAgentStatusResponse' => [ 'type' => 'structure', 'members' => [ 'AgentStatus' => [ 'shape' => 'AgentStatus', ], ], ], 'DescribeContactEvaluationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationId', ], ], ], 'DescribeContactEvaluationResponse' => [ 'type' => 'structure', 'required' => [ 'Evaluation', 'EvaluationForm', ], 'members' => [ 'Evaluation' => [ 'shape' => 'Evaluation', ], 'EvaluationForm' => [ 'shape' => 'EvaluationFormContent', ], ], ], 'DescribeContactFlowModuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowModuleId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowModuleId' => [ 'shape' => 'ContactFlowModuleId', 'location' => 'uri', 'locationName' => 'ContactFlowModuleId', ], ], ], 'DescribeContactFlowModuleResponse' => [ 'type' => 'structure', 'members' => [ 'ContactFlowModule' => [ 'shape' => 'ContactFlowModule', ], ], ], 'DescribeContactFlowRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], ], ], 'DescribeContactFlowResponse' => [ 'type' => 'structure', 'members' => [ 'ContactFlow' => [ 'shape' => 'ContactFlow', ], ], ], 'DescribeContactRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], ], ], 'DescribeContactResponse' => [ 'type' => 'structure', 'members' => [ 'Contact' => [ 'shape' => 'Contact', ], ], ], 'DescribeEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', 'box' => true, 'location' => 'querystring', 'locationName' => 'version', ], ], ], 'DescribeEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationForm', ], 'members' => [ 'EvaluationForm' => [ 'shape' => 'EvaluationForm', ], ], ], 'DescribeHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', 'location' => 'uri', 'locationName' => 'HoursOfOperationId', ], ], ], 'DescribeHoursOfOperationResponse' => [ 'type' => 'structure', 'members' => [ 'HoursOfOperation' => [ 'shape' => 'HoursOfOperation', ], ], ], 'DescribeInstanceAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AttributeType', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AttributeType' => [ 'shape' => 'InstanceAttributeType', 'location' => 'uri', 'locationName' => 'AttributeType', ], ], ], 'DescribeInstanceAttributeResponse' => [ 'type' => 'structure', 'members' => [ 'Attribute' => [ 'shape' => 'Attribute', ], ], ], 'DescribeInstanceRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'DescribeInstanceResponse' => [ 'type' => 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'members' => [ 'ClaimedPhoneNumberSummary' => [ 'shape' => 'ClaimedPhoneNumberSummary', ], ], ], 'DescribePredefinedAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'PredefinedAttributeName', 'location' => 'uri', 'locationName' => 'Name', ], ], ], 'DescribePredefinedAttributeResponse' => [ 'type' => 'structure', 'members' => [ 'PredefinedAttribute' => [ 'shape' => 'PredefinedAttribute', ], ], ], 'DescribePromptRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'PromptId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'PromptId' => [ 'shape' => 'PromptId', 'location' => 'uri', 'locationName' => 'PromptId', ], ], ], 'DescribePromptResponse' => [ 'type' => 'structure', 'members' => [ 'Prompt' => [ 'shape' => 'Prompt', ], ], ], 'DescribeQueueRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], ], ], 'DescribeQueueResponse' => [ 'type' => 'structure', 'members' => [ 'Queue' => [ 'shape' => 'Queue', ], ], ], 'DescribeQuickConnectRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QuickConnectId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', 'location' => 'uri', 'locationName' => 'QuickConnectId', ], ], ], 'DescribeQuickConnectResponse' => [ 'type' => 'structure', 'members' => [ 'QuickConnect' => [ 'shape' => 'QuickConnect', ], ], ], 'DescribeRoutingProfileRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], ], ], 'DescribeRoutingProfileResponse' => [ 'type' => 'structure', 'members' => [ 'RoutingProfile' => [ 'shape' => 'RoutingProfile', ], ], ], 'DescribeRuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RuleId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RuleId' => [ 'shape' => 'RuleId', 'location' => 'uri', 'locationName' => 'RuleId', ], ], ], 'DescribeRuleResponse' => [ 'type' => 'structure', 'required' => [ 'Rule', ], 'members' => [ 'Rule' => [ 'shape' => 'Rule', ], ], ], 'DescribeSecurityProfileRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileId', 'InstanceId', ], 'members' => [ 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', 'location' => 'uri', 'locationName' => 'SecurityProfileId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'DescribeSecurityProfileResponse' => [ 'type' => 'structure', 'members' => [ 'SecurityProfile' => [ 'shape' => 'SecurityProfile', ], ], ], 'DescribeTrafficDistributionGroupRequest' => [ 'type' => 'structure', 'required' => [ 'TrafficDistributionGroupId', ], 'members' => [ 'TrafficDistributionGroupId' => [ 'shape' => 'TrafficDistributionGroupIdOrArn', 'location' => 'uri', 'locationName' => 'TrafficDistributionGroupId', ], ], ], 'DescribeTrafficDistributionGroupResponse' => [ 'type' => 'structure', 'members' => [ 'TrafficDistributionGroup' => [ 'shape' => 'TrafficDistributionGroup', ], ], ], 'DescribeUserHierarchyGroupRequest' => [ 'type' => 'structure', 'required' => [ 'HierarchyGroupId', 'InstanceId', ], 'members' => [ 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', 'location' => 'uri', 'locationName' => 'HierarchyGroupId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'DescribeUserHierarchyGroupResponse' => [ 'type' => 'structure', 'members' => [ 'HierarchyGroup' => [ 'shape' => 'HierarchyGroup', ], ], ], 'DescribeUserHierarchyStructureRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'DescribeUserHierarchyStructureResponse' => [ 'type' => 'structure', 'members' => [ 'HierarchyStructure' => [ 'shape' => 'HierarchyStructure', ], ], ], 'DescribeUserRequest' => [ 'type' => 'structure', 'required' => [ 'UserId', 'InstanceId', ], 'members' => [ 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'DescribeUserResponse' => [ 'type' => 'structure', 'members' => [ 'User' => [ 'shape' => 'User', ], ], ], 'DescribeViewRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], ], ], 'DescribeViewResponse' => [ 'type' => 'structure', 'members' => [ 'View' => [ 'shape' => 'View', ], ], ], 'DescribeVocabularyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'VocabularyId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', 'location' => 'uri', 'locationName' => 'VocabularyId', ], ], ], 'DescribeVocabularyResponse' => [ 'type' => 'structure', 'required' => [ 'Vocabulary', ], 'members' => [ 'Vocabulary' => [ 'shape' => 'Vocabulary', ], ], ], 'Description' => [ 'type' => 'string', 'max' => 4096, 'min' => 0, 'sensitive' => true, ], 'Description250' => [ 'type' => 'string', 'max' => 250, 'min' => 1, 'pattern' => '(^[\\S].*[\\S]$)|(^[\\S]$)', ], 'DestinationId' => [ 'type' => 'string', 'max' => 255, 'min' => 1, ], 'DestinationNotAllowedException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 403, ], 'exception' => true, ], 'Dimensions' => [ 'type' => 'structure', 'members' => [ 'Queue' => [ 'shape' => 'QueueReference', ], 'Channel' => [ 'shape' => 'Channel', ], 'RoutingProfile' => [ 'shape' => 'RoutingProfileReference', ], 'RoutingStepExpression' => [ 'shape' => 'RoutingExpression', ], ], ], 'DimensionsV2Key' => [ 'type' => 'string', ], 'DimensionsV2Map' => [ 'type' => 'map', 'key' => [ 'shape' => 'DimensionsV2Key', ], 'value' => [ 'shape' => 'DimensionsV2Value', ], ], 'DimensionsV2Value' => [ 'type' => 'string', ], 'DirectoryAlias' => [ 'type' => 'string', 'max' => 45, 'min' => 1, 'pattern' => '^(?!d-)([\\da-zA-Z]+)([-]*[\\da-zA-Z])*$', 'sensitive' => true, ], 'DirectoryId' => [ 'type' => 'string', 'max' => 12, 'min' => 12, 'pattern' => '^d-[0-9a-f]{10}$', ], 'DirectoryType' => [ 'type' => 'string', 'enum' => [ 'SAML', 'CONNECT_MANAGED', 'EXISTING_DIRECTORY', ], ], 'DirectoryUserId' => [ 'type' => 'string', ], 'DisassociateAnalyticsDataSetRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'DataSetId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'DataSetId' => [ 'shape' => 'DataSetId', ], 'TargetAccountId' => [ 'shape' => 'AWSAccountId', ], ], ], 'DisassociateApprovedOriginRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Origin', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Origin' => [ 'shape' => 'Origin', 'location' => 'querystring', 'locationName' => 'origin', ], ], ], 'DisassociateBotRequest' 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'PhoneNumberTypes' => [ 'shape' => 'PhoneNumberTypes', 'location' => 'querystring', 'locationName' => 'phoneNumberTypes', ], 'PhoneNumberCountryCodes' => [ 'shape' => 'PhoneNumberCountryCodes', 'location' => 'querystring', 'locationName' => 'phoneNumberCountryCodes', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListPhoneNumbersResponse' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberSummaryList' => [ 'shape' => 'PhoneNumberSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListPhoneNumbersSummary' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', ], 'PhoneNumberArn' => [ 'shape' => 'ARN', ], 'PhoneNumber' => [ 'shape' => 'PhoneNumber', ], 'PhoneNumberCountryCode' => [ 'shape' => 'PhoneNumberCountryCode', ], 'PhoneNumberType' => [ 'shape' => 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'NextToken2500' => [ 'type' => 'string', 'max' => 2500, 'min' => 1, ], 'NotificationContentType' => [ 'type' => 'string', 'enum' => [ 'PLAIN_TEXT', ], ], 'NotificationDeliveryType' => [ 'type' => 'string', 'enum' => [ 'EMAIL', ], ], 'NotificationRecipientType' => [ 'type' => 'structure', 'members' => [ 'UserTags' => [ 'shape' => 'UserTagMap', ], 'UserIds' => [ 'shape' => 'UserIdList', ], ], ], 'NumberReference' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ReferenceKey', ], 'Value' => [ 'shape' => 'ReferenceValue', ], ], ], 'NumericQuestionPropertyAutomationLabel' => [ 'type' => 'string', 'enum' => [ 'OVERALL_CUSTOMER_SENTIMENT_SCORE', 'OVERALL_AGENT_SENTIMENT_SCORE', 'NON_TALK_TIME', 'NON_TALK_TIME_PERCENTAGE', 'NUMBER_OF_INTERRUPTIONS', 'CONTACT_DURATION', 'AGENT_INTERACTION_DURATION', 'CUSTOMER_HOLD_TIME', ], ], 'NumericQuestionPropertyValueAutomation' => [ 'type' => 'structure', 'required' => [ 'Label', ], 'members' => [ 'Label' => [ 'shape' => 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'sensitive' => true, ], 'PauseContactRequest' => [ 'type' => 'structure', 'required' => [ 'ContactId', 'InstanceId', ], 'members' => [ 'ContactId' => [ 'shape' => 'ContactId', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], ], ], 'PauseContactResponse' => [ 'type' => 'structure', 'members' => [], ], 'Percentage' => [ 'type' => 'integer', 'max' => 100, 'min' => 0, ], 'Permission' => [ 'type' => 'string', 'max' => 128, 'min' => 1, ], 'PermissionsList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityProfilePermission', ], 'max' => 500, ], 'PersistentChat' => [ 'type' => 'structure', 'members' => [ 'RehydrationType' => [ 'shape' => 'RehydrationType', ], 'SourceContactId' => [ 'shape' => 'ContactId', ], ], ], 'PhoneNumber' => [ 'type' => 'string', 'pattern' => '\\\\+[1-9]\\\\d{1,14}$', ], 'PhoneNumberCountryCode' => [ 'type' => 'string', 'enum' => [ 'AF', 'AL', 'DZ', 'AS', 'AD', 'AO', 'AI', 'AQ', 'AG', 'AR', 'AM', 'AW', 'AU', 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'QuickConnectId' => [ 'shape' => 'QuickConnectId', ], 'RelatedContactId' => [ 'shape' => 'ContactId', ], ], ], 'StartTaskContactResponse' => [ 'type' => 'structure', 'members' => [ 'ContactId' => [ 'shape' => 'ContactId', ], ], ], 'StartWebRTCContactRequest' => [ 'type' => 'structure', 'required' => [ 'ContactFlowId', 'InstanceId', 'ParticipantDetails', ], 'members' => [ 'Attributes' => [ 'shape' => 'Attributes', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'AllowedCapabilities' => [ 'shape' => 'AllowedCapabilities', ], 'ParticipantDetails' => [ 'shape' => 'ParticipantDetails', ], 'RelatedContactId' => [ 'shape' => 'ContactId', ], 'References' => [ 'shape' => 'ContactReferences', ], 'Description' => [ 'shape' => 'Description', ], ], ], 'StartWebRTCContactResponse' => [ 'type' => 'structure', 'members' => [ 'ConnectionData' => [ 'shape' => 'ConnectionData', ], 'ContactId' => [ 'shape' => 'ContactId', ], 'ParticipantId' => [ 'shape' => 'ParticipantId', ], 'ParticipantToken' => [ 'shape' => 'ParticipantToken', ], ], ], 'Statistic' => [ 'type' => 'string', 'enum' => [ 'SUM', 'MAX', 'AVG', ], ], 'StopContactRecordingRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'InitialContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', ], 'InitialContactId' => [ 'shape' => 'ContactId', ], ], ], 'StopContactRecordingResponse' => [ 'type' => 'structure', 'members' => [], ], 'StopContactRequest' => [ 'type' => 'structure', 'required' => [ 'ContactId', 'InstanceId', ], 'members' => [ 'ContactId' => [ 'shape' => 'ContactId', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'DisconnectReason' => [ 'shape' => 'DisconnectReason', ], ], ], 'StopContactResponse' => [ 'type' => 'structure', 'members' => [], ], 'StopContactStreamingRequest' => [ 'type' => 'structure', 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'TelephonyConfig' => [ 'type' => 'structure', 'required' => [ 'Distributions', ], 'members' => [ 'Distributions' => [ 'shape' => 'DistributionList', ], ], ], 'TemplateId' => [ 'type' => 'string', 'max' => 500, 'min' => 1, ], 'Threshold' => [ 'type' => 'structure', 'members' => [ 'Comparison' => [ 'shape' => 'Comparison', ], 'ThresholdValue' => [ 'shape' => 'ThresholdValue', 'box' => true, ], ], ], 'ThresholdCollections' => [ 'type' => 'list', 'member' => [ 'shape' => 'ThresholdV2', ], 'max' => 1, ], 'ThresholdV2' => [ 'type' => 'structure', 'members' => [ 'Comparison' => [ 'shape' => 'ResourceArnOrId', ], 'ThresholdValue' => [ 'shape' => 'ThresholdValue', 'box' => true, ], ], ], 'ThresholdValue' => [ 'type' => 'double', ], 'ThrottlingException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 429, ], 'exception' => true, ], 'TimeZone' => [ 'type' => 'string', ], 'TimerEligibleParticipantRoles' => [ 'type' => 'string', 'enum' => [ 'CUSTOMER', 'AGENT', ], ], 'Timestamp' => [ 'type' => 'timestamp', ], 'TooManyRequestsException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 429, ], 'exception' => true, ], 'TotalCount' => [ 'type' => 'long', ], 'TotalPauseCount' => [ 'type' => 'integer', 'max' => 10, 'min' => 0, ], 'TotalPauseDurationInSeconds' => [ 'type' => 'integer', 'min' => 0, ], 'TrafficDistributionGroup' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'TrafficDistributionGroupId', ], 'Arn' => [ 'shape' => 'TrafficDistributionGroupArn', ], 'Name' => [ 'shape' => 'Name128', ], 'Description' => [ 'shape' => 'Description250', ], 'InstanceArn' => [ 'shape' => 'InstanceArn', ], 'Status' => [ 'shape' => 'TrafficDistributionGroupStatus', ], 'Tags' => [ 'shape' => 'TagMap', ], 'IsDefault' => [ 'shape' => 'Boolean', ], ], ], 'TrafficDistributionGroupArn' => [ 'type' => 'string', 'pattern' => 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'Status' => [ 'shape' => 'TrafficDistributionGroupStatus', ], 'IsDefault' => [ 'shape' => 'Boolean', ], ], ], 'TrafficDistributionGroupSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TrafficDistributionGroupSummary', ], 'max' => 10, 'min' => 0, ], 'TrafficDistributionGroupUserSummary' => [ 'type' => 'structure', 'members' => [ 'UserId' => [ 'shape' => 'UserId', ], ], ], 'TrafficDistributionGroupUserSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TrafficDistributionGroupUserSummary', ], 'max' => 10, 'min' => 0, ], 'TrafficType' => [ 'type' => 'string', 'enum' => [ 'GENERAL', 'CAMPAIGN', ], ], 'Transcript' => [ 'type' => 'structure', 'required' => [ 'Criteria', ], 'members' => [ 'Criteria' => [ 'shape' => 'TranscriptCriteriaList', ], 'MatchType' => [ 'shape' => 'SearchContactsMatchType', ], ], ], 'TranscriptCriteria' => [ 'type' => 'structure', 'required' => [ 'ParticipantRole', 'SearchText', 'MatchType', ], 'members' => [ 'ParticipantRole' => [ 'shape' => 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], 'UntagContactRequest' => [ 'type' => 'structure', 'required' => [ 'ContactId', 'InstanceId', 'TagKeys', ], 'members' => [ 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'TagKeys' => [ 'shape' => 'ContactTagKeys', 'location' => 'querystring', 'locationName' => 'TagKeys', ], ], ], 'UntagContactResponse' => [ 'type' => 'structure', 'members' => [], ], 'UntagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'resourceArn', 'tagKeys', ], 'members' => [ 'resourceArn' => [ 'shape' => 'ARN', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'tagKeys' => [ 'shape' => 'TagKeyList', 'location' => 'querystring', 'locationName' => 'tagKeys', ], ], ], 'UpdateAgentStatusDescription' => [ 'type' => 'string', 'max' => 250, 'min' => 0, ], 'UpdateAgentStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AgentStatusId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AgentStatusId' => [ 'shape' => 'AgentStatusId', 'location' => 'uri', 'locationName' => 'AgentStatusId', ], 'Name' => [ 'shape' => 'AgentStatusName', ], 'Description' => [ 'shape' => 'UpdateAgentStatusDescription', ], 'State' => [ 'shape' => 'AgentStatusState', ], 'DisplayOrder' => [ 'shape' => 'AgentStatusOrderNumber', 'box' => true, ], 'ResetOrderNumber' => [ 'shape' => 'Boolean', ], ], ], 'UpdateCaseActionDefinition' => [ 'type' => 'structure', 'required' => [ 'Fields', ], 'members' => [ 'Fields' => [ 'shape' => 'FieldValues', ], ], ], 'UpdateContactAttributesRequest' => [ 'type' => 'structure', 'required' => [ 'InitialContactId', 'InstanceId', 'Attributes', ], 'members' => [ 'InitialContactId' => [ 'shape' => 'ContactId', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'Attributes' => [ 'shape' => 'Attributes', ], ], ], 'UpdateContactAttributesResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactEvaluationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationId', ], 'Answers' => [ 'shape' => 'EvaluationAnswersInputMap', ], 'Notes' => [ 'shape' => 'EvaluationNotesMap', ], ], ], 'UpdateContactEvaluationResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationId', 'EvaluationArn', ], 'members' => [ 'EvaluationId' => [ 'shape' => 'ResourceId', ], 'EvaluationArn' => [ 'shape' => 'ARN', ], ], ], 'UpdateContactFlowContentRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], 'Content' => [ 'shape' => 'ContactFlowContent', ], ], ], 'UpdateContactFlowContentResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactFlowMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'Description' => [ 'shape' => 'ContactFlowDescription', ], 'ContactFlowState' => [ 'shape' => 'ContactFlowState', ], ], ], 'UpdateContactFlowMetadataResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactFlowModuleContentRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowModuleId', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowModuleId' => [ 'shape' => 'ContactFlowModuleId', 'location' => 'uri', 'locationName' => 'ContactFlowModuleId', ], 'Content' => [ 'shape' => 'ContactFlowModuleContent', ], ], ], 'UpdateContactFlowModuleContentResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactFlowModuleMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowModuleId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowModuleId' => [ 'shape' => 'ContactFlowModuleId', 'location' => 'uri', 'locationName' => 'ContactFlowModuleId', ], 'Name' => [ 'shape' => 'ContactFlowModuleName', ], 'Description' => [ 'shape' => 'ContactFlowModuleDescription', ], 'State' => [ 'shape' => 'ContactFlowModuleState', ], ], ], 'UpdateContactFlowModuleMetadataResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactFlowNameRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'Description' => [ 'shape' => 'ContactFlowDescription', ], ], ], 'UpdateContactFlowNameResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'Name' => [ 'shape' => 'Name', ], 'Description' => [ 'shape' => 'Description', ], 'References' => [ 'shape' => 'ContactReferences', ], ], ], 'UpdateContactResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactRoutingDataRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'QueueTimeAdjustmentSeconds' => [ 'shape' => 'QueueTimeAdjustmentSeconds', ], 'QueuePriority' => [ 'shape' => 'QueuePriority', ], ], ], 'UpdateContactRoutingDataResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactScheduleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'ScheduledTime', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', ], 'ScheduledTime' => [ 'shape' => 'Timestamp', ], ], ], 'UpdateContactScheduleResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', 'EvaluationFormVersion', 'Title', 'Items', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], 'CreateNewVersion' => [ 'shape' => 'BoxedBoolean', 'box' => true, ], 'Title' => [ 'shape' => 'EvaluationFormTitle', ], 'Description' => [ 'shape' => 'EvaluationFormDescription', ], 'Items' => [ 'shape' => 'EvaluationFormItemsList', ], 'ScoringStrategy' => [ 'shape' => 'EvaluationFormScoringStrategy', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'UpdateEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormId', 'EvaluationFormArn', 'EvaluationFormVersion', ], 'members' => [ 'EvaluationFormId' => [ 'shape' => 'ResourceId', ], 'EvaluationFormArn' => [ 'shape' => 'ARN', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], ], ], 'UpdateHoursOfOperationDescription' => [ 'type' => 'string', 'max' => 250, 'min' => 0, ], 'UpdateHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', 'location' => 'uri', 'locationName' => 'HoursOfOperationId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'UpdateHoursOfOperationDescription', ], 'TimeZone' => [ 'shape' => 'TimeZone', ], 'Config' => [ 'shape' => 'HoursOfOperationConfigList', ], ], ], 'UpdateInstanceAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AttributeType', 'Value', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AttributeType' => [ 'shape' => 'InstanceAttributeType', 'location' => 'uri', 'locationName' => 'AttributeType', ], 'Value' => [ 'shape' => 'InstanceAttributeValue', ], ], ], 'UpdateInstanceStorageConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AssociationId', 'ResourceType', 'StorageConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AssociationId' => [ 'shape' => 'AssociationId', 'location' => 'uri', 'locationName' => 'AssociationId', ], 'ResourceType' => [ 'shape' => 'InstanceStorageResourceType', 'location' => 'querystring', 'locationName' => 'resourceType', ], 'StorageConfig' => [ 'shape' => 'InstanceStorageConfig', ], ], ], 'UpdateParticipantRoleConfigChannelInfo' => [ 'type' => 'structure', 'members' => [ 'Chat' => [ 'shape' => 'ChatParticipantRoleConfig', ], ], 'union' => true, ], 'UpdateParticipantRoleConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'ChannelConfiguration', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'ChannelConfiguration' => [ 'shape' => 'UpdateParticipantRoleConfigChannelInfo', ], ], ], 'UpdateParticipantRoleConfigResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdatePhoneNumberMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneNumberId', ], 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', 'location' => 'uri', 'locationName' => 'PhoneNumberId', ], 'PhoneNumberDescription' => [ 'shape' => 'PhoneNumberDescription', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'UpdatePhoneNumberRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneNumberId', ], 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', 'location' => 'uri', 'locationName' => 'PhoneNumberId', ], 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'UpdatePhoneNumberResponse' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', ], 'PhoneNumberArn' => [ 'shape' => 'ARN', ], ], ], 'UpdatePredefinedAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'PredefinedAttributeName', 'location' => 'uri', 'locationName' => 'Name', ], 'Values' => [ 'shape' => 'PredefinedAttributeValues', ], ], ], 'UpdatePromptRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'PromptId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'PromptId' => [ 'shape' => 'PromptId', 'location' => 'uri', 'locationName' => 'PromptId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'PromptDescription', ], 'S3Uri' => [ 'shape' => 'S3Uri', ], ], ], 'UpdatePromptResponse' => [ 'type' => 'structure', 'members' => [ 'PromptARN' => [ 'shape' => 'ARN', ], 'PromptId' => [ 'shape' => 'PromptId', ], ], ], 'UpdateQueueHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', ], ], ], 'UpdateQueueMaxContactsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'MaxContacts' => [ 'shape' => 'QueueMaxContacts', 'box' => true, ], ], ], 'UpdateQueueNameRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'QueueDescription', ], ], ], 'UpdateQueueOutboundCallerConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', 'OutboundCallerConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'OutboundCallerConfig' => [ 'shape' => 'OutboundCallerConfig', ], ], ], 'UpdateQueueStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', 'Status', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'Status' => [ 'shape' => 'QueueStatus', ], ], ], 'UpdateQuickConnectConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QuickConnectId', 'QuickConnectConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', 'location' => 'uri', 'locationName' => 'QuickConnectId', ], 'QuickConnectConfig' => [ 'shape' => 'QuickConnectConfig', ], ], ], 'UpdateQuickConnectDescription' => [ 'type' => 'string', 'max' => 250, 'min' => 0, ], 'UpdateQuickConnectNameRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QuickConnectId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', 'location' => 'uri', 'locationName' => 'QuickConnectId', ], 'Name' => [ 'shape' => 'QuickConnectName', ], 'Description' => [ 'shape' => 'UpdateQuickConnectDescription', ], ], ], 'UpdateRoutingProfileAgentAvailabilityTimerRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'AgentAvailabilityTimer', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'AgentAvailabilityTimer' => [ 'shape' => 'AgentAvailabilityTimer', ], ], ], 'UpdateRoutingProfileConcurrencyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'MediaConcurrencies', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'MediaConcurrencies' => [ 'shape' => 'MediaConcurrencies', ], ], ], 'UpdateRoutingProfileDefaultOutboundQueueRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'DefaultOutboundQueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'DefaultOutboundQueueId' => [ 'shape' => 'QueueId', ], ], ], 'UpdateRoutingProfileNameRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'Name' => [ 'shape' => 'RoutingProfileName', ], 'Description' => [ 'shape' => 'RoutingProfileDescription', ], ], ], 'UpdateRoutingProfileQueuesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'QueueConfigs', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'QueueConfigs' => [ 'shape' => 'RoutingProfileQueueConfigList', ], ], ], 'UpdateRuleRequest' => [ 'type' => 'structure', 'required' => [ 'RuleId', 'InstanceId', 'Name', 'Function', 'Actions', 'PublishStatus', ], 'members' => [ 'RuleId' => [ 'shape' => 'RuleId', 'location' => 'uri', 'locationName' => 'RuleId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'RuleName', ], 'Function' => [ 'shape' => 'RuleFunction', ], 'Actions' => [ 'shape' => 'RuleActions', ], 'PublishStatus' => [ 'shape' => 'RulePublishStatus', ], ], ], 'UpdateSecurityProfileRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileId', 'InstanceId', ], 'members' => [ 'Description' => [ 'shape' => 'SecurityProfileDescription', ], 'Permissions' => [ 'shape' => 'PermissionsList', ], 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', 'location' => 'uri', 'locationName' => 'SecurityProfileId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AllowedAccessControlTags' => [ 'shape' => 'AllowedAccessControlTags', ], 'TagRestrictedResources' => [ 'shape' => 'TagRestrictedResourceList', ], 'Applications' => [ 'shape' => 'Applications', ], ], ], 'UpdateTaskTemplateRequest' => [ 'type' => 'structure', 'required' => [ 'TaskTemplateId', 'InstanceId', ], 'members' => [ 'TaskTemplateId' => [ 'shape' => 'TaskTemplateId', 'location' => 'uri', 'locationName' => 'TaskTemplateId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'TaskTemplateName', ], 'Description' => [ 'shape' => 'TaskTemplateDescription', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'Constraints' => [ 'shape' => 'TaskTemplateConstraints', ], 'Defaults' => [ 'shape' => 'TaskTemplateDefaults', ], 'Status' => [ 'shape' => 'TaskTemplateStatus', ], 'Fields' => [ 'shape' => 'TaskTemplateFields', ], ], ], 'UpdateTaskTemplateResponse' => [ 'type' => 'structure', 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'Id' => [ 'shape' => 'TaskTemplateId', ], 'Arn' => [ 'shape' => 'TaskTemplateArn', ], 'Name' => [ 'shape' => 'TaskTemplateName', ], 'Description' => [ 'shape' => 'TaskTemplateDescription', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'Constraints' => [ 'shape' => 'TaskTemplateConstraints', ], 'Defaults' => [ 'shape' => 'TaskTemplateDefaults', ], 'Fields' => [ 'shape' => 'TaskTemplateFields', ], 'Status' => [ 'shape' => 'TaskTemplateStatus', ], 'LastModifiedTime' => [ 'shape' => 'timestamp', ], 'CreatedTime' => [ 'shape' => 'timestamp', ], ], ], 'UpdateTrafficDistributionRequest' => [ 'type' => 'structure', 'required' => [ 'Id', ], 'members' => [ 'Id' => [ 'shape' => 'TrafficDistributionGroupIdOrArn', 'location' => 'uri', 'locationName' => 'Id', ], 'TelephonyConfig' => [ 'shape' => 'TelephonyConfig', ], 'SignInConfig' => [ 'shape' => 'SignInConfig', ], 'AgentConfig' => [ 'shape' => 'AgentConfig', ], ], ], 'UpdateTrafficDistributionResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateUserHierarchyGroupNameRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'HierarchyGroupId', 'InstanceId', ], 'members' => [ 'Name' => [ 'shape' => 'HierarchyGroupName', ], 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', 'location' => 'uri', 'locationName' => 'HierarchyGroupId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserHierarchyRequest' => [ 'type' => 'structure', 'required' => [ 'UserId', 'InstanceId', ], 'members' => [ 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserHierarchyStructureRequest' => [ 'type' => 'structure', 'required' => [ 'HierarchyStructure', 'InstanceId', ], 'members' => [ 'HierarchyStructure' => [ 'shape' => 'HierarchyStructureUpdate', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserIdentityInfoRequest' => [ 'type' => 'structure', 'required' => [ 'IdentityInfo', 'UserId', 'InstanceId', ], 'members' => [ 'IdentityInfo' => [ 'shape' => 'UserIdentityInfo', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserPhoneConfigRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneConfig', 'UserId', 'InstanceId', ], 'members' => [ 'PhoneConfig' => [ 'shape' => 'UserPhoneConfig', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserProficienciesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'UserId', 'UserProficiencies', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'UserProficiencies' => [ 'shape' => 'UserProficiencyList', ], ], ], 'UpdateUserRoutingProfileRequest' => [ 'type' => 'structure', 'required' => [ 'RoutingProfileId', 'UserId', 'InstanceId', ], 'members' => [ 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserSecurityProfilesRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileIds', 'UserId', 'InstanceId', ], 'members' => [ 'SecurityProfileIds' => [ 'shape' => 'SecurityProfileIds', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateViewContentRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', 'Status', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'Status' => [ 'shape' => 'ViewStatus', ], 'Content' => [ 'shape' => 'ViewInputContent', ], ], ], 'UpdateViewContentResponse' => [ 'type' => 'structure', 'members' => [ 'View' => [ 'shape' => 'View', ], ], ], 'UpdateViewMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'Name' => [ 'shape' => 'ViewName', ], 'Description' => [ 'shape' => 'ViewDescription', ], ], ], 'UpdateViewMetadataResponse' => [ 'type' => 'structure', 'members' => [], ], 'Url' => [ 'type' => 'string', ], 'UrlReference' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ReferenceKey', ], 'Value' => [ 'shape' => 'ReferenceValue', ], ], ], 'UseCase' => [ 'type' => 'structure', 'members' => [ 'UseCaseId' => [ 'shape' => 'UseCaseId', ], 'UseCaseArn' => [ 'shape' => 'ARN', ], 'UseCaseType' => [ 'shape' => 'UseCaseType', ], ], ], 'UseCaseId' => [ 'type' => 'string', 'max' => 200, 'min' => 1, ], 'UseCaseSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UseCase', ], ], 'UseCaseType' => [ 'type' => 'string', 'enum' => [ 'RULES_EVALUATION', 'CONNECT_CAMPAIGNS', ], ], 'User' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'UserId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Username' => [ 'shape' => 'AgentUsername', ], 'IdentityInfo' => [ 'shape' => 'UserIdentityInfo', ], 'PhoneConfig' => [ 'shape' => 'UserPhoneConfig', ], 'DirectoryUserId' => [ 'shape' => 'DirectoryUserId', ], 'SecurityProfileIds' => [ 'shape' => 'SecurityProfileIds', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'Tags' => [ 'shape' => 'TagMap', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'UserData' => [ 'type' => 'structure', 'members' => [ 'User' => [ 'shape' => 'UserReference', ], 'RoutingProfile' => [ 'shape' => 'RoutingProfileReference', ], 'HierarchyPath' => [ 'shape' => 'HierarchyPathReference', ], 'Status' => [ 'shape' => 'AgentStatusReference', ], 'AvailableSlotsByChannel' => [ 'shape' => 'ChannelToCountMap', ], 'MaxSlotsByChannel' => [ 'shape' => 'ChannelToCountMap', ], 'ActiveSlotsByChannel' => [ 'shape' => 'ChannelToCountMap', ], 'Contacts' => [ 'shape' => 'AgentContactReferenceList', ], 'NextStatus' => [ 'shape' => 'AgentStatusName', ], ], ], 'UserDataFilters' => [ 'type' => 'structure', 'members' => [ 'Queues' => [ 'shape' => 'Queues', ], 'ContactFilter' => [ 'shape' => 'ContactFilter', ], 'RoutingProfiles' => [ 'shape' => 'RoutingProfiles', ], 'Agents' => [ 'shape' => 'AgentsMinOneMaxHundred', ], 'UserHierarchyGroups' => [ 'shape' => 'UserDataHierarchyGroups', ], ], ], 'UserDataHierarchyGroups' => [ 'type' => 'list', 'member' => [ 'shape' => 'HierarchyGroupId', ], 'max' => 1, 'min' => 1, ], 'UserDataList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserData', ], ], 'UserId' => [ 'type' => 'string', ], 'UserIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserId', ], ], 'UserIdentityInfo' => [ 'type' => 'structure', 'members' => [ 'FirstName' => [ 'shape' => 'AgentFirstName', ], 'LastName' => [ 'shape' => 'AgentLastName', ], 'Email' => [ 'shape' => 'Email', ], 'SecondaryEmail' => [ 'shape' => 'Email', ], 'Mobile' => [ 'shape' => 'PhoneNumber', ], ], ], 'UserIdentityInfoLite' => [ 'type' => 'structure', 'members' => [ 'FirstName' => [ 'shape' => 'AgentFirstName', ], 'LastName' => [ 'shape' => 'AgentLastName', ], ], ], 'UserNotFoundException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 404, ], 'exception' => true, ], 'UserPhoneConfig' => [ 'type' => 'structure', 'required' => [ 'PhoneType', ], 'members' => [ 'PhoneType' => [ 'shape' => 'PhoneType', ], 'AutoAccept' => [ 'shape' => 'AutoAccept', ], 'AfterContactWorkTimeLimit' => [ 'shape' => 'AfterContactWorkTimeLimit', ], 'DeskPhoneNumber' => [ 'shape' => 'PhoneNumber', ], ], ], 'UserProficiency' => [ 'type' => 'structure', 'required' => [ 'AttributeName', 'AttributeValue', 'Level', ], 'members' => [ 'AttributeName' => [ 'shape' => 'PredefinedAttributeName', ], 'AttributeValue' => [ 'shape' => 'PredefinedAttributeStringValue', ], 'Level' => [ 'shape' => 'ProficiencyLevel', ], ], ], 'UserProficiencyDisassociate' => [ 'type' => 'structure', 'required' => [ 'AttributeName', 'AttributeValue', ], 'members' => [ 'AttributeName' => [ 'shape' => 'PredefinedAttributeName', ], 'AttributeValue' => [ 'shape' => 'PredefinedAttributeStringValue', ], ], ], 'UserProficiencyDisassociateList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserProficiencyDisassociate', ], ], 'UserProficiencyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserProficiency', ], ], 'UserQuickConnectConfig' => [ 'type' => 'structure', 'required' => [ 'UserId', 'ContactFlowId', ], 'members' => [ 'UserId' => [ 'shape' => 'UserId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], ], ], 'UserReference' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'UserId', ], 'Arn' => [ 'shape' => 'ARN', ], ], ], 'UserSearchConditionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserSearchCriteria', ], ], 'UserSearchCriteria' => [ 'type' => 'structure', 'members' => [ 'OrConditions' => [ 'shape' => 'UserSearchConditionList', ], 'AndConditions' => [ 'shape' => 'UserSearchConditionList', ], 'StringCondition' => [ 'shape' => 'StringCondition', ], 'HierarchyGroupCondition' => [ 'shape' => 'HierarchyGroupCondition', ], ], ], 'UserSearchFilter' => [ 'type' => 'structure', 'members' => [ 'TagFilter' => [ 'shape' => 'ControlPlaneTagFilter', ], ], ], 'UserSearchSummary' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'DirectoryUserId' => [ 'shape' => 'DirectoryUserId', ], 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'Id' => [ 'shape' => 'UserId', ], 'IdentityInfo' => [ 'shape' => 'UserIdentityInfoLite', ], 'PhoneConfig' => [ 'shape' => 'UserPhoneConfig', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], 'SecurityProfileIds' => [ 'shape' => 'SecurityProfileIds', ], 'Tags' => [ 'shape' => 'TagMap', ], 'Username' => [ 'shape' => 'AgentUsername', ], ], ], 'UserSearchSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserSearchSummary', ], ], 'UserSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'UserId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Username' => [ 'shape' => 'AgentUsername', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'UserSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserSummary', ], ], 'UserTagMap' => [ 'type' => 'map', 'key' => [ 'shape' => 'String', ], 'value' => [ 'shape' => 'String', ], ], 'Value' => [ 'type' => 'double', ], 'VersionNumber' => [ 'type' => 'integer', 'min' => 1, ], 'VideoCapability' => [ 'type' => 'string', 'enum' => [ 'SEND', ], ], 'View' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ViewId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'ViewName', ], 'Status' => [ 'shape' => 'ViewStatus', ], 'Type' => [ 'shape' => 'ViewType', ], 'Description' => [ 'shape' => 'ViewDescription', ], 'Version' => [ 'shape' => 'ViewVersion', ], 'VersionDescription' => [ 'shape' => 'ViewDescription', ], 'Content' => [ 'shape' => 'ViewContent', ], 'Tags' => [ 'shape' => 'TagMap', ], 'CreatedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'ViewContentSha256' => [ 'shape' => 'ViewContentSha256', ], ], ], 'ViewAction' => [ 'type' => 'string', 'max' => 255, 'min' => 1, 'pattern' => '^([\\p{L}\\p{N}_.:\\/=+\\-@()\']+[\\p{L}\\p{Z}\\p{N}_.:\\/=+\\-@()\']*)$', 'sensitive' => true, ], 'ViewActions' => [ 'type' => 'list', 'member' => [ 'shape' => 'ViewAction', ], ], 'ViewContent' => [ 'type' => 'structure', 'members' => [ 'InputSchema' => [ 'shape' => 'ViewInputSchema', ], 'Template' => [ 'shape' => 'ViewTemplate', ], 'Actions' => [ 'shape' => 'ViewActions', ], ], ], 'ViewContentSha256' => [ 'type' => 'string', 'max' => 64, 'min' => 1, 'pattern' => '^[a-zA-Z0-9]$', ], 'ViewDescription' => [ 'type' => 'string', 'max' => 4096, 'min' => 1, 'pattern' => '^([\\p{L}\\p{N}_.:\\/=+\\-@,()\']+[\\p{L}\\p{Z}\\p{N}_.:\\/=+\\-@,()\']*)$', ], 'ViewId' => [ 'type' => 'string', 'max' => 500, 'min' => 1, 'pattern' => '^[a-zA-Z0-9\\_\\-:\\/$]+$', ], 'ViewInputContent' => [ 'type' => 'structure', 'members' => [ 'Template' => [ 'shape' => 'ViewTemplate', ], 'Actions' => [ 'shape' => 'ViewActions', ], ], ], 'ViewInputSchema' => [ 'type' => 'string', 'sensitive' => true, ], 'ViewName' => [ 'type' => 'string', 'max' => 255, 'min' => 1, 'pattern' => '^([\\p{L}\\p{N}_.:\\/=+\\-@()\']+[\\p{L}\\p{Z}\\p{N}_.:\\/=+\\-@()\']*)$', 'sensitive' => true, ], 'ViewStatus' => [ 'type' => 'string', 'enum' => [ 'PUBLISHED', 'SAVED', ], ], 'ViewSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ViewId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'ViewName', ], 'Type' => [ 'shape' => 'ViewType', ], 'Status' => [ 'shape' => 'ViewStatus', ], 'Description' => [ 'shape' => 'ViewDescription', ], ], ], 'ViewTemplate' => [ 'type' => 'string', ], 'ViewType' => [ 'type' => 'string', 'enum' => [ 'CUSTOMER_MANAGED', 'AWS_MANAGED', ], ], 'ViewVersion' => [ 'type' => 'integer', ], 'ViewVersionSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ViewId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Description' => [ 'shape' => 'ViewDescription', ], 'Name' => [ 'shape' => 'ViewName', ], 'Type' => [ 'shape' => 'ViewType', ], 'Version' => [ 'shape' => 'ViewVersion', ], 'VersionDescription' => [ 'shape' => 'ViewDescription', ], ], ], 'ViewVersionSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ViewVersionSummary', ], ], 'ViewsClientToken' => [ 'type' => 'string', 'max' => 500, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:\\/=+\\-@]*)$', ], 'ViewsInstanceId' => [ 'type' => 'string', 'max' => 100, 'min' => 1, 'pattern' => '^[a-zA-Z0-9\\_\\-:\\/]+$', ], 'ViewsNextToken' => [ 'type' => 'string', 'max' => 4096, 'min' => 1, 'pattern' => '^[a-zA-Z0-9=\\/+_.-]+$', ], 'ViewsSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ViewSummary', ], ], 'Vocabulary' => [ 'type' => 'structure', 'required' => [ 'Name', 'Id', 'Arn', 'LanguageCode', 'State', 'LastModifiedTime', ], 'members' => [ 'Name' => [ 'shape' => 'VocabularyName', ], 'Id' => [ 'shape' => 'VocabularyId', ], 'Arn' => [ 'shape' => 'ARN', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], 'State' => [ 'shape' => 'VocabularyState', ], 'LastModifiedTime' => [ 'shape' => 'VocabularyLastModifiedTime', ], 'FailureReason' => [ 'shape' => 'VocabularyFailureReason', ], 'Content' => [ 'shape' => 'VocabularyContent', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'VocabularyContent' => [ 'type' => 'string', 'max' => 60000, 'min' => 1, ], 'VocabularyFailureReason' => [ 'type' => 'string', ], 'VocabularyId' => [ 'type' => 'string', 'max' => 500, 'min' => 1, ], 'VocabularyLanguageCode' => [ 'type' => 'string', 'enum' => [ 'ar-AE', 'de-CH', 'de-DE', 'en-AB', 'en-AU', 'en-GB', 'en-IE', 'en-IN', 'en-US', 'en-WL', 'es-ES', 'es-US', 'fr-CA', 'fr-FR', 'hi-IN', 'it-IT', 'ja-JP', 'ko-KR', 'pt-BR', 'pt-PT', 'zh-CN', 'en-NZ', 'en-ZA', ], ], 'VocabularyLastModifiedTime' => [ 'type' => 'timestamp', ], 'VocabularyName' => [ 'type' => 'string', 'max' => 140, 'min' => 1, 'pattern' => '^[0-9a-zA-Z._-]+', ], 'VocabularyNextToken' => [ 'type' => 'string', 'max' => 131070, 'min' => 1, 'pattern' => '.*\\S.*', ], 'VocabularyState' => [ 'type' => 'string', 'enum' => [ 'CREATION_IN_PROGRESS', 'ACTIVE', 'CREATION_FAILED', 'DELETE_IN_PROGRESS', ], ], 'VocabularySummary' => [ 'type' => 'structure', 'required' => [ 'Name', 'Id', 'Arn', 'LanguageCode', 'State', 'LastModifiedTime', ], 'members' => [ 'Name' => [ 'shape' => 'VocabularyName', ], 'Id' => [ 'shape' => 'VocabularyId', ], 'Arn' => [ 'shape' => 'ARN', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], 'State' => [ 'shape' => 'VocabularyState', ], 'LastModifiedTime' => [ 'shape' => 'VocabularyLastModifiedTime', ], 'FailureReason' => [ 'shape' => 'VocabularyFailureReason', ], ], ], 'VocabularySummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VocabularySummary', ], ], 'VoiceRecordingConfiguration' => [ 'type' => 'structure', 'members' => [ 'VoiceRecordingTrack' => [ 'shape' => 'VoiceRecordingTrack', ], ], ], 'VoiceRecordingTrack' => [ 'type' => 'string', 'enum' => [ 'FROM_AGENT', 'TO_AGENT', 'ALL', ], ], 'WisdomInfo' => [ 'type' => 'structure', 'members' => [ 'SessionArn' => [ 'shape' => 'ARN', ], ], ], 'resourceArnListMaxLimit100' => [ 'type' => 'list', 'member' => [ 'shape' => 'ARN', ], 'max' => 100, 'min' => 1, ], 'timestamp' => [ 'type' => 'timestamp', ], ],]; +return [ 'version' => '2.0', 'metadata' => [ 'apiVersion' => '2017-08-08', 'endpointPrefix' => 'connect', 'jsonVersion' => '1.1', 'protocol' => 'rest-json', 'serviceAbbreviation' => 'Amazon Connect', 'serviceFullName' => 'Amazon Connect Service', 'serviceId' => 'Connect', 'signatureVersion' => 'v4', 'signingName' => 'connect', 'uid' => 'connect-2017-08-08', ], 'operations' => [ 'ActivateEvaluationForm' => [ 'name' => 'ActivateEvaluationForm', 'http' => [ 'method' => 'POST', 'requestUri' => '/evaluation-forms/{InstanceId}/{EvaluationFormId}/activate', ], 'input' => [ 'shape' => 'ActivateEvaluationFormRequest', ], 'output' => [ 'shape' => 'ActivateEvaluationFormResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceConflictException', ], ], ], 'AssociateAnalyticsDataSet' => [ 'name' => 'AssociateAnalyticsDataSet', 'http' => [ 'method' => 'PUT', 'requestUri' => '/analytics-data/instance/{InstanceId}/association', ], 'input' => [ 'shape' => 'AssociateAnalyticsDataSetRequest', ], 'output' => [ 'shape' => 'AssociateAnalyticsDataSetResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'AssociateApprovedOrigin' => [ 'name' => 'AssociateApprovedOrigin', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/approved-origin', ], 'input' => [ 'shape' => 'AssociateApprovedOriginRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateBot' => [ 'name' => 'AssociateBot', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/bot', ], 'input' => [ 'shape' => 'AssociateBotRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateDefaultVocabulary' => [ 'name' => 'AssociateDefaultVocabulary', 'http' => [ 'method' => 'PUT', 'requestUri' => '/default-vocabulary/{InstanceId}/{LanguageCode}', ], 'input' => [ 'shape' => 'AssociateDefaultVocabularyRequest', ], 'output' => [ 'shape' => 'AssociateDefaultVocabularyResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'AssociateFlow' => [ 'name' => 'AssociateFlow', 'http' => [ 'method' => 'PUT', 'requestUri' => '/flow-associations/{InstanceId}', ], 'input' => [ 'shape' => 'AssociateFlowRequest', ], 'output' => [ 'shape' => 'AssociateFlowResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateInstanceStorageConfig' => [ 'name' => 'AssociateInstanceStorageConfig', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/storage-config', ], 'input' => [ 'shape' => 'AssociateInstanceStorageConfigRequest', ], 'output' => [ 'shape' => 'AssociateInstanceStorageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateLambdaFunction' => [ 'name' => 'AssociateLambdaFunction', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/lambda-function', ], 'input' => [ 'shape' => 'AssociateLambdaFunctionRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateLexBot' => [ 'name' => 'AssociateLexBot', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/lex-bot', ], 'input' => [ 'shape' => 'AssociateLexBotRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociatePhoneNumberContactFlow' => [ 'name' => 'AssociatePhoneNumberContactFlow', 'http' => [ 'method' => 'PUT', 'requestUri' => '/phone-number/{PhoneNumberId}/contact-flow', ], 'input' => [ 'shape' => 'AssociatePhoneNumberContactFlowRequest', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'AssociateQueueQuickConnects' => [ 'name' => 'AssociateQueueQuickConnects', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/associate-quick-connects', ], 'input' => [ 'shape' => 'AssociateQueueQuickConnectsRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'AssociateRoutingProfileQueues' => [ 'name' => 'AssociateRoutingProfileQueues', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/associate-queues', ], 'input' => [ 'shape' => 'AssociateRoutingProfileQueuesRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'AssociateSecurityKey' => [ 'name' => 'AssociateSecurityKey', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/security-key', ], 'input' => [ 'shape' => 'AssociateSecurityKeyRequest', ], 'output' => [ 'shape' => 'AssociateSecurityKeyResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'AssociateTrafficDistributionGroupUser' => [ 'name' => 'AssociateTrafficDistributionGroupUser', 'http' => [ 'method' => 'PUT', 'requestUri' => '/traffic-distribution-group/{TrafficDistributionGroupId}/user', ], 'input' => [ 'shape' => 'AssociateTrafficDistributionGroupUserRequest', ], 'output' => [ 'shape' => 'AssociateTrafficDistributionGroupUserResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InternalServiceException', ], ], 'idempotent' => true, ], 'AssociateUserProficiencies' => [ 'name' => 'AssociateUserProficiencies', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/associate-proficiencies', ], 'input' => [ 'shape' => 'AssociateUserProficienciesRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'BatchAssociateAnalyticsDataSet' => [ 'name' => 'BatchAssociateAnalyticsDataSet', 'http' => [ 'method' => 'PUT', 'requestUri' => '/analytics-data/instance/{InstanceId}/associations', ], 'input' => [ 'shape' => 'BatchAssociateAnalyticsDataSetRequest', ], 'output' => [ 'shape' => 'BatchAssociateAnalyticsDataSetResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'BatchDisassociateAnalyticsDataSet' => [ 'name' => 'BatchDisassociateAnalyticsDataSet', 'http' => [ 'method' => 'POST', 'requestUri' => '/analytics-data/instance/{InstanceId}/associations', ], 'input' => [ 'shape' => 'BatchDisassociateAnalyticsDataSetRequest', ], 'output' => [ 'shape' => 'BatchDisassociateAnalyticsDataSetResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'BatchGetFlowAssociation' => [ 'name' => 'BatchGetFlowAssociation', 'http' => [ 'method' => 'POST', 'requestUri' => '/flow-associations-batch/{InstanceId}', ], 'input' => [ 'shape' => 'BatchGetFlowAssociationRequest', ], 'output' => [ 'shape' => 'BatchGetFlowAssociationResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'BatchPutContact' => [ 'name' => 'BatchPutContact', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/batch/{InstanceId}', ], 'input' => [ 'shape' => 'BatchPutContactRequest', ], 'output' => [ 'shape' => 'BatchPutContactResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'IdempotencyException', ], ], 'idempotent' => true, ], 'ClaimPhoneNumber' => [ 'name' => 'ClaimPhoneNumber', 'http' => [ 'method' => 'POST', 'requestUri' => '/phone-number/claim', ], 'input' => [ 'shape' => 'ClaimPhoneNumberRequest', ], 'output' => [ 'shape' => 'ClaimPhoneNumberResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'CreateAgentStatus' => [ 'name' => 'CreateAgentStatus', 'http' => [ 'method' => 'PUT', 'requestUri' => '/agent-status/{InstanceId}', ], 'input' => [ 'shape' => 'CreateAgentStatusRequest', ], 'output' => [ 'shape' => 'CreateAgentStatusResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateContactFlow' => [ 'name' => 'CreateContactFlow', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact-flows/{InstanceId}', ], 'input' => [ 'shape' => 'CreateContactFlowRequest', ], 'output' => [ 'shape' => 'CreateContactFlowResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidContactFlowException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateContactFlowModule' => [ 'name' => 'CreateContactFlowModule', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact-flow-modules/{InstanceId}', ], 'input' => [ 'shape' => 'CreateContactFlowModuleRequest', ], 'output' => [ 'shape' => 'CreateContactFlowModuleResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidContactFlowModuleException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateEvaluationForm' => [ 'name' => 'CreateEvaluationForm', 'http' => [ 'method' => 'PUT', 'requestUri' => '/evaluation-forms/{InstanceId}', ], 'input' => [ 'shape' => 'CreateEvaluationFormRequest', ], 'output' => [ 'shape' => 'CreateEvaluationFormResponse', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ResourceConflictException', ], ], 'idempotent' => true, ], 'CreateHoursOfOperation' => [ 'name' => 'CreateHoursOfOperation', 'http' => [ 'method' => 'PUT', 'requestUri' => '/hours-of-operations/{InstanceId}', ], 'input' => [ 'shape' => 'CreateHoursOfOperationRequest', ], 'output' => [ 'shape' => 'CreateHoursOfOperationResponse', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateInstance' => [ 'name' => 'CreateInstance', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance', ], 'input' => [ 'shape' => 'CreateInstanceRequest', ], 'output' => [ 'shape' => 'CreateInstanceResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateIntegrationAssociation' => [ 'name' => 'CreateIntegrationAssociation', 'http' => [ 'method' => 'PUT', 'requestUri' => '/instance/{InstanceId}/integration-associations', ], 'input' => [ 'shape' => 'CreateIntegrationAssociationRequest', ], 'output' => [ 'shape' => 'CreateIntegrationAssociationResponse', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'CreateParticipant' => [ 'name' => 'CreateParticipant', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/create-participant', ], 'input' => [ 'shape' => 'CreateParticipantRequest', ], 'output' => [ 'shape' => 'CreateParticipantResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'CreatePersistentContactAssociation' => [ 'name' => 'CreatePersistentContactAssociation', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/persistent-contact-association/{InstanceId}/{InitialContactId}', ], 'input' => [ 'shape' => 'CreatePersistentContactAssociationRequest', ], 'output' => [ 'shape' => 'CreatePersistentContactAssociationResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreatePredefinedAttribute' => [ 'name' => 'CreatePredefinedAttribute', 'http' => [ 'method' => 'PUT', 'requestUri' => '/predefined-attributes/{InstanceId}', ], 'input' => [ 'shape' => 'CreatePredefinedAttributeRequest', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreatePrompt' => [ 'name' => 'CreatePrompt', 'http' => [ 'method' => 'PUT', 'requestUri' => '/prompts/{InstanceId}', ], 'input' => [ 'shape' => 'CreatePromptRequest', ], 'output' => [ 'shape' => 'CreatePromptResponse', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateQueue' => [ 'name' => 'CreateQueue', 'http' => [ 'method' => 'PUT', 'requestUri' => '/queues/{InstanceId}', ], 'input' => [ 'shape' => 'CreateQueueRequest', ], 'output' => [ 'shape' => 'CreateQueueResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateQuickConnect' => [ 'name' => 'CreateQuickConnect', 'http' => [ 'method' => 'PUT', 'requestUri' => '/quick-connects/{InstanceId}', ], 'input' => [ 'shape' => 'CreateQuickConnectRequest', ], 'output' => [ 'shape' => 'CreateQuickConnectResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'CreateRoutingProfile' => [ 'name' => 'CreateRoutingProfile', 'http' => [ 'method' => 'PUT', 'requestUri' => '/routing-profiles/{InstanceId}', ], 'input' => [ 'shape' => 'CreateRoutingProfileRequest', ], 'output' => [ 'shape' => 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'input' => [ 'shape' => 'DeleteUseCaseRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'DeleteUser' => [ 'name' => 'DeleteUser', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/users/{InstanceId}/{UserId}', ], 'input' => [ 'shape' => 'DeleteUserRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'DeleteUserHierarchyGroup' => [ 'name' => 'DeleteUserHierarchyGroup', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/user-hierarchy-groups/{InstanceId}/{HierarchyGroupId}', ], 'input' => [ 'shape' => 'DeleteUserHierarchyGroupRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 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'output' => [ 'shape' => 'DescribeVocabularyResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'DisassociateAnalyticsDataSet' => [ 'name' => 'DisassociateAnalyticsDataSet', 'http' => [ 'method' => 'POST', 'requestUri' => '/analytics-data/instance/{InstanceId}/association', ], 'input' => [ 'shape' => 'DisassociateAnalyticsDataSetRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'DisassociateApprovedOrigin' => [ 'name' => 'DisassociateApprovedOrigin', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/instance/{InstanceId}/approved-origin', ], 'input' => [ 'shape' => 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'requestUri' => '/agent-status/{InstanceId}', ], 'input' => [ 'shape' => 'ListAgentStatusRequest', ], 'output' => [ 'shape' => 'ListAgentStatusResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListAnalyticsDataAssociations' => [ 'name' => 'ListAnalyticsDataAssociations', 'http' => [ 'method' => 'GET', 'requestUri' => '/analytics-data/instance/{InstanceId}/association', ], 'input' => [ 'shape' => 'ListAnalyticsDataAssociationsRequest', ], 'output' => [ 'shape' => 'ListAnalyticsDataAssociationsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListApprovedOrigins' => [ 'name' => 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'/contact-evaluations/{InstanceId}', ], 'input' => [ 'shape' => 'ListContactEvaluationsRequest', ], 'output' => [ 'shape' => 'ListContactEvaluationsResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListContactFlowModules' => [ 'name' => 'ListContactFlowModules', 'http' => [ 'method' => 'GET', 'requestUri' => '/contact-flow-modules-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListContactFlowModulesRequest', ], 'output' => [ 'shape' => 'ListContactFlowModulesResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListContactFlows' => [ 'name' => 'ListContactFlows', 'http' => [ 'method' => 'GET', 'requestUri' => '/contact-flows-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListContactFlowsRequest', ], 'output' => [ 'shape' => 'ListContactFlowsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListContactReferences' => [ 'name' => 'ListContactReferences', 'http' => [ 'method' => 'GET', 'requestUri' => '/contact/references/{InstanceId}/{ContactId}', ], 'input' => [ 'shape' => 'ListContactReferencesRequest', ], 'output' => [ 'shape' => 'ListContactReferencesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListDefaultVocabularies' => [ 'name' => 'ListDefaultVocabularies', 'http' => [ 'method' => 'POST', 'requestUri' => '/default-vocabulary-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListDefaultVocabulariesRequest', ], 'output' => [ 'shape' => 'ListDefaultVocabulariesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'ListEvaluationFormVersions' => [ 'name' => 'ListEvaluationFormVersions', 'http' => [ 'method' => 'GET', 'requestUri' => '/evaluation-forms/{InstanceId}/{EvaluationFormId}/versions', ], 'input' => [ 'shape' => 'ListEvaluationFormVersionsRequest', ], 'output' => [ 'shape' => 'ListEvaluationFormVersionsResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListEvaluationForms' => [ 'name' => 'ListEvaluationForms', 'http' => [ 'method' => 'GET', 'requestUri' => '/evaluation-forms/{InstanceId}', ], 'input' => [ 'shape' => 'ListEvaluationFormsRequest', ], 'output' => [ 'shape' => 'ListEvaluationFormsResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListFlowAssociations' => [ 'name' => 'ListFlowAssociations', 'http' => [ 'method' => 'GET', 'requestUri' => '/flow-associations-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListFlowAssociationsRequest', ], 'output' => [ 'shape' => 'ListFlowAssociationsResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListHoursOfOperations' => [ 'name' => 'ListHoursOfOperations', 'http' => [ 'method' => 'GET', 'requestUri' => '/hours-of-operations-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListHoursOfOperationsRequest', ], 'output' => [ 'shape' => 'ListHoursOfOperationsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListInstanceAttributes' => [ 'name' => 'ListInstanceAttributes', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance/{InstanceId}/attributes', ], 'input' => [ 'shape' => 'ListInstanceAttributesRequest', ], 'output' => [ 'shape' => 'ListInstanceAttributesResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListInstanceStorageConfigs' => [ 'name' => 'ListInstanceStorageConfigs', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance/{InstanceId}/storage-configs', ], 'input' => [ 'shape' => 'ListInstanceStorageConfigsRequest', ], 'output' => [ 'shape' => 'ListInstanceStorageConfigsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListInstances' => [ 'name' => 'ListInstances', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance', ], 'input' => [ 'shape' => 'ListInstancesRequest', ], 'output' => [ 'shape' => 'ListInstancesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListIntegrationAssociations' => [ 'name' => 'ListIntegrationAssociations', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance/{InstanceId}/integration-associations', ], 'input' => [ 'shape' => 'ListIntegrationAssociationsRequest', ], 'output' => [ 'shape' => 'ListIntegrationAssociationsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListLambdaFunctions' => [ 'name' => 'ListLambdaFunctions', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance/{InstanceId}/lambda-functions', ], 'input' => [ 'shape' => 'ListLambdaFunctionsRequest', ], 'output' => [ 'shape' => 'ListLambdaFunctionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListLexBots' => [ 'name' => 'ListLexBots', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance/{InstanceId}/lex-bots', ], 'input' => [ 'shape' => 'ListLexBotsRequest', ], 'output' => [ 'shape' => 'ListLexBotsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListPhoneNumbers' => [ 'name' => 'ListPhoneNumbers', 'http' => [ 'method' => 'GET', 'requestUri' => '/phone-numbers-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListPhoneNumbersRequest', ], 'output' => [ 'shape' => 'ListPhoneNumbersResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListPhoneNumbersV2' => [ 'name' => 'ListPhoneNumbersV2', 'http' => [ 'method' => 'POST', 'requestUri' => '/phone-number/list', ], 'input' => [ 'shape' => 'ListPhoneNumbersV2Request', ], 'output' => [ 'shape' => 'ListPhoneNumbersV2Response', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'ListPredefinedAttributes' => [ 'name' => 'ListPredefinedAttributes', 'http' => [ 'method' => 'GET', 'requestUri' => '/predefined-attributes/{InstanceId}', ], 'input' => [ 'shape' => 'ListPredefinedAttributesRequest', ], 'output' => [ 'shape' => 'ListPredefinedAttributesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListPrompts' => [ 'name' => 'ListPrompts', 'http' => [ 'method' => 'GET', 'requestUri' => '/prompts-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListPromptsRequest', ], 'output' => [ 'shape' => 'ListPromptsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListQueueQuickConnects' => [ 'name' => 'ListQueueQuickConnects', 'http' => [ 'method' => 'GET', 'requestUri' => '/queues/{InstanceId}/{QueueId}/quick-connects', ], 'input' => [ 'shape' => 'ListQueueQuickConnectsRequest', ], 'output' => [ 'shape' => 'ListQueueQuickConnectsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListQueues' => [ 'name' => 'ListQueues', 'http' => [ 'method' => 'GET', 'requestUri' => '/queues-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListQueuesRequest', ], 'output' => [ 'shape' => 'ListQueuesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListQuickConnects' => [ 'name' => 'ListQuickConnects', 'http' => [ 'method' => 'GET', 'requestUri' => '/quick-connects/{InstanceId}', ], 'input' => [ 'shape' => 'ListQuickConnectsRequest', ], 'output' => [ 'shape' => 'ListQuickConnectsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListRealtimeContactAnalysisSegmentsV2' => [ 'name' => 'ListRealtimeContactAnalysisSegmentsV2', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/list-real-time-analysis-segments-v2/{InstanceId}/{ContactId}', ], 'input' => [ 'shape' => 'ListRealtimeContactAnalysisSegmentsV2Request', ], 'output' => [ 'shape' => 'ListRealtimeContactAnalysisSegmentsV2Response', ], 'errors' => [ [ 'shape' => 'OutputTypeNotFoundException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListRoutingProfileQueues' => [ 'name' => 'ListRoutingProfileQueues', 'http' => [ 'method' => 'GET', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/queues', ], 'input' => [ 'shape' => 'ListRoutingProfileQueuesRequest', ], 'output' => [ 'shape' => 'ListRoutingProfileQueuesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListRoutingProfiles' => [ 'name' => 'ListRoutingProfiles', 'http' => [ 'method' => 'GET', 'requestUri' => '/routing-profiles-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListRoutingProfilesRequest', ], 'output' => [ 'shape' => 'ListRoutingProfilesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListRules' => [ 'name' => 'ListRules', 'http' => [ 'method' => 'GET', 'requestUri' => '/rules/{InstanceId}', ], 'input' => [ 'shape' => 'ListRulesRequest', ], 'output' => [ 'shape' => 'ListRulesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], ], ], 'ListSecurityKeys' => [ 'name' => 'ListSecurityKeys', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance/{InstanceId}/security-keys', ], 'input' => [ 'shape' => 'ListSecurityKeysRequest', ], 'output' => [ 'shape' => 'ListSecurityKeysResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListSecurityProfileApplications' => [ 'name' => 'ListSecurityProfileApplications', 'http' => [ 'method' => 'GET', 'requestUri' => '/security-profiles-applications/{InstanceId}/{SecurityProfileId}', ], 'input' => [ 'shape' => 'ListSecurityProfileApplicationsRequest', ], 'output' => [ 'shape' => 'ListSecurityProfileApplicationsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListSecurityProfilePermissions' => [ 'name' => 'ListSecurityProfilePermissions', 'http' => [ 'method' => 'GET', 'requestUri' => '/security-profiles-permissions/{InstanceId}/{SecurityProfileId}', ], 'input' => [ 'shape' => 'ListSecurityProfilePermissionsRequest', ], 'output' => [ 'shape' => 'ListSecurityProfilePermissionsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListSecurityProfiles' => [ 'name' => 'ListSecurityProfiles', 'http' => [ 'method' => 'GET', 'requestUri' => '/security-profiles-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListSecurityProfilesRequest', ], 'output' => [ 'shape' => 'ListSecurityProfilesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListTagsForResource' => [ 'name' => 'ListTagsForResource', 'http' => [ 'method' => 'GET', 'requestUri' => '/tags/{resourceArn}', ], 'input' => [ 'shape' => 'ListTagsForResourceRequest', ], 'output' => [ 'shape' => 'ListTagsForResourceResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListTaskTemplates' => [ 'name' => 'ListTaskTemplates', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance/{InstanceId}/task/template', ], 'input' => [ 'shape' => 'ListTaskTemplatesRequest', ], 'output' => [ 'shape' => 'ListTaskTemplatesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListTrafficDistributionGroupUsers' => [ 'name' => 'ListTrafficDistributionGroupUsers', 'http' => [ 'method' => 'GET', 'requestUri' => '/traffic-distribution-group/{TrafficDistributionGroupId}/user', ], 'input' => [ 'shape' => 'ListTrafficDistributionGroupUsersRequest', ], 'output' => [ 'shape' => 'ListTrafficDistributionGroupUsersResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListTrafficDistributionGroups' => [ 'name' => 'ListTrafficDistributionGroups', 'http' => [ 'method' => 'GET', 'requestUri' => '/traffic-distribution-groups', ], 'input' => [ 'shape' => 'ListTrafficDistributionGroupsRequest', ], 'output' => [ 'shape' => 'ListTrafficDistributionGroupsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListUseCases' => [ 'name' => 'ListUseCases', 'http' => [ 'method' => 'GET', 'requestUri' => '/instance/{InstanceId}/integration-associations/{IntegrationAssociationId}/use-cases', ], 'input' => [ 'shape' => 'ListUseCasesRequest', ], 'output' => [ 'shape' => 'ListUseCasesResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'ListUserHierarchyGroups' => [ 'name' => 'ListUserHierarchyGroups', 'http' => [ 'method' => 'GET', 'requestUri' => '/user-hierarchy-groups-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListUserHierarchyGroupsRequest', ], 'output' => [ 'shape' => 'ListUserHierarchyGroupsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListUserProficiencies' => [ 'name' => 'ListUserProficiencies', 'http' => [ 'method' => 'GET', 'requestUri' => '/users/{InstanceId}/{UserId}/proficiencies', ], 'input' => [ 'shape' => 'ListUserProficienciesRequest', ], 'output' => [ 'shape' => 'ListUserProficienciesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListUsers' => [ 'name' => 'ListUsers', 'http' => [ 'method' => 'GET', 'requestUri' => '/users-summary/{InstanceId}', ], 'input' => [ 'shape' => 'ListUsersRequest', ], 'output' => [ 'shape' => 'ListUsersResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ListViewVersions' => [ 'name' => 'ListViewVersions', 'http' => [ 'method' => 'GET', 'requestUri' => '/views/{InstanceId}/{ViewId}/versions', ], 'input' => [ 'shape' => 'ListViewVersionsRequest', ], 'output' => [ 'shape' => 'ListViewVersionsResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], ], ], 'ListViews' => [ 'name' => 'ListViews', 'http' => [ 'method' => 'GET', 'requestUri' => '/views/{InstanceId}', ], 'input' => [ 'shape' => 'ListViewsRequest', ], 'output' => [ 'shape' => 'ListViewsResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], ], ], 'MonitorContact' => [ 'name' => 'MonitorContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/monitor', ], 'input' => [ 'shape' => 'MonitorContactRequest', ], 'output' => [ 'shape' => 'MonitorContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'PauseContact' => [ 'name' => 'PauseContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/pause', ], 'input' => [ 'shape' => 'PauseContactRequest', ], 'output' => [ 'shape' => 'PauseContactResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ConflictException', ], ], ], 'PutUserStatus' => [ 'name' => 'PutUserStatus', 'http' => [ 'method' => 'PUT', 'requestUri' => '/users/{InstanceId}/{UserId}/status', ], 'input' => [ 'shape' => 'PutUserStatusRequest', ], 'output' => [ 'shape' => 'PutUserStatusResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'ReleasePhoneNumber' => [ 'name' => 'ReleasePhoneNumber', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/phone-number/{PhoneNumberId}', ], 'input' => [ 'shape' => 'ReleasePhoneNumberRequest', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceInUseException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'ReplicateInstance' => [ 'name' => 'ReplicateInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/instance/{InstanceId}/replicate', ], 'input' => [ 'shape' => 'ReplicateInstanceRequest', ], 'output' => [ 'shape' => 'ReplicateInstanceResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceNotReadyException', ], [ 'shape' => 'ResourceConflictException', ], ], ], 'ResumeContact' => [ 'name' => 'ResumeContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/resume', ], 'input' => [ 'shape' => 'ResumeContactRequest', ], 'output' => [ 'shape' => 'ResumeContactResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ConflictException', ], ], ], 'ResumeContactRecording' => [ 'name' => 'ResumeContactRecording', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/resume-recording', ], 'input' => [ 'shape' => 'ResumeContactRecordingRequest', ], 'output' => [ 'shape' => 'ResumeContactRecordingResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchAvailablePhoneNumbers' => [ 'name' => 'SearchAvailablePhoneNumbers', 'http' => [ 'method' => 'POST', 'requestUri' => '/phone-number/search-available', ], 'input' => [ 'shape' => 'SearchAvailablePhoneNumbersRequest', ], 'output' => [ 'shape' => 'SearchAvailablePhoneNumbersResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'SearchContacts' => [ 'name' => 'SearchContacts', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-contacts', ], 'input' => [ 'shape' => 'SearchContactsRequest', ], 'output' => [ 'shape' => 'SearchContactsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'SearchHoursOfOperations' => [ 'name' => 'SearchHoursOfOperations', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-hours-of-operations', ], 'input' => [ 'shape' => 'SearchHoursOfOperationsRequest', ], 'output' => [ 'shape' => 'SearchHoursOfOperationsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchPredefinedAttributes' => [ 'name' => 'SearchPredefinedAttributes', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-predefined-attributes', ], 'input' => [ 'shape' => 'SearchPredefinedAttributesRequest', ], 'output' => [ 'shape' => 'SearchPredefinedAttributesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchPrompts' => [ 'name' => 'SearchPrompts', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-prompts', ], 'input' => [ 'shape' => 'SearchPromptsRequest', ], 'output' => [ 'shape' => 'SearchPromptsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchQueues' => [ 'name' => 'SearchQueues', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-queues', ], 'input' => [ 'shape' => 'SearchQueuesRequest', ], 'output' => [ 'shape' => 'SearchQueuesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchQuickConnects' => [ 'name' => 'SearchQuickConnects', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-quick-connects', ], 'input' => [ 'shape' => 'SearchQuickConnectsRequest', ], 'output' => [ 'shape' => 'SearchQuickConnectsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchResourceTags' => [ 'name' => 'SearchResourceTags', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-resource-tags', ], 'input' => [ 'shape' => 'SearchResourceTagsRequest', ], 'output' => [ 'shape' => 'SearchResourceTagsResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'MaximumResultReturnedException', ], ], ], 'SearchRoutingProfiles' => [ 'name' => 'SearchRoutingProfiles', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-routing-profiles', ], 'input' => [ 'shape' => 'SearchRoutingProfilesRequest', ], 'output' => [ 'shape' => 'SearchRoutingProfilesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchSecurityProfiles' => [ 'name' => 'SearchSecurityProfiles', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-security-profiles', ], 'input' => [ 'shape' => 'SearchSecurityProfilesRequest', ], 'output' => [ 'shape' => 'SearchSecurityProfilesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchUsers' => [ 'name' => 'SearchUsers', 'http' => [ 'method' => 'POST', 'requestUri' => '/search-users', ], 'input' => [ 'shape' => 'SearchUsersRequest', ], 'output' => [ 'shape' => 'SearchUsersResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SearchVocabularies' => [ 'name' => 'SearchVocabularies', 'http' => [ 'method' => 'POST', 'requestUri' => '/vocabulary-summary/{InstanceId}', ], 'input' => [ 'shape' => 'SearchVocabulariesRequest', ], 'output' => [ 'shape' => 'SearchVocabulariesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'SendChatIntegrationEvent' => [ 'name' => 'SendChatIntegrationEvent', 'http' => [ 'method' => 'POST', 'requestUri' => '/chat-integration-event', ], 'input' => [ 'shape' => 'SendChatIntegrationEventRequest', ], 'output' => [ 'shape' => 'SendChatIntegrationEventResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'StartChatContact' => [ 'name' => 'StartChatContact', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/chat', ], 'input' => [ 'shape' => 'StartChatContactRequest', ], 'output' => [ 'shape' => 'StartChatContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'LimitExceededException', ], ], ], 'StartContactEvaluation' => [ 'name' => 'StartContactEvaluation', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact-evaluations/{InstanceId}', ], 'input' => [ 'shape' => 'StartContactEvaluationRequest', ], 'output' => [ 'shape' => 'StartContactEvaluationResponse', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ResourceConflictException', ], ], 'idempotent' => true, ], 'StartContactRecording' => [ 'name' => 'StartContactRecording', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/start-recording', ], 'input' => [ 'shape' => 'StartContactRecordingRequest', ], 'output' => [ 'shape' => 'StartContactRecordingResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'StartContactStreaming' => [ 'name' => 'StartContactStreaming', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/start-streaming', ], 'input' => [ 'shape' => 'StartContactStreamingRequest', ], 'output' => [ 'shape' => 'StartContactStreamingResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'LimitExceededException', ], ], ], 'StartOutboundVoiceContact' => [ 'name' => 'StartOutboundVoiceContact', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/outbound-voice', ], 'input' => [ 'shape' => 'StartOutboundVoiceContactRequest', ], 'output' => [ 'shape' => 'StartOutboundVoiceContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'DestinationNotAllowedException', ], [ 'shape' => 'OutboundContactNotPermittedException', ], ], ], 'StartTaskContact' => [ 'name' => 'StartTaskContact', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/task', ], 'input' => [ 'shape' => 'StartTaskContactRequest', ], 'output' => [ 'shape' => 'StartTaskContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'StartWebRTCContact' => [ 'name' => 'StartWebRTCContact', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/webrtc', ], 'input' => [ 'shape' => 'StartWebRTCContactRequest', ], 'output' => [ 'shape' => 'StartWebRTCContactResponse', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ResourceNotFoundException', ], ], ], 'StopContact' => [ 'name' => 'StopContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/stop', ], 'input' => [ 'shape' => 'StopContactRequest', ], 'output' => [ 'shape' => 'StopContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ContactNotFoundException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'StopContactRecording' => [ 'name' => 'StopContactRecording', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/stop-recording', ], 'input' => [ 'shape' => 'StopContactRecordingRequest', ], 'output' => [ 'shape' => 'StopContactRecordingResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'StopContactStreaming' => [ 'name' => 'StopContactStreaming', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/stop-streaming', ], 'input' => [ 'shape' => 'StopContactStreamingRequest', ], 'output' => [ 'shape' => 'StopContactStreamingResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'SubmitContactEvaluation' => [ 'name' => 'SubmitContactEvaluation', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-evaluations/{InstanceId}/{EvaluationId}/submit', ], 'input' => [ 'shape' => 'SubmitContactEvaluationRequest', ], 'output' => [ 'shape' => 'SubmitContactEvaluationResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceConflictException', ], ], ], 'SuspendContactRecording' => [ 'name' => 'SuspendContactRecording', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/suspend-recording', ], 'input' => [ 'shape' => 'SuspendContactRecordingRequest', ], 'output' => [ 'shape' => 'SuspendContactRecordingResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'TagContact' => [ 'name' => 'TagContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/tags', ], 'input' => [ 'shape' => 'TagContactRequest', ], 'output' => [ 'shape' => 'TagContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], 'idempotent' => true, ], 'TagResource' => [ 'name' => 'TagResource', 'http' => [ 'method' => 'POST', 'requestUri' => '/tags/{resourceArn}', ], 'input' => [ 'shape' => 'TagResourceRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'TransferContact' => [ 'name' => 'TransferContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/transfer', ], 'input' => [ 'shape' => 'TransferContactRequest', ], 'output' => [ 'shape' => 'TransferContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UntagContact' => [ 'name' => 'UntagContact', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/contact/tags/{InstanceId}/{ContactId}', ], 'input' => [ 'shape' => 'UntagContactRequest', ], 'output' => [ 'shape' => 'UntagContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], 'idempotent' => true, ], 'UntagResource' => [ 'name' => 'UntagResource', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/tags/{resourceArn}', ], 'input' => [ 'shape' => 'UntagResourceRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'UpdateAgentStatus' => [ 'name' => 'UpdateAgentStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/agent-status/{InstanceId}/{AgentStatusId}', ], 'input' => [ 'shape' => 'UpdateAgentStatusRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContact' => [ 'name' => 'UpdateContact', 'http' => [ 'method' => 'POST', 'requestUri' => '/contacts/{InstanceId}/{ContactId}', ], 'input' => [ 'shape' => 'UpdateContactRequest', ], 'output' => [ 'shape' => 'UpdateContactResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'UpdateContactAttributes' => [ 'name' => 'UpdateContactAttributes', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/attributes', ], 'input' => [ 'shape' => 'UpdateContactAttributesRequest', ], 'output' => [ 'shape' => 'UpdateContactAttributesResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactEvaluation' => [ 'name' => 'UpdateContactEvaluation', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-evaluations/{InstanceId}/{EvaluationId}', ], 'input' => [ 'shape' => 'UpdateContactEvaluationRequest', ], 'output' => [ 'shape' => 'UpdateContactEvaluationResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceConflictException', ], ], ], 'UpdateContactFlowContent' => [ 'name' => 'UpdateContactFlowContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flows/{InstanceId}/{ContactFlowId}/content', ], 'input' => [ 'shape' => 'UpdateContactFlowContentRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowContentResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidContactFlowException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactFlowMetadata' => [ 'name' => 'UpdateContactFlowMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flows/{InstanceId}/{ContactFlowId}/metadata', ], 'input' => [ 'shape' => 'UpdateContactFlowMetadataRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowMetadataResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactFlowModuleContent' => [ 'name' => 'UpdateContactFlowModuleContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flow-modules/{InstanceId}/{ContactFlowModuleId}/content', ], 'input' => [ 'shape' => 'UpdateContactFlowModuleContentRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowModuleContentResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidContactFlowModuleException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactFlowModuleMetadata' => [ 'name' => 'UpdateContactFlowModuleMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flow-modules/{InstanceId}/{ContactFlowModuleId}/metadata', ], 'input' => [ 'shape' => 'UpdateContactFlowModuleMetadataRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowModuleMetadataResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactFlowName' => [ 'name' => 'UpdateContactFlowName', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact-flows/{InstanceId}/{ContactFlowId}/name', ], 'input' => [ 'shape' => 'UpdateContactFlowNameRequest', ], 'output' => [ 'shape' => 'UpdateContactFlowNameResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateContactRoutingData' => [ 'name' => 'UpdateContactRoutingData', 'http' => [ 'method' => 'POST', 'requestUri' => '/contacts/{InstanceId}/{ContactId}/routing-data', ], 'input' => [ 'shape' => 'UpdateContactRoutingDataRequest', ], 'output' => [ 'shape' => 'UpdateContactRoutingDataResponse', ], 'errors' => [ [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'UpdateContactSchedule' => [ 'name' => 'UpdateContactSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/contact/schedule', ], 'input' => [ 'shape' => 'UpdateContactScheduleRequest', ], 'output' => [ 'shape' => 'UpdateContactScheduleResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'LimitExceededException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateEvaluationForm' => [ 'name' => 'UpdateEvaluationForm', 'http' => [ 'method' => 'PUT', 'requestUri' => '/evaluation-forms/{InstanceId}/{EvaluationFormId}', ], 'input' => [ 'shape' => 'UpdateEvaluationFormRequest', ], 'output' => [ 'shape' => 'UpdateEvaluationFormResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'ResourceConflictException', ], ], 'idempotent' => true, ], 'UpdateHoursOfOperation' => [ 'name' => 'UpdateHoursOfOperation', 'http' => [ 'method' => 'POST', 'requestUri' => '/hours-of-operations/{InstanceId}/{HoursOfOperationId}', ], 'input' => [ 'shape' => 'UpdateHoursOfOperationRequest', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateInstanceAttribute' => [ 'name' => 'UpdateInstanceAttribute', 'http' => [ 'method' => 'POST', 'requestUri' => '/instance/{InstanceId}/attribute/{AttributeType}', ], 'input' => [ 'shape' => 'UpdateInstanceAttributeRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'UpdateInstanceStorageConfig' => [ 'name' => 'UpdateInstanceStorageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/instance/{InstanceId}/storage-config/{AssociationId}', ], 'input' => [ 'shape' => 'UpdateInstanceStorageConfigRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ThrottlingException', ], ], ], 'UpdateParticipantRoleConfig' => [ 'name' => 'UpdateParticipantRoleConfig', 'http' => [ 'method' => 'PUT', 'requestUri' => '/contact/participant-role-config/{InstanceId}/{ContactId}', ], 'input' => [ 'shape' => 'UpdateParticipantRoleConfigRequest', ], 'output' => [ 'shape' => 'UpdateParticipantRoleConfigResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdatePhoneNumber' => [ 'name' => 'UpdatePhoneNumber', 'http' => [ 'method' => 'PUT', 'requestUri' => '/phone-number/{PhoneNumberId}', ], 'input' => [ 'shape' => 'UpdatePhoneNumberRequest', ], 'output' => [ 'shape' => 'UpdatePhoneNumberResponse', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ResourceInUseException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'AccessDeniedException', ], ], ], 'UpdatePhoneNumberMetadata' => [ 'name' => 'UpdatePhoneNumberMetadata', 'http' => [ 'method' => 'PUT', 'requestUri' => '/phone-number/{PhoneNumberId}/metadata', ], 'input' => [ 'shape' => 'UpdatePhoneNumberMetadataRequest', ], 'errors' => [ [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceInUseException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdatePredefinedAttribute' => [ 'name' => 'UpdatePredefinedAttribute', 'http' => [ 'method' => 'POST', 'requestUri' => '/predefined-attributes/{InstanceId}/{Name}', ], 'input' => [ 'shape' => 'UpdatePredefinedAttributeRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdatePrompt' => [ 'name' => 'UpdatePrompt', 'http' => [ 'method' => 'POST', 'requestUri' => '/prompts/{InstanceId}/{PromptId}', ], 'input' => [ 'shape' => 'UpdatePromptRequest', ], 'output' => [ 'shape' => 'UpdatePromptResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueHoursOfOperation' => [ 'name' => 'UpdateQueueHoursOfOperation', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/hours-of-operation', ], 'input' => [ 'shape' => 'UpdateQueueHoursOfOperationRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueMaxContacts' => [ 'name' => 'UpdateQueueMaxContacts', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/max-contacts', ], 'input' => [ 'shape' => 'UpdateQueueMaxContactsRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueName' => [ 'name' => 'UpdateQueueName', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/name', ], 'input' => [ 'shape' => 'UpdateQueueNameRequest', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueOutboundCallerConfig' => [ 'name' => 'UpdateQueueOutboundCallerConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/outbound-caller-config', ], 'input' => [ 'shape' => 'UpdateQueueOutboundCallerConfigRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQueueStatus' => [ 'name' => 'UpdateQueueStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/queues/{InstanceId}/{QueueId}/status', ], 'input' => [ 'shape' => 'UpdateQueueStatusRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQuickConnectConfig' => [ 'name' => 'UpdateQuickConnectConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/quick-connects/{InstanceId}/{QuickConnectId}/config', ], 'input' => [ 'shape' => 'UpdateQuickConnectConfigRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateQuickConnectName' => [ 'name' => 'UpdateQuickConnectName', 'http' => [ 'method' => 'POST', 'requestUri' => '/quick-connects/{InstanceId}/{QuickConnectId}/name', ], 'input' => [ 'shape' => 'UpdateQuickConnectNameRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileAgentAvailabilityTimer' => [ 'name' => 'UpdateRoutingProfileAgentAvailabilityTimer', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/agent-availability-timer', ], 'input' => [ 'shape' => 'UpdateRoutingProfileAgentAvailabilityTimerRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileConcurrency' => [ 'name' => 'UpdateRoutingProfileConcurrency', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/concurrency', ], 'input' => [ 'shape' => 'UpdateRoutingProfileConcurrencyRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileDefaultOutboundQueue' => [ 'name' => 'UpdateRoutingProfileDefaultOutboundQueue', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/default-outbound-queue', ], 'input' => [ 'shape' => 'UpdateRoutingProfileDefaultOutboundQueueRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileName' => [ 'name' => 'UpdateRoutingProfileName', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/name', ], 'input' => [ 'shape' => 'UpdateRoutingProfileNameRequest', ], 'errors' => [ [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRoutingProfileQueues' => [ 'name' => 'UpdateRoutingProfileQueues', 'http' => [ 'method' => 'POST', 'requestUri' => '/routing-profiles/{InstanceId}/{RoutingProfileId}/queues', ], 'input' => [ 'shape' => 'UpdateRoutingProfileQueuesRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateRule' => [ 'name' => 'UpdateRule', 'http' => [ 'method' => 'PUT', 'requestUri' => '/rules/{InstanceId}/{RuleId}', ], 'input' => [ 'shape' => 'UpdateRuleRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceConflictException', ], ], ], 'UpdateSecurityProfile' => [ 'name' => 'UpdateSecurityProfile', 'http' => [ 'method' => 'POST', 'requestUri' => '/security-profiles/{InstanceId}/{SecurityProfileId}', ], 'input' => [ 'shape' => 'UpdateSecurityProfileRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateTaskTemplate' => [ 'name' => 'UpdateTaskTemplate', 'http' => [ 'method' => 'POST', 'requestUri' => '/instance/{InstanceId}/task/template/{TaskTemplateId}', ], 'input' => [ 'shape' => 'UpdateTaskTemplateRequest', ], 'output' => [ 'shape' => 'UpdateTaskTemplateResponse', ], 'errors' => [ [ 'shape' => 'PropertyValidationException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateTrafficDistribution' => [ 'name' => 'UpdateTrafficDistribution', 'http' => [ 'method' => 'PUT', 'requestUri' => '/traffic-distribution/{Id}', ], 'input' => [ 'shape' => 'UpdateTrafficDistributionRequest', ], 'output' => [ 'shape' => 'UpdateTrafficDistributionResponse', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ResourceConflictException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserHierarchy' => [ 'name' => 'UpdateUserHierarchy', 'http' => [ 'method' => 'POST', 'requestUri' => '/users/{InstanceId}/{UserId}/hierarchy', ], 'input' => [ 'shape' => 'UpdateUserHierarchyRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserHierarchyGroupName' => [ 'name' => 'UpdateUserHierarchyGroupName', 'http' => [ 'method' => 'POST', 'requestUri' => '/user-hierarchy-groups/{InstanceId}/{HierarchyGroupId}/name', ], 'input' => [ 'shape' => 'UpdateUserHierarchyGroupNameRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'DuplicateResourceException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServiceException', ], ], ], 'UpdateUserHierarchyStructure' => [ 'name' => 'UpdateUserHierarchyStructure', 'http' => [ 'method' => 'POST', 'requestUri' => '/user-hierarchy-structure/{InstanceId}', ], 'input' => [ 'shape' => 'UpdateUserHierarchyStructureRequest', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InvalidParameterException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 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'AvailableNumbersList' => [ 'type' => 'list', 'member' => [ 'shape' => 'AvailableNumberSummary', ], ], 'AwsRegion' => [ 'type' => 'string', 'max' => 31, 'min' => 8, 'pattern' => '[a-z]{2}(-[a-z]+){1,2}(-[0-9])?', ], 'BatchAssociateAnalyticsDataSetRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'DataSetIds', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'DataSetIds' => [ 'shape' => 'DataSetIds', ], 'TargetAccountId' => [ 'shape' => 'AWSAccountId', ], ], ], 'BatchAssociateAnalyticsDataSetResponse' => [ 'type' => 'structure', 'members' => [ 'Created' => [ 'shape' => 'AnalyticsDataAssociationResults', ], 'Errors' => [ 'shape' => 'ErrorResults', ], ], ], 'BatchDisassociateAnalyticsDataSetRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'DataSetIds', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'DataSetIds' => [ 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'ChatParticipantRoleConfig' => [ 'type' => 'structure', 'required' => [ 'ParticipantTimerConfigList', ], 'members' => [ 'ParticipantTimerConfigList' => [ 'shape' => 'ParticipantTimerConfigList', ], ], ], 'ChatStreamingConfiguration' => [ 'type' => 'structure', 'required' => [ 'StreamingEndpointArn', ], 'members' => [ 'StreamingEndpointArn' => [ 'shape' => 'ChatStreamingEndpointARN', ], ], ], 'ChatStreamingEndpointARN' => [ 'type' => 'string', 'max' => 350, 'min' => 1, ], 'ClaimPhoneNumberRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneNumber', ], 'members' => [ 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'PhoneNumber' => [ 'shape' => 'PhoneNumber', ], 'PhoneNumberDescription' => [ 'shape' => 'PhoneNumberDescription', ], 'Tags' => [ 'shape' => 'TagMap', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'ClaimPhoneNumberResponse' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', ], 'PhoneNumberArn' => [ 'shape' => 'ARN', ], ], ], 'ClaimedPhoneNumberSummary' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', ], 'PhoneNumberArn' => [ 'shape' => 'ARN', ], 'PhoneNumber' => [ 'shape' => 'PhoneNumber', ], 'PhoneNumberCountryCode' => [ 'shape' => 'PhoneNumberCountryCode', ], 'PhoneNumberType' => [ 'shape' => 'PhoneNumberType', ], 'PhoneNumberDescription' => [ 'shape' => 'PhoneNumberDescription', ], 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'Tags' => [ 'shape' => 'TagMap', ], 'PhoneNumberStatus' => [ 'shape' => 'PhoneNumberStatus', ], 'SourcePhoneNumberArn' => [ 'shape' => 'ARN', ], ], ], 'ClientToken' => [ 'type' => 'string', 'max' => 500, ], 'CommonNameLength127' => [ 'type' => 'string', 'max' => 127, 'min' => 1, ], 'Comparison' => [ 'type' => 'string', 'enum' => [ 'LT', ], ], 'Concurrency' => [ 'type' => 'integer', 'max' => 10, 'min' => 1, ], 'ConflictException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 409, ], 'exception' => true, ], 'ConnectionData' => [ 'type' => 'structure', 'members' => [ 'Attendee' => [ 'shape' => 'Attendee', ], 'Meeting' => [ 'shape' => 'Meeting', ], ], ], 'Contact' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'Id' => [ 'shape' => 'ContactId', ], 'InitialContactId' => [ 'shape' => 'ContactId', ], 'PreviousContactId' => [ 'shape' => 'ContactId', ], 'InitiationMethod' => [ 'shape' => 'ContactInitiationMethod', ], 'Name' => [ 'shape' => 'Name', ], 'Description' => [ 'shape' => 'Description', ], 'Channel' => [ 'shape' => 'Channel', ], 'QueueInfo' => [ 'shape' => 'QueueInfo', ], 'AgentInfo' => [ 'shape' => 'AgentInfo', ], 'InitiationTimestamp' => [ 'shape' => 'timestamp', ], 'DisconnectTimestamp' => [ 'shape' => 'timestamp', ], 'LastUpdateTimestamp' => [ 'shape' => 'timestamp', ], 'LastPausedTimestamp' => [ 'shape' => 'timestamp', ], 'LastResumedTimestamp' => [ 'shape' => 'timestamp', ], 'TotalPauseCount' => [ 'shape' => 'TotalPauseCount', ], 'TotalPauseDurationInSeconds' => [ 'shape' => 'TotalPauseDurationInSeconds', ], 'ScheduledTimestamp' => [ 'shape' => 'timestamp', ], 'RelatedContactId' => [ 'shape' => 'ContactId', ], 'WisdomInfo' => [ 'shape' => 'WisdomInfo', ], 'QueueTimeAdjustmentSeconds' => [ 'shape' => 'QueueTimeAdjustmentSeconds', ], 'QueuePriority' => [ 'shape' => 'QueuePriority', ], 'Tags' => [ 'shape' => 'ContactTagMap', ], ], ], 'ContactAnalysis' => [ 'type' => 'structure', 'members' => [ 'Transcript' => [ 'shape' => 'Transcript', ], ], ], 'ContactDataRequest' => [ 'type' => 'structure', 'members' => [ 'SystemEndpoint' => [ 'shape' => 'Endpoint', ], 'CustomerEndpoint' => [ 'shape' => 'Endpoint', ], 'RequestIdentifier' => [ 'shape' => 'RequestIdentifier', ], 'QueueId' => [ 'shape' => 'QueueId', ], 'Attributes' => [ 'shape' => 'Attributes', ], 'Campaign' => [ 'shape' => 'Campaign', ], ], ], 'ContactDataRequestList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactDataRequest', ], 'max' => 25, 'min' => 1, ], 'ContactFilter' => [ 'type' => 'structure', 'members' => [ 'ContactStates' => [ 'shape' => 'ContactStates', ], ], ], 'ContactFlow' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'Id' => [ 'shape' => 'ContactFlowId', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'Type' => [ 'shape' => 'ContactFlowType', ], 'State' => [ 'shape' => 'ContactFlowState', ], 'Description' => [ 'shape' => 'ContactFlowDescription', ], 'Content' => [ 'shape' => 'ContactFlowContent', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'ContactFlowContent' => [ 'type' => 'string', ], 'ContactFlowDescription' => [ 'type' => 'string', ], 'ContactFlowId' => [ 'type' => 'string', 'max' => 500, ], 'ContactFlowModule' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'Id' => [ 'shape' => 'ContactFlowModuleId', ], 'Name' => [ 'shape' => 'ContactFlowModuleName', ], 'Content' => [ 'shape' => 'ContactFlowModuleContent', ], 'Description' => [ 'shape' => 'ContactFlowModuleDescription', ], 'State' => [ 'shape' => 'ContactFlowModuleState', ], 'Status' => [ 'shape' => 'ContactFlowModuleStatus', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'ContactFlowModuleContent' => [ 'type' => 'string', 'max' => 256000, 'min' => 1, ], 'ContactFlowModuleDescription' => [ 'type' => 'string', 'max' => 500, 'min' => 0, 'pattern' => '.*\\S.*', ], 'ContactFlowModuleId' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'ContactFlowModuleName' => [ 'type' => 'string', 'max' => 127, 'min' => 1, 'pattern' => '.*\\S.*', ], 'ContactFlowModuleState' => [ 'type' => 'string', 'enum' => [ 'ACTIVE', 'ARCHIVED', ], ], 'ContactFlowModuleStatus' => [ 'type' => 'string', 'enum' => [ 'PUBLISHED', 'SAVED', ], ], 'ContactFlowModuleSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ContactFlowModuleId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'ContactFlowModuleName', ], 'State' => [ 'shape' => 'ContactFlowModuleState', ], ], ], 'ContactFlowModulesSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactFlowModuleSummary', ], ], 'ContactFlowName' => [ 'type' => 'string', 'min' => 1, ], 'ContactFlowNotPublishedException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 404, ], 'exception' => true, ], 'ContactFlowState' => [ 'type' => 'string', 'enum' => [ 'ACTIVE', 'ARCHIVED', ], ], 'ContactFlowSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ContactFlowId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'ContactFlowType' => [ 'shape' => 'ContactFlowType', ], 'ContactFlowState' => [ 'shape' => 'ContactFlowState', ], ], ], 'ContactFlowSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactFlowSummary', ], ], 'ContactFlowType' => [ 'type' => 'string', 'enum' => [ 'CONTACT_FLOW', 'CUSTOMER_QUEUE', 'CUSTOMER_HOLD', 'CUSTOMER_WHISPER', 'AGENT_HOLD', 'AGENT_WHISPER', 'OUTBOUND_WHISPER', 'AGENT_TRANSFER', 'QUEUE_TRANSFER', ], ], 'ContactFlowTypes' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactFlowType', ], 'max' => 10, ], 'ContactId' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'ContactInitiationMethod' => [ 'type' => 'string', 'enum' => [ 'INBOUND', 'OUTBOUND', 'TRANSFER', 'QUEUE_TRANSFER', 'CALLBACK', 'API', 'DISCONNECT', 'MONITOR', 'EXTERNAL_OUTBOUND', ], ], 'ContactNotFoundException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 410, ], 'exception' => true, ], 'ContactReferences' => [ 'type' => 'map', 'key' => [ 'shape' => 'ReferenceKey', ], 'value' => [ 'shape' => 'Reference', ], ], 'ContactSearchSummary' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'Id' => [ 'shape' => 'ContactId', ], 'InitialContactId' => [ 'shape' => 'ContactId', ], 'PreviousContactId' => [ 'shape' => 'ContactId', ], 'InitiationMethod' => [ 'shape' => 'ContactInitiationMethod', ], 'Channel' => [ 'shape' => 'Channel', ], 'QueueInfo' => [ 'shape' => 'ContactSearchSummaryQueueInfo', ], 'AgentInfo' => [ 'shape' => 'ContactSearchSummaryAgentInfo', ], 'InitiationTimestamp' => [ 'shape' => 'timestamp', ], 'DisconnectTimestamp' => [ 'shape' => 'timestamp', ], 'ScheduledTimestamp' => [ 'shape' => 'timestamp', ], ], ], 'ContactSearchSummaryAgentInfo' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'AgentResourceId', ], 'ConnectedToAgentTimestamp' => [ 'shape' => 'timestamp', ], ], ], 'ContactSearchSummaryQueueInfo' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'QueueId', ], 'EnqueueTimestamp' => [ 'shape' => 'timestamp', ], ], ], 'ContactState' => [ 'type' => 'string', 'enum' => [ 'INCOMING', 'PENDING', 'CONNECTING', 'CONNECTED', 'CONNECTED_ONHOLD', 'MISSED', 'ERROR', 'ENDED', 'REJECTED', ], ], 'ContactStates' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactState', ], 'max' => 9, ], 'ContactTagKey' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '^(?!aws:)[a-zA-Z+-=._:/]+$', ], 'ContactTagKeys' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactTagKey', ], 'max' => 6, 'min' => 1, ], 'ContactTagMap' => [ 'type' => 'map', 'key' => [ 'shape' => 'ContactTagKey', ], 'value' => [ 'shape' => 'ContactTagValue', ], 'max' => 6, 'min' => 1, ], 'ContactTagValue' => [ 'type' => 'string', 'max' => 256, ], 'Contacts' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContactSearchSummary', ], ], 'Content' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'ContentType' => [ 'type' => 'string', 'max' => 255, 'min' => 1, ], 'ControlPlaneTagFilter' => [ 'type' => 'structure', 'members' => [ 'OrConditions' => [ 'shape' => 'TagOrConditionList', ], 'AndConditions' => [ 'shape' => 'TagAndConditionList', ], 'TagCondition' => [ 'shape' => 'TagCondition', ], ], ], 'CreateAgentStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'State', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'AgentStatusName', ], 'Description' => [ 'shape' => 'AgentStatusDescription', ], 'State' => [ 'shape' => 'AgentStatusState', ], 'DisplayOrder' => [ 'shape' => 'AgentStatusOrderNumber', 'box' => true, ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateAgentStatusResponse' => [ 'type' => 'structure', 'members' => [ 'AgentStatusARN' => [ 'shape' => 'ARN', ], 'AgentStatusId' => [ 'shape' => 'AgentStatusId', ], ], ], 'CreateCaseActionDefinition' => [ 'type' => 'structure', 'required' => [ 'Fields', 'TemplateId', ], 'members' => [ 'Fields' => [ 'shape' => 'FieldValues', ], 'TemplateId' => [ 'shape' => 'TemplateId', ], ], ], 'CreateContactFlowModuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'ContactFlowModuleName', ], 'Description' => [ 'shape' => 'ContactFlowModuleDescription', ], 'Content' => [ 'shape' => 'ContactFlowModuleContent', ], 'Tags' => [ 'shape' => 'TagMap', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'CreateContactFlowModuleResponse' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ContactFlowModuleId', ], 'Arn' => [ 'shape' => 'ARN', ], ], ], 'CreateContactFlowRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Type', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'Type' => [ 'shape' => 'ContactFlowType', ], 'Description' => [ 'shape' => 'ContactFlowDescription', ], 'Content' => [ 'shape' => 'ContactFlowContent', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateContactFlowResponse' => [ 'type' => 'structure', 'members' => [ 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'ContactFlowArn' => [ 'shape' => 'ARN', ], ], ], 'CreateEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Title', 'Items', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Title' => [ 'shape' => 'EvaluationFormTitle', ], 'Description' => [ 'shape' => 'EvaluationFormDescription', ], 'Items' => [ 'shape' => 'EvaluationFormItemsList', ], 'ScoringStrategy' => [ 'shape' => 'EvaluationFormScoringStrategy', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'CreateEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormId', 'EvaluationFormArn', ], 'members' => [ 'EvaluationFormId' => [ 'shape' => 'ResourceId', ], 'EvaluationFormArn' => [ 'shape' => 'ARN', ], ], ], 'CreateHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'TimeZone', 'Config', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'HoursOfOperationDescription', ], 'TimeZone' => [ 'shape' => 'TimeZone', ], 'Config' => [ 'shape' => 'HoursOfOperationConfigList', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateHoursOfOperationResponse' => [ 'type' => 'structure', 'members' => [ 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', ], 'HoursOfOperationArn' => [ 'shape' => 'ARN', ], ], ], 'CreateInstanceRequest' => [ 'type' => 'structure', 'required' => [ 'IdentityManagementType', 'InboundCallsEnabled', 'OutboundCallsEnabled', ], 'members' => [ 'ClientToken' => [ 'shape' => 'ClientToken', ], 'IdentityManagementType' => [ 'shape' => 'DirectoryType', ], 'InstanceAlias' => [ 'shape' => 'DirectoryAlias', ], 'DirectoryId' => [ 'shape' => 'DirectoryId', ], 'InboundCallsEnabled' => [ 'shape' => 'InboundCallsEnabled', ], 'OutboundCallsEnabled' => [ 'shape' => 'OutboundCallsEnabled', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateInstanceResponse' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'InstanceId', ], 'Arn' => [ 'shape' => 'ARN', ], ], ], 'CreateIntegrationAssociationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'IntegrationType', 'IntegrationArn', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'IntegrationType' => [ 'shape' => 'IntegrationType', ], 'IntegrationArn' => [ 'shape' => 'ARN', ], 'SourceApplicationUrl' => [ 'shape' => 'URI', ], 'SourceApplicationName' => [ 'shape' => 'SourceApplicationName', ], 'SourceType' => [ 'shape' => 'SourceType', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateIntegrationAssociationResponse' => [ 'type' => 'structure', 'members' => [ 'IntegrationAssociationId' => [ 'shape' => 'IntegrationAssociationId', ], 'IntegrationAssociationArn' => [ 'shape' => 'ARN', ], ], ], 'CreateParticipantRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'ParticipantDetails', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'ParticipantDetails' => [ 'shape' => 'ParticipantDetailsToAdd', ], ], ], 'CreateParticipantResponse' => [ 'type' => 'structure', 'members' => [ 'ParticipantCredentials' => [ 'shape' => 'ParticipantTokenCredentials', ], 'ParticipantId' => [ 'shape' => 'ParticipantId', ], ], ], 'CreatePersistentContactAssociationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'InitialContactId', 'RehydrationType', 'SourceContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'InitialContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'InitialContactId', ], 'RehydrationType' => [ 'shape' => 'RehydrationType', ], 'SourceContactId' => [ 'shape' => 'ContactId', ], 'ClientToken' => [ 'shape' => 'ClientToken', ], ], ], 'CreatePersistentContactAssociationResponse' => [ 'type' => 'structure', 'members' => [ 'ContinuedFromContactId' => [ 'shape' => 'ContactId', ], ], ], 'CreatePredefinedAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Values', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'PredefinedAttributeName', ], 'Values' => [ 'shape' => 'PredefinedAttributeValues', ], ], ], 'CreatePromptRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'S3Uri', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'PromptDescription', ], 'S3Uri' => [ 'shape' => 'S3Uri', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreatePromptResponse' => [ 'type' => 'structure', 'members' => [ 'PromptARN' => [ 'shape' => 'ARN', ], 'PromptId' => [ 'shape' => 'PromptId', ], ], ], 'CreateQueueRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'QueueDescription', ], 'OutboundCallerConfig' => [ 'shape' => 'OutboundCallerConfig', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', ], 'MaxContacts' => [ 'shape' => 'QueueMaxContacts', 'box' => true, ], 'QuickConnectIds' => [ 'shape' => 'QuickConnectsList', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateQueueResponse' => [ 'type' => 'structure', 'members' => [ 'QueueArn' => [ 'shape' => 'ARN', ], 'QueueId' => [ 'shape' => 'QueueId', ], ], ], 'CreateQuickConnectRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'QuickConnectConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'QuickConnectName', ], 'Description' => [ 'shape' => 'QuickConnectDescription', ], 'QuickConnectConfig' => [ 'shape' => 'QuickConnectConfig', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateQuickConnectResponse' => [ 'type' => 'structure', 'members' => [ 'QuickConnectARN' => [ 'shape' => 'ARN', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', ], ], ], 'CreateRoutingProfileRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Description', 'DefaultOutboundQueueId', 'MediaConcurrencies', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'RoutingProfileName', ], 'Description' => [ 'shape' => 'RoutingProfileDescription', ], 'DefaultOutboundQueueId' => [ 'shape' => 'QueueId', ], 'QueueConfigs' => [ 'shape' => 'RoutingProfileQueueConfigList', ], 'MediaConcurrencies' => [ 'shape' => 'MediaConcurrencies', ], 'Tags' => [ 'shape' => 'TagMap', ], 'AgentAvailabilityTimer' => [ 'shape' => 'AgentAvailabilityTimer', ], ], ], 'CreateRoutingProfileResponse' => [ 'type' => 'structure', 'members' => [ 'RoutingProfileArn' => [ 'shape' => 'ARN', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], ], ], 'CreateRuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'TriggerEventSource', 'Function', 'Actions', 'PublishStatus', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'RuleName', ], 'TriggerEventSource' => [ 'shape' => 'RuleTriggerEventSource', ], 'Function' => [ 'shape' => 'RuleFunction', ], 'Actions' => [ 'shape' => 'RuleActions', ], 'PublishStatus' => [ 'shape' => 'RulePublishStatus', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'CreateRuleResponse' => [ 'type' => 'structure', 'required' => [ 'RuleArn', 'RuleId', ], 'members' => [ 'RuleArn' => [ 'shape' => 'ARN', ], 'RuleId' => [ 'shape' => 'RuleId', ], ], ], 'CreateSecurityProfileName' => [ 'type' => 'string', 'max' => 127, 'min' => 1, 'pattern' => '^[ a-zA-Z0-9_@-]+$', ], 'CreateSecurityProfileRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileName', 'InstanceId', ], 'members' => [ 'SecurityProfileName' => [ 'shape' => 'CreateSecurityProfileName', ], 'Description' => [ 'shape' => 'SecurityProfileDescription', ], 'Permissions' => [ 'shape' => 'PermissionsList', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Tags' => [ 'shape' => 'TagMap', ], 'AllowedAccessControlTags' => [ 'shape' => 'AllowedAccessControlTags', ], 'TagRestrictedResources' => [ 'shape' => 'TagRestrictedResourceList', ], 'Applications' => [ 'shape' => 'Applications', ], ], ], 'CreateSecurityProfileResponse' => [ 'type' => 'structure', 'members' => [ 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', ], 'SecurityProfileArn' => [ 'shape' => 'ARN', ], ], ], 'CreateTaskTemplateRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', 'Fields', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'TaskTemplateName', ], 'Description' => [ 'shape' => 'TaskTemplateDescription', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'Constraints' => [ 'shape' => 'TaskTemplateConstraints', ], 'Defaults' => [ 'shape' => 'TaskTemplateDefaults', ], 'Status' => [ 'shape' => 'TaskTemplateStatus', ], 'Fields' => [ 'shape' => 'TaskTemplateFields', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'CreateTaskTemplateResponse' => [ 'type' => 'structure', 'required' => [ 'Id', 'Arn', ], 'members' => [ 'Id' => [ 'shape' => 'TaskTemplateId', ], 'Arn' => [ 'shape' => 'TaskTemplateArn', ], ], ], 'CreateTrafficDistributionGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'InstanceId', ], 'members' => [ 'Name' => [ 'shape' => 'Name128', ], 'Description' => [ 'shape' => 'Description250', ], 'InstanceId' => [ 'shape' => 'InstanceIdOrArn', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateTrafficDistributionGroupResponse' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'TrafficDistributionGroupId', ], 'Arn' => [ 'shape' => 'TrafficDistributionGroupArn', ], ], ], 'CreateUseCaseRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'IntegrationAssociationId', 'UseCaseType', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'IntegrationAssociationId' => [ 'shape' => 'IntegrationAssociationId', 'location' => 'uri', 'locationName' => 'IntegrationAssociationId', ], 'UseCaseType' => [ 'shape' => 'UseCaseType', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateUseCaseResponse' => [ 'type' => 'structure', 'members' => [ 'UseCaseId' => [ 'shape' => 'UseCaseId', ], 'UseCaseArn' => [ 'shape' => 'ARN', ], ], ], 'CreateUserHierarchyGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'InstanceId', ], 'members' => [ 'Name' => [ 'shape' => 'HierarchyGroupName', ], 'ParentGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateUserHierarchyGroupResponse' => [ 'type' => 'structure', 'members' => [ 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'HierarchyGroupArn' => [ 'shape' => 'ARN', ], ], ], 'CreateUserRequest' => [ 'type' => 'structure', 'required' => [ 'Username', 'PhoneConfig', 'SecurityProfileIds', 'RoutingProfileId', 'InstanceId', ], 'members' => [ 'Username' => [ 'shape' => 'AgentUsername', ], 'Password' => [ 'shape' => 'Password', ], 'IdentityInfo' => [ 'shape' => 'UserIdentityInfo', ], 'PhoneConfig' => [ 'shape' => 'UserPhoneConfig', ], 'DirectoryUserId' => [ 'shape' => 'DirectoryUserId', ], 'SecurityProfileIds' => [ 'shape' => 'SecurityProfileIds', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateUserResponse' => [ 'type' => 'structure', 'members' => [ 'UserId' => [ 'shape' => 'UserId', ], 'UserArn' => [ 'shape' => 'ARN', ], ], ], 'CreateViewRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Status', 'Content', 'Name', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ClientToken' => [ 'shape' => 'ViewsClientToken', ], 'Status' => [ 'shape' => 'ViewStatus', ], 'Content' => [ 'shape' => 'ViewInputContent', ], 'Description' => [ 'shape' => 'ViewDescription', ], 'Name' => [ 'shape' => 'ViewName', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateViewResponse' => [ 'type' => 'structure', 'members' => [ 'View' => [ 'shape' => 'View', ], ], ], 'CreateViewVersionRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'VersionDescription' => [ 'shape' => 'ViewDescription', ], 'ViewContentSha256' => [ 'shape' => 'ViewContentSha256', ], ], ], 'CreateViewVersionResponse' => [ 'type' => 'structure', 'members' => [ 'View' => [ 'shape' => 'View', ], ], ], 'CreateVocabularyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'VocabularyName', 'LanguageCode', 'Content', ], 'members' => [ 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'VocabularyName' => [ 'shape' => 'VocabularyName', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], 'Content' => [ 'shape' => 'VocabularyContent', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'CreateVocabularyResponse' => [ 'type' => 'structure', 'required' => [ 'VocabularyArn', 'VocabularyId', 'State', ], 'members' => [ 'VocabularyArn' => [ 'shape' => 'ARN', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', ], 'State' => [ 'shape' => 'VocabularyState', ], ], ], 'Credentials' => [ 'type' => 'structure', 'members' => [ 'AccessToken' => [ 'shape' => 'SecurityToken', ], 'AccessTokenExpiration' => [ 'shape' => 'timestamp', ], 'RefreshToken' => [ 'shape' => 'SecurityToken', ], 'RefreshTokenExpiration' => [ 'shape' => 'timestamp', ], ], 'sensitive' => true, ], 'CrossChannelBehavior' => [ 'type' => 'structure', 'required' => [ 'BehaviorType', ], 'members' => [ 'BehaviorType' => [ 'shape' => 'BehaviorType', ], ], ], 'CurrentMetric' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'CurrentMetricName', ], 'Unit' => [ 'shape' => 'Unit', ], ], ], 'CurrentMetricData' => [ 'type' => 'structure', 'members' => [ 'Metric' => [ 'shape' => 'CurrentMetric', ], 'Value' => [ 'shape' => 'Value', 'box' => true, ], ], ], 'CurrentMetricDataCollections' => [ 'type' => 'list', 'member' => [ 'shape' => 'CurrentMetricData', ], ], 'CurrentMetricName' => [ 'type' => 'string', 'enum' => [ 'AGENTS_ONLINE', 'AGENTS_AVAILABLE', 'AGENTS_ON_CALL', 'AGENTS_NON_PRODUCTIVE', 'AGENTS_AFTER_CONTACT_WORK', 'AGENTS_ERROR', 'AGENTS_STAFFED', 'CONTACTS_IN_QUEUE', 'OLDEST_CONTACT_AGE', 'CONTACTS_SCHEDULED', 'AGENTS_ON_CONTACT', 'SLOTS_ACTIVE', 'SLOTS_AVAILABLE', ], ], 'CurrentMetricResult' => [ 'type' => 'structure', 'members' => [ 'Dimensions' => [ 'shape' => 'Dimensions', ], 'Collections' => [ 'shape' => 'CurrentMetricDataCollections', ], ], ], 'CurrentMetricResults' => [ 'type' => 'list', 'member' => [ 'shape' => 'CurrentMetricResult', ], ], 'CurrentMetricSortCriteria' => [ 'type' => 'structure', 'members' => [ 'SortByMetric' => [ 'shape' => 'CurrentMetricName', ], 'SortOrder' => [ 'shape' => 'SortOrder', ], ], ], 'CurrentMetricSortCriteriaMaxOne' => [ 'type' => 'list', 'member' => [ 'shape' => 'CurrentMetricSortCriteria', ], 'max' => 1, 'min' => 0, ], 'CurrentMetrics' => [ 'type' => 'list', 'member' => [ 'shape' => 'CurrentMetric', ], ], 'DataSetId' => [ 'type' => 'string', 'max' => 255, 'min' => 1, ], 'DataSetIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'DataSetId', ], ], 'DateReference' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ReferenceKey', ], 'Value' => [ 'shape' => 'ReferenceValue', ], ], ], 'DeactivateEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', 'EvaluationFormVersion', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], ], ], 'DeactivateEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormId', 'EvaluationFormArn', 'EvaluationFormVersion', ], 'members' => [ 'EvaluationFormId' => [ 'shape' => 'ResourceId', ], 'EvaluationFormArn' => [ 'shape' => 'ARN', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], ], ], 'DefaultVocabulary' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'LanguageCode', 'VocabularyId', 'VocabularyName', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', ], 'VocabularyName' => [ 'shape' => 'VocabularyName', ], ], ], 'DefaultVocabularyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'DefaultVocabulary', ], ], 'Delay' => [ 'type' => 'integer', 'max' => 9999, 'min' => 0, ], 'DeleteContactEvaluationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationId', ], ], ], 'DeleteContactFlowModuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowModuleId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowModuleId' => [ 'shape' => 'ContactFlowModuleId', 'location' => 'uri', 'locationName' => 'ContactFlowModuleId', ], ], ], 'DeleteContactFlowModuleResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteContactFlowRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], ], ], 'DeleteContactFlowResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', 'box' => true, 'location' => 'querystring', 'locationName' => 'version', ], ], ], 'DeleteHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', 'location' => 'uri', 'locationName' => 'HoursOfOperationId', ], ], ], 'DeleteInstanceRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'DeleteIntegrationAssociationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'IntegrationAssociationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'IntegrationAssociationId' => [ 'shape' => 'IntegrationAssociationId', 'location' => 'uri', 'locationName' => 'IntegrationAssociationId', ], ], ], 'DeletePredefinedAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'PredefinedAttributeName', 'location' => 'uri', 'locationName' => 'Name', ], ], ], 'DeletePromptRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'PromptId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'PromptId' => [ 'shape' => 'PromptId', 'location' => 'uri', 'locationName' => 'PromptId', ], ], ], 'DeleteQueueRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], ], ], 'DeleteQuickConnectRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QuickConnectId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', 'location' => 'uri', 'locationName' => 'QuickConnectId', ], ], ], 'DeleteRoutingProfileRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], ], ], 'DeleteRuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RuleId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RuleId' => [ 'shape' => 'RuleId', 'location' => 'uri', 'locationName' => 'RuleId', ], ], ], 'DeleteSecurityProfileRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'SecurityProfileId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', 'location' => 'uri', 'locationName' => 'SecurityProfileId', ], ], ], 'DeleteTaskTemplateRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'TaskTemplateId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'TaskTemplateId' => [ 'shape' => 'TaskTemplateId', 'location' => 'uri', 'locationName' => 'TaskTemplateId', ], ], ], 'DeleteTaskTemplateResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteTrafficDistributionGroupRequest' => [ 'type' => 'structure', 'required' => [ 'TrafficDistributionGroupId', ], 'members' => [ 'TrafficDistributionGroupId' => [ 'shape' => 'TrafficDistributionGroupIdOrArn', 'location' => 'uri', 'locationName' => 'TrafficDistributionGroupId', ], ], ], 'DeleteTrafficDistributionGroupResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteUseCaseRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'IntegrationAssociationId', 'UseCaseId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'IntegrationAssociationId' => [ 'shape' => 'IntegrationAssociationId', 'location' => 'uri', 'locationName' => 'IntegrationAssociationId', ], 'UseCaseId' => [ 'shape' => 'UseCaseId', 'location' => 'uri', 'locationName' => 'UseCaseId', ], ], ], 'DeleteUserHierarchyGroupRequest' => [ 'type' => 'structure', 'required' => [ 'HierarchyGroupId', 'InstanceId', ], 'members' => [ 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', 'location' => 'uri', 'locationName' => 'HierarchyGroupId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'DeleteUserRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'UserId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], ], ], 'DeleteViewRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], ], ], 'DeleteViewResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteViewVersionRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', 'ViewVersion', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'ViewVersion' => [ 'shape' => 'ViewVersion', 'location' => 'uri', 'locationName' => 'ViewVersion', ], ], ], 'DeleteViewVersionResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteVocabularyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'VocabularyId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', 'location' => 'uri', 'locationName' => 'VocabularyId', ], ], ], 'DeleteVocabularyResponse' => [ 'type' => 'structure', 'required' => [ 'VocabularyArn', 'VocabularyId', 'State', ], 'members' => [ 'VocabularyArn' => [ 'shape' => 'ARN', ], 'VocabularyId' => [ 'shape' => 'VocabularyId', ], 'State' => [ 'shape' => 'VocabularyState', ], ], ], 'DescribeAgentStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AgentStatusId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AgentStatusId' => [ 'shape' => 'AgentStatusId', 'location' => 'uri', 'locationName' => 'AgentStatusId', ], ], ], 'DescribeAgentStatusResponse' => [ 'type' => 'structure', 'members' => [ 'AgentStatus' => [ 'shape' => 'AgentStatus', ], ], ], 'DescribeContactEvaluationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationId', ], ], ], 'DescribeContactEvaluationResponse' => [ 'type' => 'structure', 'required' => [ 'Evaluation', 'EvaluationForm', ], 'members' => [ 'Evaluation' => [ 'shape' => 'Evaluation', ], 'EvaluationForm' => [ 'shape' => 'EvaluationFormContent', ], ], ], 'DescribeContactFlowModuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowModuleId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowModuleId' => [ 'shape' => 'ContactFlowModuleId', 'location' => 'uri', 'locationName' => 'ContactFlowModuleId', ], ], ], 'DescribeContactFlowModuleResponse' => [ 'type' => 'structure', 'members' => [ 'ContactFlowModule' => [ 'shape' => 'ContactFlowModule', ], ], ], 'DescribeContactFlowRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], ], ], 'DescribeContactFlowResponse' => [ 'type' => 'structure', 'members' => [ 'ContactFlow' => [ 'shape' => 'ContactFlow', ], ], ], 'DescribeContactRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], ], ], 'DescribeContactResponse' => [ 'type' => 'structure', 'members' => [ 'Contact' => [ 'shape' => 'Contact', ], ], ], 'DescribeEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', 'box' => true, 'location' => 'querystring', 'locationName' => 'version', ], ], ], 'DescribeEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationForm', ], 'members' => [ 'EvaluationForm' => [ 'shape' => 'EvaluationForm', ], ], ], 'DescribeHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', 'location' => 'uri', 'locationName' => 'HoursOfOperationId', ], ], ], 'DescribeHoursOfOperationResponse' => [ 'type' => 'structure', 'members' => [ 'HoursOfOperation' => [ 'shape' => 'HoursOfOperation', ], ], ], 'DescribeInstanceAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AttributeType', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AttributeType' => [ 'shape' => 'InstanceAttributeType', 'location' => 'uri', 'locationName' => 'AttributeType', ], ], ], 'DescribeInstanceAttributeResponse' => [ 'type' => 'structure', 'members' => [ 'Attribute' => [ 'shape' => 'Attribute', ], ], ], 'DescribeInstanceRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'DescribeInstanceResponse' => [ 'type' => 'structure', 'members' => [ 'Instance' => [ 'shape' => 'Instance', ], ], ], 'DescribeInstanceStorageConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AssociationId', 'ResourceType', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AssociationId' => [ 'shape' => 'AssociationId', 'location' => 'uri', 'locationName' => 'AssociationId', ], 'ResourceType' => [ 'shape' => 'InstanceStorageResourceType', 'location' => 'querystring', 'locationName' => 'resourceType', ], ], ], 'DescribeInstanceStorageConfigResponse' => [ 'type' => 'structure', 'members' => [ 'StorageConfig' => [ 'shape' => 'InstanceStorageConfig', ], ], ], 'DescribePhoneNumberRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneNumberId', ], 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', 'location' => 'uri', 'locationName' => 'PhoneNumberId', ], ], ], 'DescribePhoneNumberResponse' => [ 'type' => 'structure', 'members' => [ 'ClaimedPhoneNumberSummary' => [ 'shape' => 'ClaimedPhoneNumberSummary', ], ], ], 'DescribePredefinedAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'PredefinedAttributeName', 'location' => 'uri', 'locationName' => 'Name', ], ], ], 'DescribePredefinedAttributeResponse' => [ 'type' => 'structure', 'members' => [ 'PredefinedAttribute' => [ 'shape' => 'PredefinedAttribute', ], ], ], 'DescribePromptRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'PromptId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'PromptId' => [ 'shape' => 'PromptId', 'location' => 'uri', 'locationName' => 'PromptId', ], ], ], 'DescribePromptResponse' => [ 'type' => 'structure', 'members' => [ 'Prompt' => [ 'shape' => 'Prompt', ], ], ], 'DescribeQueueRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], ], ], 'DescribeQueueResponse' => [ 'type' => 'structure', 'members' => [ 'Queue' => [ 'shape' => 'Queue', ], ], ], 'DescribeQuickConnectRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QuickConnectId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', 'location' => 'uri', 'locationName' => 'QuickConnectId', ], ], ], 'DescribeQuickConnectResponse' => [ 'type' => 'structure', 'members' => [ 'QuickConnect' => [ 'shape' => 'QuickConnect', ], ], ], 'DescribeRoutingProfileRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], ], ], 'DescribeRoutingProfileResponse' => [ 'type' => 'structure', 'members' => [ 'RoutingProfile' => [ 'shape' => 'RoutingProfile', ], ], ], 'DescribeRuleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RuleId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RuleId' => [ 'shape' => 'RuleId', 'location' => 'uri', 'locationName' => 'RuleId', ], ], ], 'DescribeRuleResponse' => [ 'type' => 'structure', 'required' => [ 'Rule', ], 'members' => [ 'Rule' => [ 'shape' => 'Rule', ], ], ], 'DescribeSecurityProfileRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileId', 'InstanceId', ], 'members' => [ 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', 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'IntegrationAssociationSummary', ], ], 'IntegrationType' => [ 'type' => 'string', 'enum' => [ 'EVENT', 'VOICE_ID', 'PINPOINT_APP', 'WISDOM_ASSISTANT', 'WISDOM_KNOWLEDGE_BASE', 'WISDOM_QUICK_RESPONSES', 'CASES_DOMAIN', 'APPLICATION', 'FILE_SCANNER', ], ], 'InternalServiceException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 500, ], 'exception' => true, ], 'IntervalDetails' => [ 'type' => 'structure', 'members' => [ 'TimeZone' => [ 'shape' => 'String', ], 'IntervalPeriod' => [ 'shape' => 'IntervalPeriod', ], ], ], 'IntervalPeriod' => [ 'type' => 'string', 'enum' => [ 'FIFTEEN_MIN', 'THIRTY_MIN', 'HOUR', 'DAY', 'WEEK', 'TOTAL', ], ], 'InvalidContactFlowException' => [ 'type' => 'structure', 'members' => [ 'problems' => [ 'shape' => 'Problems', ], ], 'error' => [ 'httpStatusCode' => 400, ], 'exception' => true, ], 'InvalidContactFlowModuleException' => [ 'type' => 'structure', 'members' => [ 'Problems' => [ 'shape' 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'required' => [ 'StreamArn', ], 'members' => [ 'StreamArn' => [ 'shape' => 'ARN', ], ], ], 'KinesisVideoStreamConfig' => [ 'type' => 'structure', 'required' => [ 'Prefix', 'RetentionPeriodHours', 'EncryptionConfig', ], 'members' => [ 'Prefix' => [ 'shape' => 'Prefix', ], 'RetentionPeriodHours' => [ 'shape' => 'Hours', ], 'EncryptionConfig' => [ 'shape' => 'EncryptionConfig', ], ], ], 'LargeNextToken' => [ 'type' => 'string', 'max' => 100000, 'min' => 1, ], 'LexBot' => [ 'type' => 'structure', 'required' => [ 'Name', 'LexRegion', ], 'members' => [ 'Name' => [ 'shape' => 'BotName', ], 'LexRegion' => [ 'shape' => 'LexRegion', ], ], ], 'LexBotConfig' => [ 'type' => 'structure', 'members' => [ 'LexBot' => [ 'shape' => 'LexBot', ], 'LexV2Bot' => [ 'shape' => 'LexV2Bot', ], ], ], 'LexBotConfigList' => [ 'type' => 'list', 'member' => [ 'shape' => 'LexBotConfig', ], ], 'LexBotsList' => [ 'type' => 'list', 'member' => [ 'shape' => 'LexBot', ], ], 'LexRegion' => [ 'type' => 'string', 'max' => 60, ], 'LexV2Bot' => [ 'type' => 'structure', 'members' => [ 'AliasArn' => [ 'shape' => 'AliasArn', ], ], ], 'LexVersion' => [ 'type' => 'string', 'enum' => [ 'V1', 'V2', ], ], 'LimitExceededException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 429, ], 'exception' => true, ], 'ListAgentStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'AgentStatusTypes' => [ 'shape' => 'AgentStatusTypes', 'location' => 'querystring', 'locationName' => 'AgentStatusTypes', ], ], ], 'ListAgentStatusResponse' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'AgentStatusSummaryList' => [ 'shape' => 'AgentStatusSummaryList', ], ], ], 'ListAnalyticsDataAssociationsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'DataSetId' => [ 'shape' => 'DataSetId', 'location' => 'querystring', 'locationName' => 'DataSetId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListAnalyticsDataAssociationsResponse' => [ 'type' => 'structure', 'members' => [ 'Results' => [ 'shape' => 'AnalyticsDataAssociationResults', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListApprovedOriginsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult25', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListApprovedOriginsResponse' => [ 'type' => 'structure', 'members' => [ 'Origins' => [ 'shape' => 'OriginsList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListBotsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'LexVersion', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult25', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'LexVersion' => [ 'shape' => 'LexVersion', 'location' => 'querystring', 'locationName' => 'lexVersion', ], ], ], 'ListBotsResponse' => [ 'type' => 'structure', 'members' => [ 'LexBots' => [ 'shape' => 'LexBotConfigList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListContactEvaluationsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'querystring', 'locationName' => 'contactId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListContactEvaluationsResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationSummaryList', ], 'members' => [ 'EvaluationSummaryList' => [ 'shape' => 'EvaluationSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListContactFlowModulesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'ContactFlowModuleState' => [ 'shape' => 'ContactFlowModuleState', 'location' => 'querystring', 'locationName' => 'state', ], ], ], 'ListContactFlowModulesResponse' => [ 'type' => 'structure', 'members' => [ 'ContactFlowModulesSummaryList' => [ 'shape' => 'ContactFlowModulesSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListContactFlowsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowTypes' => [ 'shape' => 'ContactFlowTypes', 'location' => 'querystring', 'locationName' => 'contactFlowTypes', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListContactFlowsResponse' => [ 'type' => 'structure', 'members' => [ 'ContactFlowSummaryList' => [ 'shape' => 'ContactFlowSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListContactReferencesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'ReferenceTypes', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'ReferenceTypes' => [ 'shape' => 'ReferenceTypes', 'location' => 'querystring', 'locationName' => 'referenceTypes', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListContactReferencesResponse' => [ 'type' => 'structure', 'members' => [ 'ReferenceSummaryList' => [ 'shape' => 'ReferenceSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListDefaultVocabulariesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], 'MaxResults' => [ 'shape' => 'MaxResult100', ], 'NextToken' => [ 'shape' => 'VocabularyNextToken', ], ], ], 'ListDefaultVocabulariesResponse' => [ 'type' => 'structure', 'required' => [ 'DefaultVocabularyList', ], 'members' => [ 'DefaultVocabularyList' => [ 'shape' => 'DefaultVocabularyList', ], 'NextToken' => [ 'shape' => 'VocabularyNextToken', ], ], ], 'ListEvaluationFormVersionsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListEvaluationFormVersionsResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormVersionSummaryList', ], 'members' => [ 'EvaluationFormVersionSummaryList' => [ 'shape' => 'EvaluationFormVersionSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListEvaluationFormsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListEvaluationFormsResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormSummaryList', ], 'members' => [ 'EvaluationFormSummaryList' => [ 'shape' => 'EvaluationFormSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListFlowAssociationResourceType' => [ 'type' => 'string', 'enum' => [ 'VOICE_PHONE_NUMBER', ], ], 'ListFlowAssociationsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ResourceType' => [ 'shape' => 'ListFlowAssociationResourceType', 'location' => 'querystring', 'locationName' => 'ResourceType', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListFlowAssociationsResponse' => [ 'type' 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'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult7', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListInstanceAttributesResponse' => [ 'type' => 'structure', 'members' => [ 'Attributes' => [ 'shape' => 'AttributesList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListInstanceStorageConfigsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ResourceType', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ResourceType' => [ 'shape' => 'InstanceStorageResourceType', 'location' => 'querystring', 'locationName' => 'resourceType', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult10', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListInstanceStorageConfigsResponse' => [ 'type' => 'structure', 'members' => [ 'StorageConfigs' => [ 'shape' => 'InstanceStorageConfigs', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListInstancesRequest' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult10', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListInstancesResponse' => [ 'type' => 'structure', 'members' => [ 'InstanceSummaryList' => [ 'shape' => 'InstanceSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListIntegrationAssociationsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'IntegrationType' => [ 'shape' => 'IntegrationType', 'location' => 'querystring', 'locationName' => 'integrationType', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'IntegrationArn' => [ 'shape' => 'ARN', 'location' => 'querystring', 'locationName' => 'integrationArn', ], ], ], 'ListIntegrationAssociationsResponse' => [ 'type' => 'structure', 'members' => [ 'IntegrationAssociationSummaryList' => [ 'shape' => 'IntegrationAssociationSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListLambdaFunctionsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult25', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListLambdaFunctionsResponse' => [ 'type' => 'structure', 'members' => [ 'LambdaFunctions' => [ 'shape' => 'FunctionArnsList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListLexBotsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult25', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListLexBotsResponse' => [ 'type' => 'structure', 'members' => [ 'LexBots' => [ 'shape' => 'LexBotsList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListPhoneNumbersRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'PhoneNumberTypes' => [ 'shape' => 'PhoneNumberTypes', 'location' => 'querystring', 'locationName' => 'phoneNumberTypes', ], 'PhoneNumberCountryCodes' => [ 'shape' => 'PhoneNumberCountryCodes', 'location' => 'querystring', 'locationName' => 'phoneNumberCountryCodes', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListPhoneNumbersResponse' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberSummaryList' => [ 'shape' => 'PhoneNumberSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListPhoneNumbersSummary' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', ], 'PhoneNumberArn' => [ 'shape' => 'ARN', ], 'PhoneNumber' => [ 'shape' => 'PhoneNumber', ], 'PhoneNumberCountryCode' => [ 'shape' => 'PhoneNumberCountryCode', ], 'PhoneNumberType' => [ 'shape' => 'PhoneNumberType', ], 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'PhoneNumberDescription' => [ 'shape' => 'PhoneNumberDescription', ], 'SourcePhoneNumberArn' => [ 'shape' => 'ARN', ], ], ], 'ListPhoneNumbersSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ListPhoneNumbersSummary', ], ], 'ListPhoneNumbersV2Request' => [ 'type' => 'structure', 'members' => [ 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, ], 'NextToken' => [ 'shape' => 'LargeNextToken', ], 'PhoneNumberCountryCodes' => [ 'shape' => 'PhoneNumberCountryCodes', ], 'PhoneNumberTypes' => [ 'shape' => 'PhoneNumberTypes', ], 'PhoneNumberPrefix' => [ 'shape' => 'PhoneNumberPrefix', ], ], ], 'ListPhoneNumbersV2Response' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'LargeNextToken', ], 'ListPhoneNumbersSummaryList' => [ 'shape' => 'ListPhoneNumbersSummaryList', ], ], ], 'ListPredefinedAttributesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListPredefinedAttributesResponse' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'PredefinedAttributeSummaryList' => [ 'shape' => 'PredefinedAttributeSummaryList', ], ], ], 'ListPromptsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListPromptsResponse' => [ 'type' => 'structure', 'members' => [ 'PromptSummaryList' => [ 'shape' => 'PromptSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListQueueQuickConnectsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListQueueQuickConnectsResponse' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'QuickConnectSummaryList' => [ 'shape' => 'QuickConnectSummaryList', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'ListQueuesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueTypes' => [ 'shape' => 'QueueTypes', 'location' => 'querystring', 'locationName' => 'queueTypes', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListQueuesResponse' => [ 'type' => 'structure', 'members' => [ 'QueueSummaryList' => [ 'shape' => 'QueueSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListQuickConnectsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'QuickConnectTypes' => [ 'shape' => 'QuickConnectTypes', 'location' => 'querystring', 'locationName' => 'QuickConnectTypes', ], ], ], 'ListQuickConnectsResponse' => [ 'type' => 'structure', 'members' => [ 'QuickConnectSummaryList' => [ 'shape' => 'QuickConnectSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListRealtimeContactAnalysisSegmentsV2Request' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'OutputType', 'SegmentTypes', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'MaxResults' => [ 'shape' => 'MaxResult100', ], 'NextToken' => [ 'shape' => 'LargeNextToken', ], 'OutputType' => [ 'shape' => 'RealTimeContactAnalysisOutputType', ], 'SegmentTypes' => [ 'shape' => 'RealTimeContactAnalysisSegmentTypes', ], ], ], 'ListRealtimeContactAnalysisSegmentsV2Response' => [ 'type' => 'structure', 'required' => [ 'Channel', 'Status', 'Segments', ], 'members' => [ 'Channel' => [ 'shape' => 'RealTimeContactAnalysisSupportedChannel', ], 'Status' => [ 'shape' => 'RealTimeContactAnalysisStatus', ], 'Segments' => [ 'shape' => 'RealtimeContactAnalysisSegments', ], 'NextToken' => [ 'shape' => 'LargeNextToken', ], ], ], 'ListRoutingProfileQueuesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListRoutingProfileQueuesResponse' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'RoutingProfileQueueConfigSummaryList' => [ 'shape' => 'RoutingProfileQueueConfigSummaryList', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'ListRoutingProfilesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListRoutingProfilesResponse' => [ 'type' => 'structure', 'members' => [ 'RoutingProfileSummaryList' => [ 'shape' => 'RoutingProfileSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListRulesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'PublishStatus' => [ 'shape' => 'RulePublishStatus', 'location' => 'querystring', 'locationName' => 'publishStatus', ], 'EventSourceName' => [ 'shape' => 'EventSourceName', 'location' => 'querystring', 'locationName' => 'eventSourceName', ], 'MaxResults' => [ 'shape' => 'MaxResult200', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListRulesResponse' => [ 'type' => 'structure', 'required' => [ 'RuleSummaryList', ], 'members' => [ 'RuleSummaryList' => [ 'shape' => 'RuleSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListSecurityKeysRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult2', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListSecurityKeysResponse' => [ 'type' => 'structure', 'members' => [ 'SecurityKeys' => [ 'shape' => 'SecurityKeysList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListSecurityProfileApplicationsRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileId', 'InstanceId', ], 'members' => [ 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', 'location' => 'uri', 'locationName' => 'SecurityProfileId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListSecurityProfileApplicationsResponse' => [ 'type' => 'structure', 'members' => [ 'Applications' => [ 'shape' => 'Applications', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'ListSecurityProfilePermissionsRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileId', 'InstanceId', ], 'members' => [ 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', 'location' => 'uri', 'locationName' => 'SecurityProfileId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListSecurityProfilePermissionsResponse' => [ 'type' => 'structure', 'members' => [ 'Permissions' => [ 'shape' => 'PermissionsList', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'ListSecurityProfilesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListSecurityProfilesResponse' => [ 'type' => 'structure', 'members' => [ 'SecurityProfileSummaryList' => [ 'shape' => 'SecurityProfileSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListTagsForResourceRequest' => [ 'type' => 'structure', 'required' => [ 'resourceArn', ], 'members' => [ 'resourceArn' => [ 'shape' => 'ARN', 'location' => 'uri', 'locationName' => 'resourceArn', ], ], ], 'ListTagsForResourceResponse' => [ 'type' => 'structure', 'members' => [ 'tags' => [ 'shape' => 'TagMap', ], ], ], 'ListTaskTemplatesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'Status' => [ 'shape' => 'TaskTemplateStatus', 'location' => 'querystring', 'locationName' => 'status', ], 'Name' => [ 'shape' => 'TaskTemplateName', 'location' => 'querystring', 'locationName' => 'name', ], ], ], 'ListTaskTemplatesResponse' => [ 'type' => 'structure', 'members' => [ 'TaskTemplates' => [ 'shape' => 'TaskTemplateList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListTrafficDistributionGroupUsersRequest' => [ 'type' => 'structure', 'required' => [ 'TrafficDistributionGroupId', ], 'members' => [ 'TrafficDistributionGroupId' => [ 'shape' => 'TrafficDistributionGroupIdOrArn', 'location' => 'uri', 'locationName' => 'TrafficDistributionGroupId', ], 'MaxResults' => [ 'shape' => 'MaxResult10', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListTrafficDistributionGroupUsersResponse' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'TrafficDistributionGroupUserSummaryList' => [ 'shape' => 'TrafficDistributionGroupUserSummaryList', ], ], ], 'ListTrafficDistributionGroupsRequest' => [ 'type' => 'structure', 'members' => [ 'MaxResults' => [ 'shape' => 'MaxResult10', 'location' => 'querystring', 'locationName' => 'maxResults', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'InstanceId' => [ 'shape' => 'InstanceIdOrArn', 'location' => 'querystring', 'locationName' => 'instanceId', ], ], ], 'ListTrafficDistributionGroupsResponse' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'TrafficDistributionGroupSummaryList' => [ 'shape' => 'TrafficDistributionGroupSummaryList', ], ], ], 'ListUseCasesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'IntegrationAssociationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'IntegrationAssociationId' => [ 'shape' => 'IntegrationAssociationId', 'location' => 'uri', 'locationName' => 'IntegrationAssociationId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListUseCasesResponse' => [ 'type' => 'structure', 'members' => [ 'UseCaseSummaryList' => [ 'shape' => 'UseCaseSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListUserHierarchyGroupsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListUserHierarchyGroupsResponse' => [ 'type' => 'structure', 'members' => [ 'UserHierarchyGroupSummaryList' => [ 'shape' => 'HierarchyGroupSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListUserProficienciesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'UserId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListUserProficienciesResponse' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'UserProficiencyList' => [ 'shape' => 'UserProficiencyList', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'ListUsersRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResult1000', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListUsersResponse' => [ 'type' => 'structure', 'members' => [ 'UserSummaryList' => [ 'shape' => 'UserSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'ListViewVersionsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'NextToken' => [ 'shape' => 'ViewsNextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListViewVersionsResponse' => [ 'type' => 'structure', 'members' => [ 'ViewVersionSummaryList' => [ 'shape' => 'ViewVersionSummaryList', ], 'NextToken' => [ 'shape' => 'ViewsNextToken', ], ], ], 'ListViewsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Type' => [ 'shape' => 'ViewType', 'location' => 'querystring', 'locationName' => 'type', ], 'NextToken' => [ 'shape' => 'ViewsNextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListViewsResponse' => [ 'type' => 'structure', 'members' => [ 'ViewsSummaryList' => [ 'shape' => 'ViewsSummaryList', ], 'NextToken' => [ 'shape' => 'ViewsNextToken', ], ], ], 'Long' => [ 'type' => 'long', ], 'MaxResult10' => [ 'type' => 'integer', 'max' => 10, 'min' => 1, ], 'MaxResult100' => [ 'type' => 'integer', 'max' => 100, 'min' => 1, ], 'MaxResult1000' => [ 'type' => 'integer', 'max' => 1000, 'min' => 1, ], 'MaxResult2' => [ 'type' => 'integer', 'max' => 2, 'min' => 1, ], 'MaxResult200' => [ 'type' => 'integer', 'max' => 200, 'min' => 1, ], 'MaxResult25' => [ 'type' => 'integer', 'max' => 25, 'min' => 1, ], 'MaxResult7' => [ 'type' => 'integer', 'max' => 7, 'min' => 1, ], 'MaxResults' => [ 'type' => 'integer', 'max' => 100, 'min' => 1, ], 'MaximumResultReturnedException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 400, ], 'exception' => true, ], 'MediaConcurrencies' => [ 'type' => 'list', 'member' => [ 'shape' => 'MediaConcurrency', ], ], 'MediaConcurrency' => [ 'type' => 'structure', 'required' => [ 'Channel', 'Concurrency', ], 'members' => [ 'Channel' => [ 'shape' => 'Channel', ], 'Concurrency' => [ 'shape' => 'Concurrency', ], 'CrossChannelBehavior' => [ 'shape' => 'CrossChannelBehavior', ], ], ], 'MediaPlacement' => [ 'type' => 'structure', 'members' => [ 'AudioHostUrl' => [ 'shape' => 'URI', ], 'AudioFallbackUrl' => [ 'shape' => 'URI', ], 'SignalingUrl' => [ 'shape' => 'URI', ], 'TurnControlUrl' => [ 'shape' => 'URI', ], 'EventIngestionUrl' => [ 'shape' => 'URI', ], ], ], 'MediaRegion' => [ 'type' => 'string', ], 'Meeting' => [ 'type' => 'structure', 'members' => [ 'MediaRegion' => [ 'shape' => 'MediaRegion', ], 'MediaPlacement' => [ 'shape' => 'MediaPlacement', ], 'MeetingFeatures' => [ 'shape' => 'MeetingFeaturesConfiguration', ], 'MeetingId' => [ 'shape' => 'MeetingId', ], ], ], 'MeetingFeatureStatus' => [ 'type' => 'string', 'enum' => [ 'AVAILABLE', 'UNAVAILABLE', ], ], 'MeetingFeaturesConfiguration' => [ 'type' => 'structure', 'members' => [ 'Audio' => [ 'shape' => 'AudioFeatures', ], ], ], 'MeetingId' => [ 'type' => 'string', ], 'Message' => [ 'type' => 'string', ], 'MetricDataCollectionsV2' => [ 'type' => 'list', 'member' => [ 'shape' => 'MetricDataV2', ], ], 'MetricDataV2' => [ 'type' => 'structure', 'members' => [ 'Metric' => [ 'shape' => 'MetricV2', ], 'Value' => [ 'shape' => 'Value', 'box' => true, ], ], ], 'MetricFilterV2' => [ 'type' => 'structure', 'members' => [ 'MetricFilterKey' => [ 'shape' => 'String', ], 'MetricFilterValues' => [ 'shape' => 'MetricFilterValueList', ], 'Negate' => [ 'shape' => 'Boolean', ], ], ], 'MetricFilterValueList' => [ 'type' => 'list', 'member' => [ 'shape' => 'String', ], 'max' => 10, 'min' => 1, ], 'MetricFiltersV2List' => [ 'type' => 'list', 'member' => [ 'shape' => 'MetricFilterV2', ], 'max' => 2, ], 'MetricInterval' => [ 'type' => 'structure', 'members' => [ 'Interval' => [ 'shape' => 'IntervalPeriod', ], 'StartTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], ], ], 'MetricNameV2' => [ 'type' => 'string', ], 'MetricResultV2' => [ 'type' => 'structure', 'members' => [ 'Dimensions' => [ 'shape' => 'DimensionsV2Map', ], 'MetricInterval' => [ 'shape' => 'MetricInterval', ], 'Collections' => [ 'shape' => 'MetricDataCollectionsV2', ], ], ], 'MetricResultsV2' => [ 'type' => 'list', 'member' => [ 'shape' => 'MetricResultV2', ], ], 'MetricV2' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'MetricNameV2', ], 'Threshold' => [ 'shape' => 'ThresholdCollections', ], 'MetricFilters' => [ 'shape' => 'MetricFiltersV2List', ], ], ], 'MetricsV2' => [ 'type' => 'list', 'member' => [ 'shape' => 'MetricV2', ], ], 'MinutesLimit60' => [ 'type' => 'integer', 'max' => 59, 'min' => 0, ], 'MonitorCapability' => [ 'type' => 'string', 'enum' => [ 'SILENT_MONITOR', 'BARGE', ], ], 'MonitorContactRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'UserId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', ], 'UserId' => [ 'shape' => 'AgentResourceId', ], 'AllowedMonitorCapabilities' => [ 'shape' => 'AllowedMonitorCapabilities', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'MonitorContactResponse' => [ 'type' => 'structure', 'members' => [ 'ContactId' => [ 'shape' => 'ContactId', ], 'ContactArn' => [ 'shape' => 'ARN', ], ], ], 'Name' => [ 'type' => 'string', 'max' => 512, 'min' => 0, 'sensitive' => true, ], 'Name128' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '(^[\\S].*[\\S]$)|(^[\\S]$)', ], 'Namespace' => [ 'type' => 'string', 'max' => 128, 'min' => 1, ], 'NewChatCreated' => [ 'type' => 'boolean', ], 'NewSessionDetails' => [ 'type' => 'structure', 'members' => [ 'SupportedMessagingContentTypes' => [ 'shape' => 'SupportedMessagingContentTypes', ], 'ParticipantDetails' => [ 'shape' => 'ParticipantDetails', ], 'Attributes' => [ 'shape' => 'Attributes', ], 'StreamingConfiguration' => [ 'shape' => 'ChatStreamingConfiguration', ], ], ], 'NextToken' => [ 'type' => 'string', ], 'NextToken2500' => [ 'type' => 'string', 'max' => 2500, 'min' => 1, ], 'NotificationContentType' => [ 'type' => 'string', 'enum' => [ 'PLAIN_TEXT', ], ], 'NotificationDeliveryType' => [ 'type' => 'string', 'enum' => [ 'EMAIL', ], ], 'NotificationRecipientType' => [ 'type' => 'structure', 'members' => [ 'UserTags' => [ 'shape' => 'UserTagMap', ], 'UserIds' => [ 'shape' => 'UserIdList', ], ], ], 'NumberReference' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ReferenceKey', ], 'Value' => [ 'shape' => 'ReferenceValue', ], ], ], 'NumericQuestionPropertyAutomationLabel' => [ 'type' => 'string', 'enum' => [ 'OVERALL_CUSTOMER_SENTIMENT_SCORE', 'OVERALL_AGENT_SENTIMENT_SCORE', 'NON_TALK_TIME', 'NON_TALK_TIME_PERCENTAGE', 'NUMBER_OF_INTERRUPTIONS', 'CONTACT_DURATION', 'AGENT_INTERACTION_DURATION', 'CUSTOMER_HOLD_TIME', ], ], 'NumericQuestionPropertyValueAutomation' => [ 'type' => 'structure', 'required' => [ 'Label', ], 'members' => [ 'Label' => [ 'shape' => 'NumericQuestionPropertyAutomationLabel', ], ], ], 'Origin' => [ 'type' => 'string', 'max' => 267, ], 'OriginsList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Origin', ], ], 'OutboundCallerConfig' => [ 'type' => 'structure', 'members' => [ 'OutboundCallerIdName' => [ 'shape' => 'OutboundCallerIdName', ], 'OutboundCallerIdNumberId' => [ 'shape' => 'PhoneNumberId', ], 'OutboundFlowId' => [ 'shape' => 'ContactFlowId', ], ], ], 'OutboundCallerIdName' => [ 'type' => 'string', 'max' => 255, 'min' => 1, ], 'OutboundCallsEnabled' => [ 'type' => 'boolean', ], 'OutboundContactNotPermittedException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 403, ], 'exception' => true, ], 'OutputTypeNotFoundException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 404, ], 'exception' => true, ], 'PEM' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'ParticipantCapabilities' => [ 'type' => 'structure', 'members' => [ 'Video' => [ 'shape' => 'VideoCapability', ], ], ], 'ParticipantDetails' => [ 'type' => 'structure', 'required' => [ 'DisplayName', ], 'members' => [ 'DisplayName' => [ 'shape' => 'DisplayName', ], ], ], 'ParticipantDetailsToAdd' => [ 'type' => 'structure', 'members' => [ 'ParticipantRole' => [ 'shape' => 'ParticipantRole', ], 'DisplayName' => [ 'shape' => 'DisplayName', ], ], ], 'ParticipantId' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'ParticipantRole' => [ 'type' => 'string', 'enum' => [ 'AGENT', 'CUSTOMER', 'SYSTEM', 'CUSTOM_BOT', 'SUPERVISOR', ], ], 'ParticipantTimerAction' => [ 'type' => 'string', 'enum' => [ 'Unset', ], ], 'ParticipantTimerConfigList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ParticipantTimerConfiguration', ], 'max' => 6, 'min' => 1, ], 'ParticipantTimerConfiguration' => [ 'type' => 'structure', 'required' => [ 'ParticipantRole', 'TimerType', 'TimerValue', ], 'members' => [ 'ParticipantRole' => [ 'shape' => 'TimerEligibleParticipantRoles', ], 'TimerType' => [ 'shape' => 'ParticipantTimerType', ], 'TimerValue' => [ 'shape' => 'ParticipantTimerValue', ], ], ], 'ParticipantTimerDurationInMinutes' => [ 'type' => 'integer', 'max' => 480, 'min' => 2, ], 'ParticipantTimerType' => [ 'type' => 'string', 'enum' => [ 'IDLE', 'DISCONNECT_NONCUSTOMER', ], ], 'ParticipantTimerValue' => [ 'type' => 'structure', 'members' => [ 'ParticipantTimerAction' => [ 'shape' => 'ParticipantTimerAction', ], 'ParticipantTimerDurationInMinutes' => [ 'shape' => 'ParticipantTimerDurationInMinutes', ], ], 'union' => true, ], 'ParticipantToken' => [ 'type' => 'string', 'max' => 1000, 'min' => 1, ], 'ParticipantTokenCredentials' => [ 'type' => 'structure', 'members' => [ 'ParticipantToken' => [ 'shape' => 'ParticipantToken', ], 'Expiry' => [ 'shape' => 'ISO8601Datetime', ], ], ], 'Password' => [ 'type' => 'string', 'pattern' => '/^(?=.*[a-z])(?=.*[A-Z])(?=.*\\d)[a-zA-Z\\d\\S]{8,64}$/', 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'Boolean', ], ], ], 'RoutingProfileDescription' => [ 'type' => 'string', 'max' => 250, 'min' => 1, ], 'RoutingProfileId' => [ 'type' => 'string', ], 'RoutingProfileList' => [ 'type' => 'list', 'member' => [ 'shape' => 'RoutingProfile', ], ], 'RoutingProfileName' => [ 'type' => 'string', 'max' => 127, 'min' => 1, ], 'RoutingProfileQueueConfig' => [ 'type' => 'structure', 'required' => [ 'QueueReference', 'Priority', 'Delay', ], 'members' => [ 'QueueReference' => [ 'shape' => 'RoutingProfileQueueReference', ], 'Priority' => [ 'shape' => 'Priority', 'box' => true, ], 'Delay' => [ 'shape' => 'Delay', 'box' => true, ], ], ], 'RoutingProfileQueueConfigList' => [ 'type' => 'list', 'member' => [ 'shape' => 'RoutingProfileQueueConfig', ], 'max' => 10, 'min' => 1, ], 'RoutingProfileQueueConfigSummary' => [ 'type' => 'structure', 'required' => [ 'QueueId', 'QueueArn', 'QueueName', 'Priority', 'Delay', 'Channel', ], 'members' => [ 'QueueId' => [ 'shape' => 'QueueId', ], 'QueueArn' => [ 'shape' => 'ARN', ], 'QueueName' => [ 'shape' => 'QueueName', ], 'Priority' => [ 'shape' => 'Priority', ], 'Delay' => [ 'shape' => 'Delay', ], 'Channel' => [ 'shape' => 'Channel', ], ], ], 'RoutingProfileQueueConfigSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'RoutingProfileQueueConfigSummary', ], ], 'RoutingProfileQueueReference' => [ 'type' => 'structure', 'required' => [ 'QueueId', 'Channel', ], 'members' => [ 'QueueId' => [ 'shape' => 'QueueId', ], 'Channel' => [ 'shape' => 'Channel', ], ], ], 'RoutingProfileQueueReferenceList' => [ 'type' => 'list', 'member' => [ 'shape' => 'RoutingProfileQueueReference', ], ], 'RoutingProfileReference' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'RoutingProfileId', ], 'Arn' => [ 'shape' => 'ARN', ], ], ], 'RoutingProfileSearchConditionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'RoutingProfileSearchCriteria', ], ], 'RoutingProfileSearchCriteria' => [ 'type' => 'structure', 'members' => [ 'OrConditions' => [ 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], 'CreateCaseAction' => [ 'shape' => 'CreateCaseActionDefinition', ], 'UpdateCaseAction' => [ 'shape' => 'UpdateCaseActionDefinition', ], 'EndAssociatedTasksAction' => [ 'shape' => 'EndAssociatedTasksActionDefinition', ], ], ], 'RuleActions' => [ 'type' => 'list', 'member' => [ 'shape' => 'RuleAction', ], ], 'RuleFunction' => [ 'type' => 'string', ], 'RuleId' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'RuleName' => [ 'type' => 'string', 'max' => 200, 'min' => 1, 'pattern' => '^[0-9a-zA-Z._-]+', ], 'RulePublishStatus' => [ 'type' => 'string', 'enum' => [ 'DRAFT', 'PUBLISHED', ], ], 'RuleSummary' => [ 'type' => 'structure', 'required' => [ 'Name', 'RuleId', 'RuleArn', 'EventSourceName', 'PublishStatus', 'ActionSummaries', 'CreatedTime', 'LastUpdatedTime', ], 'members' => [ 'Name' => [ 'shape' => 'RuleName', ], 'RuleId' => [ 'shape' => 'RuleId', ], 'RuleArn' => [ 'shape' => 'ARN', ], 'EventSourceName' => [ 'shape' => 'EventSourceName', ], 'PublishStatus' => [ 'shape' => 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[ 'PhoneNumberCountryCode', 'PhoneNumberType', ], 'members' => [ 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'PhoneNumberCountryCode' => [ 'shape' => 'PhoneNumberCountryCode', ], 'PhoneNumberType' => [ 'shape' => 'PhoneNumberType', ], 'PhoneNumberPrefix' => [ 'shape' => 'PhoneNumberPrefix', ], 'MaxResults' => [ 'shape' => 'MaxResult10', 'box' => true, ], 'NextToken' => [ 'shape' => 'LargeNextToken', ], ], ], 'SearchAvailablePhoneNumbersResponse' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'LargeNextToken', ], 'AvailableNumbersList' => [ 'shape' => 'AvailableNumbersList', ], ], ], 'SearchContactsMatchType' => [ 'type' => 'string', 'enum' => [ 'MATCH_ALL', 'MATCH_ANY', ], ], 'SearchContactsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'TimeRange', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'TimeRange' => [ 'shape' => 'SearchContactsTimeRange', ], 'SearchCriteria' => [ 'shape' => 'SearchCriteria', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, ], 'NextToken' => [ 'shape' => 'LargeNextToken', ], 'Sort' => [ 'shape' => 'Sort', ], ], ], 'SearchContactsResponse' => [ 'type' => 'structure', 'required' => [ 'Contacts', ], 'members' => [ 'Contacts' => [ 'shape' => 'Contacts', ], 'NextToken' => [ 'shape' => 'LargeNextToken', ], 'TotalCount' => [ 'shape' => 'TotalCount', ], ], ], 'SearchContactsTimeRange' => [ 'type' => 'structure', 'required' => [ 'Type', 'StartTime', 'EndTime', ], 'members' => [ 'Type' => [ 'shape' => 'SearchContactsTimeRangeType', ], 'StartTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], ], ], 'SearchContactsTimeRangeType' => [ 'type' => 'string', 'enum' => [ 'INITIATION_TIMESTAMP', 'SCHEDULED_TIMESTAMP', 'CONNECTED_TO_AGENT_TIMESTAMP', 'DISCONNECT_TIMESTAMP', ], ], 'SearchCriteria' => [ 'type' => 'structure', 'members' => [ 'AgentIds' => [ 'shape' => 'AgentResourceIdList', ], 'AgentHierarchyGroups' => [ 'shape' => 'AgentHierarchyGroups', ], 'Channels' => [ 'shape' => 'ChannelList', ], 'ContactAnalysis' => [ 'shape' => 'ContactAnalysis', ], 'InitiationMethods' => [ 'shape' => 'InitiationMethodList', ], 'QueueIds' => [ 'shape' => 'QueueIdList', ], 'SearchableContactAttributes' => [ 'shape' => 'SearchableContactAttributes', ], ], ], 'SearchHoursOfOperationsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, ], 'SearchFilter' => [ 'shape' => 'HoursOfOperationSearchFilter', ], 'SearchCriteria' => [ 'shape' => 'HoursOfOperationSearchCriteria', ], ], ], 'SearchHoursOfOperationsResponse' => [ 'type' => 'structure', 'members' => [ 'HoursOfOperations' => [ 'shape' => 'HoursOfOperationList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'ApproximateTotalCount' => [ 'shape' => 'ApproximateTotalCount', ], ], ], 'SearchPredefinedAttributesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, ], 'SearchCriteria' => [ 'shape' => 'PredefinedAttributeSearchCriteria', ], ], ], 'SearchPredefinedAttributesResponse' => [ 'type' => 'structure', 'members' => [ 'PredefinedAttributes' => [ 'shape' => 'PredefinedAttributeSearchSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'ApproximateTotalCount' => [ 'shape' => 'ApproximateTotalCount', ], ], ], 'SearchPromptsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, ], 'SearchFilter' => [ 'shape' => 'PromptSearchFilter', ], 'SearchCriteria' => [ 'shape' => 'PromptSearchCriteria', ], ], ], 'SearchPromptsResponse' => [ 'type' => 'structure', 'members' => [ 'Prompts' => [ 'shape' => 'PromptList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'ApproximateTotalCount' => [ 'shape' => 'ApproximateTotalCount', ], ], ], 'SearchQueuesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, ], 'SearchFilter' => [ 'shape' => 'QueueSearchFilter', ], 'SearchCriteria' => [ 'shape' => 'QueueSearchCriteria', ], ], ], 'SearchQueuesResponse' => [ 'type' => 'structure', 'members' => [ 'Queues' => [ 'shape' => 'QueueSearchSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'ApproximateTotalCount' => [ 'shape' => 'ApproximateTotalCount', ], ], ], 'SearchQuickConnectsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, ], 'SearchFilter' => [ 'shape' => 'QuickConnectSearchFilter', ], 'SearchCriteria' => [ 'shape' => 'QuickConnectSearchCriteria', ], ], ], 'SearchQuickConnectsResponse' => [ 'type' => 'structure', 'members' => [ 'QuickConnects' => [ 'shape' => 'QuickConnectSearchSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'ApproximateTotalCount' => [ 'shape' => 'ApproximateTotalCount', ], ], ], 'SearchResourceTagsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceIdOrArn', ], 'ResourceTypes' => [ 'shape' => 'ResourceTypeList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, ], 'SearchCriteria' => [ 'shape' => 'ResourceTagsSearchCriteria', ], ], ], 'SearchResourceTagsResponse' => [ 'type' => 'structure', 'members' => [ 'Tags' => [ 'shape' => 'TagsList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], ], ], 'SearchRoutingProfilesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'MaxResults' => [ 'shape' => 'MaxResult100', 'box' => true, ], 'SearchFilter' => [ 'shape' => 'RoutingProfileSearchFilter', ], 'SearchCriteria' => [ 'shape' => 'RoutingProfileSearchCriteria', ], ], ], 'SearchRoutingProfilesResponse' => [ 'type' => 'structure', 'members' => [ 'RoutingProfiles' => [ 'shape' => 'RoutingProfileList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'ApproximateTotalCount' => [ 'shape' => 'ApproximateTotalCount', ], ], ], 'SearchSecurityProfilesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'MaxResults' => [ 'shape' => 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], ], 'SearchUsersResponse' => [ 'type' => 'structure', 'members' => [ 'Users' => [ 'shape' => 'UserSearchSummaryList', ], 'NextToken' => [ 'shape' => 'NextToken2500', ], 'ApproximateTotalCount' => [ 'shape' => 'ApproximateTotalCount', ], ], ], 'SearchVocabulariesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'MaxResults' => [ 'shape' => 'MaxResult100', ], 'NextToken' => [ 'shape' => 'VocabularyNextToken', ], 'State' => [ 'shape' => 'VocabularyState', ], 'NameStartsWith' => [ 'shape' => 'VocabularyName', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], ], ], 'SearchVocabulariesResponse' => [ 'type' => 'structure', 'members' => [ 'VocabularySummaryList' => [ 'shape' => 'VocabularySummaryList', ], 'NextToken' => [ 'shape' => 'VocabularyNextToken', ], ], ], 'SearchableContactAttributeKey' => [ 'type' => 'string', 'max' => 100, 'min' => 0, 'sensitive' => true, ], 'SearchableContactAttributeValue' => [ 'type' => 'string', 'max' => 100, 'min' => 0, 'sensitive' => true, ], 'SearchableContactAttributeValueList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SearchableContactAttributeValue', ], 'max' => 20, 'min' => 0, ], 'SearchableContactAttributes' => [ 'type' => 'structure', 'required' => [ 'Criteria', ], 'members' => [ 'Criteria' => [ 'shape' => 'SearchableContactAttributesCriteriaList', ], 'MatchType' => [ 'shape' => 'SearchContactsMatchType', ], ], ], 'SearchableContactAttributesCriteria' => [ 'type' => 'structure', 'required' => [ 'Key', 'Values', ], 'members' => [ 'Key' => [ 'shape' => 'SearchableContactAttributeKey', ], 'Values' => [ 'shape' => 'SearchableContactAttributeValueList', ], ], ], 'SearchableContactAttributesCriteriaList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SearchableContactAttributesCriteria', ], 'max' => 15, 'min' => 0, ], 'SearchableQueueType' => [ 'type' => 'string', 'enum' => [ 'STANDARD', ], ], 'SecurityKey' => [ 'type' => 'structure', 'members' => [ 'AssociationId' => [ 'shape' => 'AssociationId', ], 'Key' => [ 'shape' => 'PEM', ], 'CreationTime' => [ 'shape' => 'timestamp', ], ], ], 'SecurityKeysList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityKey', ], ], 'SecurityProfile' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'SecurityProfileId', ], 'OrganizationResourceId' => [ 'shape' => 'InstanceId', ], 'Arn' => [ 'shape' => 'ARN', ], 'SecurityProfileName' => [ 'shape' => 'SecurityProfileName', ], 'Description' => [ 'shape' => 'SecurityProfileDescription', ], 'Tags' => [ 'shape' => 'TagMap', ], 'AllowedAccessControlTags' => [ 'shape' => 'AllowedAccessControlTags', ], 'TagRestrictedResources' => [ 'shape' => 'TagRestrictedResourceList', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'SecurityProfileDescription' => [ 'type' => 'string', 'max' => 250, ], 'SecurityProfileId' => [ 'type' => 'string', ], 'SecurityProfileIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityProfileId', ], 'max' => 10, 'min' => 1, ], 'SecurityProfileName' => [ 'type' => 'string', ], 'SecurityProfilePermission' => [ 'type' => 'string', 'max' => 128, 'min' => 1, ], 'SecurityProfilePolicyKey' => [ 'type' => 'string', 'max' => 128, 'min' => 1, ], 'SecurityProfilePolicyValue' => [ 'type' => 'string', 'max' => 256, ], 'SecurityProfileSearchConditionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityProfileSearchCriteria', ], ], 'SecurityProfileSearchCriteria' => [ 'type' => 'structure', 'members' => [ 'OrConditions' => [ 'shape' => 'SecurityProfileSearchConditionList', ], 'AndConditions' => [ 'shape' => 'SecurityProfileSearchConditionList', ], 'StringCondition' => [ 'shape' => 'StringCondition', ], ], ], 'SecurityProfileSearchSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'SecurityProfileId', ], 'OrganizationResourceId' => [ 'shape' => 'InstanceId', ], 'Arn' => [ 'shape' => 'ARN', ], 'SecurityProfileName' => [ 'shape' => 'SecurityProfileName', ], 'Description' => [ 'shape' => 'SecurityProfileDescription', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'SecurityProfileSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'SecurityProfileId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'SecurityProfileName', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'SecurityProfileSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityProfileSummary', ], ], 'SecurityProfilesSearchFilter' => [ 'type' => 'structure', 'members' => [ 'TagFilter' => [ 'shape' => 'ControlPlaneTagFilter', ], ], ], 'SecurityProfilesSearchSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityProfileSearchSummary', ], ], 'SecurityToken' => [ 'type' => 'string', 'sensitive' => true, ], 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], 'UntagContactRequest' => [ 'type' => 'structure', 'required' => [ 'ContactId', 'InstanceId', 'TagKeys', ], 'members' => [ 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'TagKeys' => [ 'shape' => 'ContactTagKeys', 'location' => 'querystring', 'locationName' => 'TagKeys', ], ], ], 'UntagContactResponse' => [ 'type' => 'structure', 'members' => [], ], 'UntagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'resourceArn', 'tagKeys', ], 'members' => [ 'resourceArn' => [ 'shape' => 'ARN', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'tagKeys' => [ 'shape' => 'TagKeyList', 'location' => 'querystring', 'locationName' => 'tagKeys', ], ], ], 'UpdateAgentStatusDescription' => [ 'type' => 'string', 'max' => 250, 'min' => 0, ], 'UpdateAgentStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AgentStatusId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AgentStatusId' => [ 'shape' => 'AgentStatusId', 'location' => 'uri', 'locationName' => 'AgentStatusId', ], 'Name' => [ 'shape' => 'AgentStatusName', ], 'Description' => [ 'shape' => 'UpdateAgentStatusDescription', ], 'State' => [ 'shape' => 'AgentStatusState', ], 'DisplayOrder' => [ 'shape' => 'AgentStatusOrderNumber', 'box' => true, ], 'ResetOrderNumber' => [ 'shape' => 'Boolean', ], ], ], 'UpdateCaseActionDefinition' => [ 'type' => 'structure', 'required' => [ 'Fields', ], 'members' => [ 'Fields' => [ 'shape' => 'FieldValues', ], ], ], 'UpdateContactAttributesRequest' => [ 'type' => 'structure', 'required' => [ 'InitialContactId', 'InstanceId', 'Attributes', ], 'members' => [ 'InitialContactId' => [ 'shape' => 'ContactId', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'Attributes' => [ 'shape' => 'Attributes', ], ], ], 'UpdateContactAttributesResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactEvaluationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationId', ], 'Answers' => [ 'shape' => 'EvaluationAnswersInputMap', ], 'Notes' => [ 'shape' => 'EvaluationNotesMap', ], ], ], 'UpdateContactEvaluationResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationId', 'EvaluationArn', ], 'members' => [ 'EvaluationId' => [ 'shape' => 'ResourceId', ], 'EvaluationArn' => [ 'shape' => 'ARN', ], ], ], 'UpdateContactFlowContentRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], 'Content' => [ 'shape' => 'ContactFlowContent', ], ], ], 'UpdateContactFlowContentResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactFlowMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'Description' => [ 'shape' => 'ContactFlowDescription', ], 'ContactFlowState' => [ 'shape' => 'ContactFlowState', ], ], ], 'UpdateContactFlowMetadataResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactFlowModuleContentRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowModuleId', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowModuleId' => [ 'shape' => 'ContactFlowModuleId', 'location' => 'uri', 'locationName' => 'ContactFlowModuleId', ], 'Content' => [ 'shape' => 'ContactFlowModuleContent', ], ], ], 'UpdateContactFlowModuleContentResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactFlowModuleMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowModuleId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowModuleId' => [ 'shape' => 'ContactFlowModuleId', 'location' => 'uri', 'locationName' => 'ContactFlowModuleId', ], 'Name' => [ 'shape' => 'ContactFlowModuleName', ], 'Description' => [ 'shape' => 'ContactFlowModuleDescription', ], 'State' => [ 'shape' => 'ContactFlowModuleState', ], ], ], 'UpdateContactFlowModuleMetadataResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactFlowNameRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactFlowId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', 'location' => 'uri', 'locationName' => 'ContactFlowId', ], 'Name' => [ 'shape' => 'ContactFlowName', ], 'Description' => [ 'shape' => 'ContactFlowDescription', ], ], ], 'UpdateContactFlowNameResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'Name' => [ 'shape' => 'Name', ], 'Description' => [ 'shape' => 'Description', ], 'References' => [ 'shape' => 'ContactReferences', ], ], ], 'UpdateContactResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactRoutingDataRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'QueueTimeAdjustmentSeconds' => [ 'shape' => 'QueueTimeAdjustmentSeconds', ], 'QueuePriority' => [ 'shape' => 'QueuePriority', ], ], ], 'UpdateContactRoutingDataResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateContactScheduleRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'ScheduledTime', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', ], 'ScheduledTime' => [ 'shape' => 'Timestamp', ], ], ], 'UpdateContactScheduleResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateEvaluationFormRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'EvaluationFormId', 'EvaluationFormVersion', 'Title', 'Items', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'EvaluationFormId' => [ 'shape' => 'ResourceId', 'location' => 'uri', 'locationName' => 'EvaluationFormId', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], 'CreateNewVersion' => [ 'shape' => 'BoxedBoolean', 'box' => true, ], 'Title' => [ 'shape' => 'EvaluationFormTitle', ], 'Description' => [ 'shape' => 'EvaluationFormDescription', ], 'Items' => [ 'shape' => 'EvaluationFormItemsList', ], 'ScoringStrategy' => [ 'shape' => 'EvaluationFormScoringStrategy', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'UpdateEvaluationFormResponse' => [ 'type' => 'structure', 'required' => [ 'EvaluationFormId', 'EvaluationFormArn', 'EvaluationFormVersion', ], 'members' => [ 'EvaluationFormId' => [ 'shape' => 'ResourceId', ], 'EvaluationFormArn' => [ 'shape' => 'ARN', ], 'EvaluationFormVersion' => [ 'shape' => 'VersionNumber', ], ], ], 'UpdateHoursOfOperationDescription' => [ 'type' => 'string', 'max' => 250, 'min' => 0, ], 'UpdateHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', 'location' => 'uri', 'locationName' => 'HoursOfOperationId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'UpdateHoursOfOperationDescription', ], 'TimeZone' => [ 'shape' => 'TimeZone', ], 'Config' => [ 'shape' => 'HoursOfOperationConfigList', ], ], ], 'UpdateInstanceAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AttributeType', 'Value', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AttributeType' => [ 'shape' => 'InstanceAttributeType', 'location' => 'uri', 'locationName' => 'AttributeType', ], 'Value' => [ 'shape' => 'InstanceAttributeValue', ], ], ], 'UpdateInstanceStorageConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'AssociationId', 'ResourceType', 'StorageConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AssociationId' => [ 'shape' => 'AssociationId', 'location' => 'uri', 'locationName' => 'AssociationId', ], 'ResourceType' => [ 'shape' => 'InstanceStorageResourceType', 'location' => 'querystring', 'locationName' => 'resourceType', ], 'StorageConfig' => [ 'shape' => 'InstanceStorageConfig', ], ], ], 'UpdateParticipantRoleConfigChannelInfo' => [ 'type' => 'structure', 'members' => [ 'Chat' => [ 'shape' => 'ChatParticipantRoleConfig', ], ], 'union' => true, ], 'UpdateParticipantRoleConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ContactId', 'ChannelConfiguration', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ContactId' => [ 'shape' => 'ContactId', 'location' => 'uri', 'locationName' => 'ContactId', ], 'ChannelConfiguration' => [ 'shape' => 'UpdateParticipantRoleConfigChannelInfo', ], ], ], 'UpdateParticipantRoleConfigResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdatePhoneNumberMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneNumberId', ], 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', 'location' => 'uri', 'locationName' => 'PhoneNumberId', ], 'PhoneNumberDescription' => [ 'shape' => 'PhoneNumberDescription', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'UpdatePhoneNumberRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneNumberId', ], 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', 'location' => 'uri', 'locationName' => 'PhoneNumberId', ], 'TargetArn' => [ 'shape' => 'ARN', ], 'InstanceId' => [ 'shape' => 'InstanceId', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], ], ], 'UpdatePhoneNumberResponse' => [ 'type' => 'structure', 'members' => [ 'PhoneNumberId' => [ 'shape' => 'PhoneNumberId', ], 'PhoneNumberArn' => [ 'shape' => 'ARN', ], ], ], 'UpdatePredefinedAttributeRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'Name', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'PredefinedAttributeName', 'location' => 'uri', 'locationName' => 'Name', ], 'Values' => [ 'shape' => 'PredefinedAttributeValues', ], ], ], 'UpdatePromptRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'PromptId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'PromptId' => [ 'shape' => 'PromptId', 'location' => 'uri', 'locationName' => 'PromptId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'PromptDescription', ], 'S3Uri' => [ 'shape' => 'S3Uri', ], ], ], 'UpdatePromptResponse' => [ 'type' => 'structure', 'members' => [ 'PromptARN' => [ 'shape' => 'ARN', ], 'PromptId' => [ 'shape' => 'PromptId', ], ], ], 'UpdateQueueHoursOfOperationRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', 'HoursOfOperationId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'HoursOfOperationId' => [ 'shape' => 'HoursOfOperationId', ], ], ], 'UpdateQueueMaxContactsRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'MaxContacts' => [ 'shape' => 'QueueMaxContacts', 'box' => true, ], ], ], 'UpdateQueueNameRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'Name' => [ 'shape' => 'CommonNameLength127', ], 'Description' => [ 'shape' => 'QueueDescription', ], ], ], 'UpdateQueueOutboundCallerConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', 'OutboundCallerConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'OutboundCallerConfig' => [ 'shape' => 'OutboundCallerConfig', ], ], ], 'UpdateQueueStatusRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QueueId', 'Status', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QueueId' => [ 'shape' => 'QueueId', 'location' => 'uri', 'locationName' => 'QueueId', ], 'Status' => [ 'shape' => 'QueueStatus', ], ], ], 'UpdateQuickConnectConfigRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QuickConnectId', 'QuickConnectConfig', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', 'location' => 'uri', 'locationName' => 'QuickConnectId', ], 'QuickConnectConfig' => [ 'shape' => 'QuickConnectConfig', ], ], ], 'UpdateQuickConnectDescription' => [ 'type' => 'string', 'max' => 250, 'min' => 0, ], 'UpdateQuickConnectNameRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'QuickConnectId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'QuickConnectId' => [ 'shape' => 'QuickConnectId', 'location' => 'uri', 'locationName' => 'QuickConnectId', ], 'Name' => [ 'shape' => 'QuickConnectName', ], 'Description' => [ 'shape' => 'UpdateQuickConnectDescription', ], ], ], 'UpdateRoutingProfileAgentAvailabilityTimerRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'AgentAvailabilityTimer', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'AgentAvailabilityTimer' => [ 'shape' => 'AgentAvailabilityTimer', ], ], ], 'UpdateRoutingProfileConcurrencyRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'MediaConcurrencies', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'MediaConcurrencies' => [ 'shape' => 'MediaConcurrencies', ], ], ], 'UpdateRoutingProfileDefaultOutboundQueueRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'DefaultOutboundQueueId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'DefaultOutboundQueueId' => [ 'shape' => 'QueueId', ], ], ], 'UpdateRoutingProfileNameRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'Name' => [ 'shape' => 'RoutingProfileName', ], 'Description' => [ 'shape' => 'RoutingProfileDescription', ], ], ], 'UpdateRoutingProfileQueuesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'RoutingProfileId', 'QueueConfigs', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', 'location' => 'uri', 'locationName' => 'RoutingProfileId', ], 'QueueConfigs' => [ 'shape' => 'RoutingProfileQueueConfigList', ], ], ], 'UpdateRuleRequest' => [ 'type' => 'structure', 'required' => [ 'RuleId', 'InstanceId', 'Name', 'Function', 'Actions', 'PublishStatus', ], 'members' => [ 'RuleId' => [ 'shape' => 'RuleId', 'location' => 'uri', 'locationName' => 'RuleId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'RuleName', ], 'Function' => [ 'shape' => 'RuleFunction', ], 'Actions' => [ 'shape' => 'RuleActions', ], 'PublishStatus' => [ 'shape' => 'RulePublishStatus', ], ], ], 'UpdateSecurityProfileRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileId', 'InstanceId', ], 'members' => [ 'Description' => [ 'shape' => 'SecurityProfileDescription', ], 'Permissions' => [ 'shape' => 'PermissionsList', ], 'SecurityProfileId' => [ 'shape' => 'SecurityProfileId', 'location' => 'uri', 'locationName' => 'SecurityProfileId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'AllowedAccessControlTags' => [ 'shape' => 'AllowedAccessControlTags', ], 'TagRestrictedResources' => [ 'shape' => 'TagRestrictedResourceList', ], 'Applications' => [ 'shape' => 'Applications', ], ], ], 'UpdateTaskTemplateRequest' => [ 'type' => 'structure', 'required' => [ 'TaskTemplateId', 'InstanceId', ], 'members' => [ 'TaskTemplateId' => [ 'shape' => 'TaskTemplateId', 'location' => 'uri', 'locationName' => 'TaskTemplateId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'Name' => [ 'shape' => 'TaskTemplateName', ], 'Description' => [ 'shape' => 'TaskTemplateDescription', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'Constraints' => [ 'shape' => 'TaskTemplateConstraints', ], 'Defaults' => [ 'shape' => 'TaskTemplateDefaults', ], 'Status' => [ 'shape' => 'TaskTemplateStatus', ], 'Fields' => [ 'shape' => 'TaskTemplateFields', ], ], ], 'UpdateTaskTemplateResponse' => [ 'type' => 'structure', 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', ], 'Id' => [ 'shape' => 'TaskTemplateId', ], 'Arn' => [ 'shape' => 'TaskTemplateArn', ], 'Name' => [ 'shape' => 'TaskTemplateName', ], 'Description' => [ 'shape' => 'TaskTemplateDescription', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], 'Constraints' => [ 'shape' => 'TaskTemplateConstraints', ], 'Defaults' => [ 'shape' => 'TaskTemplateDefaults', ], 'Fields' => [ 'shape' => 'TaskTemplateFields', ], 'Status' => [ 'shape' => 'TaskTemplateStatus', ], 'LastModifiedTime' => [ 'shape' => 'timestamp', ], 'CreatedTime' => [ 'shape' => 'timestamp', ], ], ], 'UpdateTrafficDistributionRequest' => [ 'type' => 'structure', 'required' => [ 'Id', ], 'members' => [ 'Id' => [ 'shape' => 'TrafficDistributionGroupIdOrArn', 'location' => 'uri', 'locationName' => 'Id', ], 'TelephonyConfig' => [ 'shape' => 'TelephonyConfig', ], 'SignInConfig' => [ 'shape' => 'SignInConfig', ], 'AgentConfig' => [ 'shape' => 'AgentConfig', ], ], ], 'UpdateTrafficDistributionResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateUserHierarchyGroupNameRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'HierarchyGroupId', 'InstanceId', ], 'members' => [ 'Name' => [ 'shape' => 'HierarchyGroupName', ], 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', 'location' => 'uri', 'locationName' => 'HierarchyGroupId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserHierarchyRequest' => [ 'type' => 'structure', 'required' => [ 'UserId', 'InstanceId', ], 'members' => [ 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserHierarchyStructureRequest' => [ 'type' => 'structure', 'required' => [ 'HierarchyStructure', 'InstanceId', ], 'members' => [ 'HierarchyStructure' => [ 'shape' => 'HierarchyStructureUpdate', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserIdentityInfoRequest' => [ 'type' => 'structure', 'required' => [ 'IdentityInfo', 'UserId', 'InstanceId', ], 'members' => [ 'IdentityInfo' => [ 'shape' => 'UserIdentityInfo', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserPhoneConfigRequest' => [ 'type' => 'structure', 'required' => [ 'PhoneConfig', 'UserId', 'InstanceId', ], 'members' => [ 'PhoneConfig' => [ 'shape' => 'UserPhoneConfig', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserProficienciesRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'UserId', 'UserProficiencies', ], 'members' => [ 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'UserProficiencies' => [ 'shape' => 'UserProficiencyList', ], ], ], 'UpdateUserRoutingProfileRequest' => [ 'type' => 'structure', 'required' => [ 'RoutingProfileId', 'UserId', 'InstanceId', ], 'members' => [ 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateUserSecurityProfilesRequest' => [ 'type' => 'structure', 'required' => [ 'SecurityProfileIds', 'UserId', 'InstanceId', ], 'members' => [ 'SecurityProfileIds' => [ 'shape' => 'SecurityProfileIds', ], 'UserId' => [ 'shape' => 'UserId', 'location' => 'uri', 'locationName' => 'UserId', ], 'InstanceId' => [ 'shape' => 'InstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], ], ], 'UpdateViewContentRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', 'Status', 'Content', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'Status' => [ 'shape' => 'ViewStatus', ], 'Content' => [ 'shape' => 'ViewInputContent', ], ], ], 'UpdateViewContentResponse' => [ 'type' => 'structure', 'members' => [ 'View' => [ 'shape' => 'View', ], ], ], 'UpdateViewMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'InstanceId', 'ViewId', ], 'members' => [ 'InstanceId' => [ 'shape' => 'ViewsInstanceId', 'location' => 'uri', 'locationName' => 'InstanceId', ], 'ViewId' => [ 'shape' => 'ViewId', 'location' => 'uri', 'locationName' => 'ViewId', ], 'Name' => [ 'shape' => 'ViewName', ], 'Description' => [ 'shape' => 'ViewDescription', ], ], ], 'UpdateViewMetadataResponse' => [ 'type' => 'structure', 'members' => [], ], 'Url' => [ 'type' => 'string', ], 'UrlReference' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ReferenceKey', ], 'Value' => [ 'shape' => 'ReferenceValue', ], ], ], 'UseCase' => [ 'type' => 'structure', 'members' => [ 'UseCaseId' => [ 'shape' => 'UseCaseId', ], 'UseCaseArn' => [ 'shape' => 'ARN', ], 'UseCaseType' => [ 'shape' => 'UseCaseType', ], ], ], 'UseCaseId' => [ 'type' => 'string', 'max' => 200, 'min' => 1, ], 'UseCaseSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UseCase', ], ], 'UseCaseType' => [ 'type' => 'string', 'enum' => [ 'RULES_EVALUATION', 'CONNECT_CAMPAIGNS', ], ], 'User' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'UserId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Username' => [ 'shape' => 'AgentUsername', ], 'IdentityInfo' => [ 'shape' => 'UserIdentityInfo', ], 'PhoneConfig' => [ 'shape' => 'UserPhoneConfig', ], 'DirectoryUserId' => [ 'shape' => 'DirectoryUserId', ], 'SecurityProfileIds' => [ 'shape' => 'SecurityProfileIds', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'Tags' => [ 'shape' => 'TagMap', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'UserData' => [ 'type' => 'structure', 'members' => [ 'User' => [ 'shape' => 'UserReference', ], 'RoutingProfile' => [ 'shape' => 'RoutingProfileReference', ], 'HierarchyPath' => [ 'shape' => 'HierarchyPathReference', ], 'Status' => [ 'shape' => 'AgentStatusReference', ], 'AvailableSlotsByChannel' => [ 'shape' => 'ChannelToCountMap', ], 'MaxSlotsByChannel' => [ 'shape' => 'ChannelToCountMap', ], 'ActiveSlotsByChannel' => [ 'shape' => 'ChannelToCountMap', ], 'Contacts' => [ 'shape' => 'AgentContactReferenceList', ], 'NextStatus' => [ 'shape' => 'AgentStatusName', ], ], ], 'UserDataFilters' => [ 'type' => 'structure', 'members' => [ 'Queues' => [ 'shape' => 'Queues', ], 'ContactFilter' => [ 'shape' => 'ContactFilter', ], 'RoutingProfiles' => [ 'shape' => 'RoutingProfiles', ], 'Agents' => [ 'shape' => 'AgentsMinOneMaxHundred', ], 'UserHierarchyGroups' => [ 'shape' => 'UserDataHierarchyGroups', ], ], ], 'UserDataHierarchyGroups' => [ 'type' => 'list', 'member' => [ 'shape' => 'HierarchyGroupId', ], 'max' => 1, 'min' => 1, ], 'UserDataList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserData', ], ], 'UserId' => [ 'type' => 'string', ], 'UserIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserId', ], ], 'UserIdentityInfo' => [ 'type' => 'structure', 'members' => [ 'FirstName' => [ 'shape' => 'AgentFirstName', ], 'LastName' => [ 'shape' => 'AgentLastName', ], 'Email' => [ 'shape' => 'Email', ], 'SecondaryEmail' => [ 'shape' => 'Email', ], 'Mobile' => [ 'shape' => 'PhoneNumber', ], ], ], 'UserIdentityInfoLite' => [ 'type' => 'structure', 'members' => [ 'FirstName' => [ 'shape' => 'AgentFirstName', ], 'LastName' => [ 'shape' => 'AgentLastName', ], ], ], 'UserNotFoundException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'Message', ], ], 'error' => [ 'httpStatusCode' => 404, ], 'exception' => true, ], 'UserPhoneConfig' => [ 'type' => 'structure', 'required' => [ 'PhoneType', ], 'members' => [ 'PhoneType' => [ 'shape' => 'PhoneType', ], 'AutoAccept' => [ 'shape' => 'AutoAccept', ], 'AfterContactWorkTimeLimit' => [ 'shape' => 'AfterContactWorkTimeLimit', ], 'DeskPhoneNumber' => [ 'shape' => 'PhoneNumber', ], ], ], 'UserProficiency' => [ 'type' => 'structure', 'required' => [ 'AttributeName', 'AttributeValue', 'Level', ], 'members' => [ 'AttributeName' => [ 'shape' => 'PredefinedAttributeName', ], 'AttributeValue' => [ 'shape' => 'PredefinedAttributeStringValue', ], 'Level' => [ 'shape' => 'ProficiencyLevel', ], ], ], 'UserProficiencyDisassociate' => [ 'type' => 'structure', 'required' => [ 'AttributeName', 'AttributeValue', ], 'members' => [ 'AttributeName' => [ 'shape' => 'PredefinedAttributeName', ], 'AttributeValue' => [ 'shape' => 'PredefinedAttributeStringValue', ], ], ], 'UserProficiencyDisassociateList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserProficiencyDisassociate', ], ], 'UserProficiencyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserProficiency', ], ], 'UserQuickConnectConfig' => [ 'type' => 'structure', 'required' => [ 'UserId', 'ContactFlowId', ], 'members' => [ 'UserId' => [ 'shape' => 'UserId', ], 'ContactFlowId' => [ 'shape' => 'ContactFlowId', ], ], ], 'UserReference' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'UserId', ], 'Arn' => [ 'shape' => 'ARN', ], ], ], 'UserSearchConditionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserSearchCriteria', ], ], 'UserSearchCriteria' => [ 'type' => 'structure', 'members' => [ 'OrConditions' => [ 'shape' => 'UserSearchConditionList', ], 'AndConditions' => [ 'shape' => 'UserSearchConditionList', ], 'StringCondition' => [ 'shape' => 'StringCondition', ], 'HierarchyGroupCondition' => [ 'shape' => 'HierarchyGroupCondition', ], ], ], 'UserSearchFilter' => [ 'type' => 'structure', 'members' => [ 'TagFilter' => [ 'shape' => 'ControlPlaneTagFilter', ], ], ], 'UserSearchSummary' => [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'ARN', ], 'DirectoryUserId' => [ 'shape' => 'DirectoryUserId', ], 'HierarchyGroupId' => [ 'shape' => 'HierarchyGroupId', ], 'Id' => [ 'shape' => 'UserId', ], 'IdentityInfo' => [ 'shape' => 'UserIdentityInfoLite', ], 'PhoneConfig' => [ 'shape' => 'UserPhoneConfig', ], 'RoutingProfileId' => [ 'shape' => 'RoutingProfileId', ], 'SecurityProfileIds' => [ 'shape' => 'SecurityProfileIds', ], 'Tags' => [ 'shape' => 'TagMap', ], 'Username' => [ 'shape' => 'AgentUsername', ], ], ], 'UserSearchSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserSearchSummary', ], ], 'UserSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'UserId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Username' => [ 'shape' => 'AgentUsername', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedRegion' => [ 'shape' => 'RegionName', ], ], ], 'UserSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserSummary', ], ], 'UserTagMap' => [ 'type' => 'map', 'key' => [ 'shape' => 'String', ], 'value' => [ 'shape' => 'String', ], ], 'Value' => [ 'type' => 'double', ], 'VersionNumber' => [ 'type' => 'integer', 'min' => 1, ], 'VideoCapability' => [ 'type' => 'string', 'enum' => [ 'SEND', ], ], 'View' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ViewId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'ViewName', ], 'Status' => [ 'shape' => 'ViewStatus', ], 'Type' => [ 'shape' => 'ViewType', ], 'Description' => [ 'shape' => 'ViewDescription', ], 'Version' => [ 'shape' => 'ViewVersion', ], 'VersionDescription' => [ 'shape' => 'ViewDescription', ], 'Content' => [ 'shape' => 'ViewContent', ], 'Tags' => [ 'shape' => 'TagMap', ], 'CreatedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'ViewContentSha256' => [ 'shape' => 'ViewContentSha256', ], ], ], 'ViewAction' => [ 'type' => 'string', 'max' => 255, 'min' => 1, 'pattern' => '^([\\p{L}\\p{N}_.:\\/=+\\-@()\']+[\\p{L}\\p{Z}\\p{N}_.:\\/=+\\-@()\']*)$', 'sensitive' => true, ], 'ViewActions' => [ 'type' => 'list', 'member' => [ 'shape' => 'ViewAction', ], ], 'ViewContent' => [ 'type' => 'structure', 'members' => [ 'InputSchema' => [ 'shape' => 'ViewInputSchema', ], 'Template' => [ 'shape' => 'ViewTemplate', ], 'Actions' => [ 'shape' => 'ViewActions', ], ], ], 'ViewContentSha256' => [ 'type' => 'string', 'max' => 64, 'min' => 1, 'pattern' => '^[a-zA-Z0-9]$', ], 'ViewDescription' => [ 'type' => 'string', 'max' => 4096, 'min' => 1, 'pattern' => '^([\\p{L}\\p{N}_.:\\/=+\\-@,()\']+[\\p{L}\\p{Z}\\p{N}_.:\\/=+\\-@,()\']*)$', ], 'ViewId' => [ 'type' => 'string', 'max' => 500, 'min' => 1, 'pattern' => '^[a-zA-Z0-9\\_\\-:\\/$]+$', ], 'ViewInputContent' => [ 'type' => 'structure', 'members' => [ 'Template' => [ 'shape' => 'ViewTemplate', ], 'Actions' => [ 'shape' => 'ViewActions', ], ], ], 'ViewInputSchema' => [ 'type' => 'string', 'sensitive' => true, ], 'ViewName' => [ 'type' => 'string', 'max' => 255, 'min' => 1, 'pattern' => '^([\\p{L}\\p{N}_.:\\/=+\\-@()\']+[\\p{L}\\p{Z}\\p{N}_.:\\/=+\\-@()\']*)$', 'sensitive' => true, ], 'ViewStatus' => [ 'type' => 'string', 'enum' => [ 'PUBLISHED', 'SAVED', ], ], 'ViewSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ViewId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Name' => [ 'shape' => 'ViewName', ], 'Type' => [ 'shape' => 'ViewType', ], 'Status' => [ 'shape' => 'ViewStatus', ], 'Description' => [ 'shape' => 'ViewDescription', ], ], ], 'ViewTemplate' => [ 'type' => 'string', ], 'ViewType' => [ 'type' => 'string', 'enum' => [ 'CUSTOMER_MANAGED', 'AWS_MANAGED', ], ], 'ViewVersion' => [ 'type' => 'integer', ], 'ViewVersionSummary' => [ 'type' => 'structure', 'members' => [ 'Id' => [ 'shape' => 'ViewId', ], 'Arn' => [ 'shape' => 'ARN', ], 'Description' => [ 'shape' => 'ViewDescription', ], 'Name' => [ 'shape' => 'ViewName', ], 'Type' => [ 'shape' => 'ViewType', ], 'Version' => [ 'shape' => 'ViewVersion', ], 'VersionDescription' => [ 'shape' => 'ViewDescription', ], ], ], 'ViewVersionSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ViewVersionSummary', ], ], 'ViewsClientToken' => [ 'type' => 'string', 'max' => 500, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:\\/=+\\-@]*)$', ], 'ViewsInstanceId' => [ 'type' => 'string', 'max' => 100, 'min' => 1, 'pattern' => '^[a-zA-Z0-9\\_\\-:\\/]+$', ], 'ViewsNextToken' => [ 'type' => 'string', 'max' => 4096, 'min' => 1, 'pattern' => '^[a-zA-Z0-9=\\/+_.-]+$', ], 'ViewsSummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ViewSummary', ], ], 'Vocabulary' => [ 'type' => 'structure', 'required' => [ 'Name', 'Id', 'Arn', 'LanguageCode', 'State', 'LastModifiedTime', ], 'members' => [ 'Name' => [ 'shape' => 'VocabularyName', ], 'Id' => [ 'shape' => 'VocabularyId', ], 'Arn' => [ 'shape' => 'ARN', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], 'State' => [ 'shape' => 'VocabularyState', ], 'LastModifiedTime' => [ 'shape' => 'VocabularyLastModifiedTime', ], 'FailureReason' => [ 'shape' => 'VocabularyFailureReason', ], 'Content' => [ 'shape' => 'VocabularyContent', ], 'Tags' => [ 'shape' => 'TagMap', ], ], ], 'VocabularyContent' => [ 'type' => 'string', 'max' => 60000, 'min' => 1, ], 'VocabularyFailureReason' => [ 'type' => 'string', ], 'VocabularyId' => [ 'type' => 'string', 'max' => 500, 'min' => 1, ], 'VocabularyLanguageCode' => [ 'type' => 'string', 'enum' => [ 'ar-AE', 'de-CH', 'de-DE', 'en-AB', 'en-AU', 'en-GB', 'en-IE', 'en-IN', 'en-US', 'en-WL', 'es-ES', 'es-US', 'fr-CA', 'fr-FR', 'hi-IN', 'it-IT', 'ja-JP', 'ko-KR', 'pt-BR', 'pt-PT', 'zh-CN', 'en-NZ', 'en-ZA', ], ], 'VocabularyLastModifiedTime' => [ 'type' => 'timestamp', ], 'VocabularyName' => [ 'type' => 'string', 'max' => 140, 'min' => 1, 'pattern' => '^[0-9a-zA-Z._-]+', ], 'VocabularyNextToken' => [ 'type' => 'string', 'max' => 131070, 'min' => 1, 'pattern' => '.*\\S.*', ], 'VocabularyState' => [ 'type' => 'string', 'enum' => [ 'CREATION_IN_PROGRESS', 'ACTIVE', 'CREATION_FAILED', 'DELETE_IN_PROGRESS', ], ], 'VocabularySummary' => [ 'type' => 'structure', 'required' => [ 'Name', 'Id', 'Arn', 'LanguageCode', 'State', 'LastModifiedTime', ], 'members' => [ 'Name' => [ 'shape' => 'VocabularyName', ], 'Id' => [ 'shape' => 'VocabularyId', ], 'Arn' => [ 'shape' => 'ARN', ], 'LanguageCode' => [ 'shape' => 'VocabularyLanguageCode', ], 'State' => [ 'shape' => 'VocabularyState', ], 'LastModifiedTime' => [ 'shape' => 'VocabularyLastModifiedTime', ], 'FailureReason' => [ 'shape' => 'VocabularyFailureReason', ], ], ], 'VocabularySummaryList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VocabularySummary', ], ], 'VoiceRecordingConfiguration' => [ 'type' => 'structure', 'members' => [ 'VoiceRecordingTrack' => [ 'shape' => 'VoiceRecordingTrack', ], ], ], 'VoiceRecordingTrack' => [ 'type' => 'string', 'enum' => [ 'FROM_AGENT', 'TO_AGENT', 'ALL', ], ], 'WisdomInfo' => [ 'type' => 'structure', 'members' => [ 'SessionArn' => [ 'shape' => 'ARN', ], ], ], 'resourceArnListMaxLimit100' => [ 'type' => 'list', 'member' => [ 'shape' => 'ARN', ], 'max' => 100, 'min' => 1, ], 'timestamp' => [ 'type' => 'timestamp', ], ],]; diff --git a/src/data/inspector2/2020-06-08/api-2.json b/src/data/inspector2/2020-06-08/api-2.json index adc13b478b..dd31548c61 100644 --- a/src/data/inspector2/2020-06-08/api-2.json +++ b/src/data/inspector2/2020-06-08/api-2.json @@ -1894,7 +1894,7 @@ "CisSessionMessages":{ "type":"list", "member":{"shape":"CisSessionMessage"}, - "max":50, + "max":150, "min":1 }, "CisSortOrder":{ @@ -2173,6 +2173,7 @@ "ec2InstanceTags":{"shape":"CoverageMapFilterList"}, "ecrImageTags":{"shape":"CoverageStringFilterList"}, "ecrRepositoryName":{"shape":"CoverageStringFilterList"}, + "imagePulledAt":{"shape":"CoverageDateFilterList"}, "lambdaFunctionName":{"shape":"CoverageStringFilterList"}, "lambdaFunctionRuntime":{"shape":"CoverageStringFilterList"}, "lambdaFunctionTags":{"shape":"CoverageMapFilterList"}, @@ -2698,6 +2699,7 @@ "type":"structure", "required":["rescanDuration"], "members":{ + "pullDateRescanDuration":{"shape":"EcrPullDateRescanDuration"}, "rescanDuration":{"shape":"EcrRescanDuration"} } }, @@ -2710,9 +2712,20 @@ "EcrContainerImageMetadata":{ "type":"structure", "members":{ + "imagePulledAt":{"shape":"DateTimeTimestamp"}, "tags":{"shape":"TagList"} } }, + "EcrPullDateRescanDuration":{ + "type":"string", + "enum":[ + "DAYS_14", + "DAYS_30", + "DAYS_60", + "DAYS_90", + "DAYS_180" + ] + }, "EcrRepositoryMetadata":{ "type":"structure", "members":{ @@ -2725,12 +2738,16 @@ "enum":[ "LIFETIME", "DAYS_30", - "DAYS_180" + "DAYS_180", + "DAYS_14", + "DAYS_60", + "DAYS_90" ] }, "EcrRescanDurationState":{ "type":"structure", "members":{ + "pullDateRescanDuration":{"shape":"EcrPullDateRescanDuration"}, "rescanDuration":{"shape":"EcrRescanDuration"}, "status":{"shape":"EcrRescanDurationStatus"}, "updatedAt":{"shape":"DateTimeTimestamp"} diff --git a/src/data/inspector2/2020-06-08/api-2.json.php b/src/data/inspector2/2020-06-08/api-2.json.php index 51c5b72ddd..343d6de84a 100644 --- a/src/data/inspector2/2020-06-08/api-2.json.php +++ b/src/data/inspector2/2020-06-08/api-2.json.php @@ -1,3 +1,3 @@ '2.0', 'metadata' => [ 'apiVersion' => '2020-06-08', 'endpointPrefix' => 'inspector2', 'jsonVersion' => '1.1', 'protocol' => 'rest-json', 'serviceAbbreviation' => 'Inspector2', 'serviceFullName' => 'Inspector2', 'serviceId' => 'Inspector2', 'signatureVersion' => 'v4', 'signingName' => 'inspector2', 'uid' => 'inspector2-2020-06-08', ], 'operations' => [ 'AssociateMember' => [ 'name' => 'AssociateMember', 'http' => [ 'method' => 'POST', 'requestUri' => '/members/associate', 'responseCode' => 200, ], 'input' => [ 'shape' => 'AssociateMemberRequest', ], 'output' => [ 'shape' => 'AssociateMemberResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetAccountStatus' => [ 'name' => 'BatchGetAccountStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/status/batch/get', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetAccountStatusRequest', ], 'output' => [ 'shape' => 'BatchGetAccountStatusResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetCodeSnippet' => [ 'name' => 'BatchGetCodeSnippet', 'http' => [ 'method' => 'POST', 'requestUri' => '/codesnippet/batchget', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetCodeSnippetRequest', ], 'output' => [ 'shape' => 'BatchGetCodeSnippetResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetFindingDetails' => [ 'name' => 'BatchGetFindingDetails', 'http' => [ 'method' => 'POST', 'requestUri' => '/findings/details/batch/get', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetFindingDetailsRequest', ], 'output' => [ 'shape' => 'BatchGetFindingDetailsResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetFreeTrialInfo' => [ 'name' => 'BatchGetFreeTrialInfo', 'http' => [ 'method' => 'POST', 'requestUri' => '/freetrialinfo/batchget', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetFreeTrialInfoRequest', ], 'output' => [ 'shape' => 'BatchGetFreeTrialInfoResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetMemberEc2DeepInspectionStatus' => [ 'name' => 'BatchGetMemberEc2DeepInspectionStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/ec2deepinspectionstatus/member/batch/get', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetMemberEc2DeepInspectionStatusRequest', ], 'output' => [ 'shape' => 'BatchGetMemberEc2DeepInspectionStatusResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchUpdateMemberEc2DeepInspectionStatus' => [ 'name' => 'BatchUpdateMemberEc2DeepInspectionStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/ec2deepinspectionstatus/member/batch/update', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchUpdateMemberEc2DeepInspectionStatusRequest', ], 'output' => [ 'shape' => 'BatchUpdateMemberEc2DeepInspectionStatusResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'CancelFindingsReport' => [ 'name' => 'CancelFindingsReport', 'http' => [ 'method' => 'POST', 'requestUri' => '/reporting/cancel', 'responseCode' => 200, ], 'input' => [ 'shape' => 'CancelFindingsReportRequest', ], 'output' => [ 'shape' => 'CancelFindingsReportResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'CancelSbomExport' => [ 'name' => 'CancelSbomExport', 'http' => [ 'method' => 'POST', 'requestUri' => '/sbomexport/cancel', 'responseCode' => 200, ], 'input' => [ 'shape' => 'CancelSbomExportRequest', ], 'output' => [ 'shape' => 'CancelSbomExportResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServerException', ], ], 'idempotent' => true, ], 'CreateCisScanConfiguration' => [ 'name' => 'CreateCisScanConfiguration', 'http' => [ 'method' => 'POST', 'requestUri' => '/cis/scan-configuration/create', 'responseCode' => 200, ], 'input' => [ 'shape' => 'CreateCisScanConfigurationRequest', ], 'output' => [ 'shape' => 'CreateCisScanConfigurationResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'CreateFilter' => [ 'name' => 'CreateFilter', 'http' => [ 'method' => 'POST', 'requestUri' => '/filters/create', 'responseCode' => 200, ], 'input' => [ 'shape' => 'CreateFilterRequest', ], 'output' => [ 'shape' => 'CreateFilterResponse', ], 'errors' => [ [ 'shape' => 'ServiceQuotaExceededException', ], [ 'shape' => 'BadRequestException', ], [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'CreateFindingsReport' => [ 'name' => 'CreateFindingsReport', 'http' => [ 'method' => 'POST', 'requestUri' => '/reporting/create', 'responseCode' => 200, ], 'input' => [ 'shape' => 'CreateFindingsReportRequest', ], 'output' => [ 'shape' => 'CreateFindingsReportResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'CreateSbomExport' => [ 'name' => 'CreateSbomExport', 'http' => [ 'method' => 'POST', 'requestUri' => '/sbomexport/create', 'responseCode' => 200, ], 'input' => [ 'shape' => 'CreateSbomExportRequest', ], 'output' => [ 'shape' => 'CreateSbomExportResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServerException', ], ], 'idempotent' => true, ], 'DeleteCisScanConfiguration' => [ 'name' => 'DeleteCisScanConfiguration', 'http' => [ 'method' => 'POST', 'requestUri' => '/cis/scan-configuration/delete', 'responseCode' => 200, ], 'input' => [ 'shape' => 'DeleteCisScanConfigurationRequest', ], 'output' => [ 'shape' => 'DeleteCisScanConfigurationResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'DeleteFilter' => [ 'name' => 'DeleteFilter', 'http' => [ 'method' => 'POST', 'requestUri' => '/filters/delete', 'responseCode' => 200, ], 'input' => [ 'shape' => 'DeleteFilterRequest', ], 'output' => [ 'shape' => 'DeleteFilterResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'DescribeOrganizationConfiguration' => [ 'name' => 'DescribeOrganizationConfiguration', 'http' => [ 'method' => 'POST', 'requestUri' => '/organizationconfiguration/describe', 'responseCode' => 200, ], 'input' => [ 'shape' => 'DescribeOrganizationConfigurationRequest', ], 'output' => [ 'shape' => 'DescribeOrganizationConfigurationResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'Disable' => [ 'name' => 'Disable', 'http' => [ 'method' => 'POST', 'requestUri' => '/disable', 'responseCode' => 200, ], 'input' => [ 'shape' => 'DisableRequest', ], 'output' => [ 'shape' => 'DisableResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'DisableDelegatedAdminAccount' => [ 'name' => 'DisableDelegatedAdminAccount', 'http' => [ 'method' => 'POST', 'requestUri' => '/delegatedadminaccounts/disable', 'responseCode' => 200, ], 'input' => [ 'shape' => 'DisableDelegatedAdminAccountRequest', ], 'output' => [ 'shape' => 'DisableDelegatedAdminAccountResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'DisassociateMember' => [ 'name' => 'DisassociateMember', 'http' => [ 'method' => 'POST', 'requestUri' => '/members/disassociate', 'responseCode' => 200, ], 'input' => [ 'shape' => 'DisassociateMemberRequest', ], 'output' => [ 'shape' => 'DisassociateMemberResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'Enable' => [ 'name' => 'Enable', 'http' => [ 'method' => 'POST', 'requestUri' => 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'output' => [ 'shape' => 'ListCisScanConfigurationsResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ValidationException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'ListCisScanResultsAggregatedByChecks' => [ 'name' => 'ListCisScanResultsAggregatedByChecks', 'http' => [ 'method' => 'POST', 'requestUri' => '/cis/scan-result/check/list', 'responseCode' => 200, ], 'input' => [ 'shape' => 'ListCisScanResultsAggregatedByChecksRequest', ], 'output' => [ 'shape' => 'ListCisScanResultsAggregatedByChecksResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ValidationException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'ListCisScanResultsAggregatedByTargetResource' => [ 'name' => 'ListCisScanResultsAggregatedByTargetResource', 'http' => [ 'method' => 'POST', 'requestUri' => '/cis/scan-result/resource/list', 'responseCode' => 200, ], 'input' => [ 'shape' => 'ListCisScanResultsAggregatedByTargetResourceRequest', ], 'output' => [ 'shape' => 'ListCisScanResultsAggregatedByTargetResourceResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ValidationException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'ListCisScans' => [ 'name' => 'ListCisScans', 'http' => [ 'method' => 'POST', 'requestUri' => '/cis/scan/list', 'responseCode' => 200, ], 'input' => [ 'shape' => 'ListCisScansRequest', ], 'output' => [ 'shape' => 'ListCisScansResponse', ], 'errors' => [ [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ValidationException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'ListCoverage' => [ 'name' => 'ListCoverage', 'http' => [ 'method' => 'POST', 'requestUri' => '/coverage/list', 'responseCode' => 200, ], 'input' => [ 'shape' => 'ListCoverageRequest', ], 'output' => [ 'shape' => 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'shape' => 'ValidationException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], 'idempotent' => true, ], 'UntagResource' => [ 'name' => 'UntagResource', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/tags/{resourceArn}', 'responseCode' => 200, ], 'input' => [ 'shape' => 'UntagResourceRequest', ], 'output' => [ 'shape' => 'UntagResourceResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'UpdateCisScanConfiguration' => [ 'name' => 'UpdateCisScanConfiguration', 'http' => [ 'method' => 'POST', 'requestUri' => '/cis/scan-configuration/update', 'responseCode' => 200, ], 'input' => [ 'shape' => 'UpdateCisScanConfigurationRequest', ], 'output' => [ 'shape' => 'UpdateCisScanConfigurationResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'UpdateConfiguration' => [ 'name' => 'UpdateConfiguration', 'http' => [ 'method' => 'POST', 'requestUri' => '/configuration/update', 'responseCode' => 200, ], 'input' => [ 'shape' => 'UpdateConfigurationRequest', ], 'output' => [ 'shape' => 'UpdateConfigurationResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'UpdateEc2DeepInspectionConfiguration' => [ 'name' => 'UpdateEc2DeepInspectionConfiguration', 'http' => [ 'method' => 'POST', 'requestUri' => '/ec2deepinspectionconfiguration/update', 'responseCode' => 200, ], 'input' => [ 'shape' => 'UpdateEc2DeepInspectionConfigurationRequest', ], 'output' => [ 'shape' => 'UpdateEc2DeepInspectionConfigurationResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'UpdateEncryptionKey' => [ 'name' => 'UpdateEncryptionKey', 'http' => [ 'method' => 'PUT', 'requestUri' => '/encryptionkey/update', 'responseCode' => 200, ], 'input' => [ 'shape' => 'UpdateEncryptionKeyRequest', ], 'output' => [ 'shape' => 'UpdateEncryptionKeyResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'InternalServerException', ], ], 'idempotent' => true, ], 'UpdateFilter' => [ 'name' => 'UpdateFilter', 'http' => [ 'method' => 'POST', 'requestUri' => '/filters/update', 'responseCode' => 200, ], 'input' => [ 'shape' => 'UpdateFilterRequest', ], 'output' => [ 'shape' => 'UpdateFilterResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 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'structure', 'required' => [ 'accountId', ], 'members' => [ 'accountId' => [ 'shape' => 'AccountId', ], ], ], 'Double' => [ 'type' => 'double', 'box' => true, ], 'Ec2DeepInspectionStatus' => [ 'type' => 'string', 'enum' => [ 'ACTIVATED', 'DEACTIVATED', 'PENDING', 'FAILED', ], ], 'Ec2InstanceAggregation' => [ 'type' => 'structure', 'members' => [ 'amis' => [ 'shape' => 'StringFilterList', ], 'instanceIds' => [ 'shape' => 'StringFilterList', ], 'instanceTags' => [ 'shape' => 'MapFilterList', ], 'operatingSystems' => [ 'shape' => 'StringFilterList', ], 'sortBy' => [ 'shape' => 'Ec2InstanceSortBy', ], 'sortOrder' => [ 'shape' => 'SortOrder', ], ], ], 'Ec2InstanceAggregationResponse' => [ 'type' => 'structure', 'required' => [ 'instanceId', ], 'members' => [ 'accountId' => [ 'shape' => 'String', ], 'ami' => [ 'shape' => 'AmiId', ], 'instanceId' => [ 'shape' => 'NonEmptyString', ], 'instanceTags' => [ 'shape' => 'TagMap', ], 'networkFindings' => [ 'shape' => 'Long', ], 'operatingSystem' => [ 'shape' => 'String', ], 'severityCounts' => [ 'shape' => 'SeverityCounts', ], ], ], 'Ec2InstanceSortBy' => [ 'type' => 'string', 'enum' => [ 'NETWORK_FINDINGS', 'CRITICAL', 'HIGH', 'ALL', ], ], 'Ec2Metadata' => [ 'type' => 'structure', 'members' => [ 'amiId' => [ 'shape' => 'AmiId', ], 'platform' => [ 'shape' => 'Ec2Platform', ], 'tags' => [ 'shape' => 'TagMap', ], ], ], 'Ec2Platform' => [ 'type' => 'string', 'enum' => [ 'WINDOWS', 'LINUX', 'UNKNOWN', 'MACOS', ], ], 'EcrConfiguration' => [ 'type' => 'structure', 'required' => [ 'rescanDuration', ], 'members' => [ 'rescanDuration' => [ 'shape' => 'EcrRescanDuration', ], ], ], 'EcrConfigurationState' => [ 'type' => 'structure', 'members' => [ 'rescanDurationState' => [ 'shape' => 'EcrRescanDurationState', ], ], ], 'EcrContainerImageMetadata' => [ 'type' => 'structure', 'members' => [ 'tags' => [ 'shape' => 'TagList', ], ], ], 'EcrRepositoryMetadata' => [ 'type' => 'structure', 'members' => [ 'name' => [ 'shape' => 'String', ], 'scanFrequency' => [ 'shape' => 'EcrScanFrequency', ], ], ], 'EcrRescanDuration' => [ 'type' => 'string', 'enum' => [ 'LIFETIME', 'DAYS_30', 'DAYS_180', ], ], 'EcrRescanDurationState' => [ 'type' => 'structure', 'members' => [ 'rescanDuration' => [ 'shape' => 'EcrRescanDuration', ], 'status' => [ 'shape' => 'EcrRescanDurationStatus', ], 'updatedAt' => [ 'shape' => 'DateTimeTimestamp', ], ], ], 'EcrRescanDurationStatus' => [ 'type' => 'string', 'enum' => [ 'SUCCESS', 'PENDING', 'FAILED', ], ], 'EcrScanFrequency' => [ 'type' => 'string', 'enum' => [ 'MANUAL', 'SCAN_ON_PUSH', 'CONTINUOUS_SCAN', ], ], 'EnableDelegatedAdminAccountRequest' => [ 'type' => 'structure', 'required' => [ 'delegatedAdminAccountId', ], 'members' => [ 'clientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'delegatedAdminAccountId' => [ 'shape' => 'AccountId', ], ], ], 'EnableDelegatedAdminAccountResponse' => [ 'type' => 'structure', 'required' => [ 'delegatedAdminAccountId', ], 'members' => [ 'delegatedAdminAccountId' => [ 'shape' => 'AccountId', ], ], ], 'EnableRequest' => [ 'type' => 'structure', 'required' => [ 'resourceTypes', ], 'members' => [ 'accountIds' => [ 'shape' => 'AccountIdSet', ], 'clientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'resourceTypes' => [ 'shape' => 'EnableResourceTypeList', ], ], ], 'EnableResourceTypeList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ResourceScanType', ], 'max' => 3, 'min' => 1, ], 'EnableResponse' => [ 'type' => 'structure', 'required' => [ 'accounts', ], 'members' => [ 'accounts' => [ 'shape' => 'AccountList', ], 'failedAccounts' => [ 'shape' => 'FailedAccountList', ], ], ], 'Epss' => [ 'type' => 'structure', 'members' => [ 'score' => [ 'shape' => 'EpssScore', ], ], ], 'EpssDetails' => [ 'type' => 'structure', 'members' => [ 'score' => [ 'shape' => 'EpssScoreValue', ], ], ], 'EpssScore' => [ 'type' => 'double', ], 'EpssScoreValue' => [ 'type' => 'double', 'max' => 1.0, 'min' => 0.0, ], 'ErrorCode' => [ 'type' => 'string', 'enum' => [ 'ALREADY_ENABLED', 'ENABLE_IN_PROGRESS', 'DISABLE_IN_PROGRESS', 'SUSPEND_IN_PROGRESS', 'RESOURCE_NOT_FOUND', 'ACCESS_DENIED', 'INTERNAL_ERROR', 'SSM_UNAVAILABLE', 'SSM_THROTTLED', 'EVENTBRIDGE_UNAVAILABLE', 'EVENTBRIDGE_THROTTLED', 'RESOURCE_SCAN_NOT_DISABLED', 'DISASSOCIATE_ALL_MEMBERS', 'ACCOUNT_IS_ISOLATED', ], ], 'ErrorMessage' => [ 'type' => 'string', ], 'Evidence' => [ 'type' => 'structure', 'members' => [ 'evidenceDetail' => [ 'shape' => 'EvidenceDetail', ], 'evidenceRule' => [ 'shape' => 'EvidenceRule', ], 'severity' => [ 'shape' => 'EvidenceSeverity', ], ], ], 'EvidenceDetail' => [ 'type' => 'string', 'min' => 0, ], 'EvidenceList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Evidence', ], ], 'EvidenceRule' => [ 'type' => 'string', 'min' => 0, ], 'EvidenceSeverity' => [ 'type' => 'string', 'min' => 0, ], 'ExecutionRoleArn' => [ 'type' => 'string', 'pattern' => '^arn:(aws[a-zA-Z-]*)?:iam::\\d{12}:role/?[a-zA-Z_0-9+=,.@\\-_/]+$', ], 'ExploitAvailable' => [ 'type' => 'string', 'enum' => [ 'YES', 'NO', ], ], 'ExploitObserved' => [ 'type' => 'structure', 'members' => [ 'firstSeen' => [ 'shape' => 'FirstSeen', ], 'lastSeen' => [ 'shape' => 'LastSeen', ], ], ], 'ExploitabilityDetails' => [ 'type' => 'structure', 'members' => [ 'lastKnownExploitAt' => [ 'shape' => 'DateTimeTimestamp', ], ], ], 'ExternalReportStatus' => [ 'type' => 'string', 'enum' => [ 'SUCCEEDED', 'IN_PROGRESS', 'CANCELLED', 'FAILED', ], ], 'FailedAccount' => [ 'type' => 'structure', 'required' => [ 'accountId', 'errorCode', 'errorMessage', ], 'members' => [ 'accountId' => [ 'shape' => 'AccountId', ], 'errorCode' => [ 'shape' => 'ErrorCode', ], 'errorMessage' => [ 'shape' => 'NonEmptyString', ], 'resourceStatus' => [ 'shape' => 'ResourceStatus', ], 'status' => [ 'shape' => 'Status', ], ], ], 'FailedAccountList' => [ 'type' => 'list', 'member' => [ 'shape' => 'FailedAccount', ], 'max' => 100, 'min' => 0, ], 'FailedMemberAccountEc2DeepInspectionStatusState' => [ 'type' => 'structure', 'required' => [ 'accountId', ], 'members' => [ 'accountId' => [ 'shape' => 'AccountId', ], 'ec2ScanStatus' => [ 'shape' => 'Status', ], 'errorMessage' => [ 'shape' => 'NonEmptyString', ], ], ], 'FailedMemberAccountEc2DeepInspectionStatusStateList' => [ 'type' => 'list', 'member' => [ 'shape' => 'FailedMemberAccountEc2DeepInspectionStatusState', ], 'max' => 100, 'min' => 0, ], 'FilePath' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'Filter' => [ 'type' => 'structure', 'required' => [ 'action', 'arn', 'createdAt', 'criteria', 'name', 'ownerId', 'updatedAt', ], 'members' => [ 'action' => [ 'shape' => 'FilterAction', ], 'arn' => [ 'shape' => 'FilterArn', ], 'createdAt' => [ 'shape' => 'DateTimeTimestamp', ], 'criteria' => [ 'shape' => 'FilterCriteria', ], 'description' => [ 'shape' => 'FilterDescription', ], 'name' => [ 'shape' => 'FilterName', ], 'ownerId' => [ 'shape' => 'OwnerId', ], 'reason' => [ 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=> [ 'steps' => [ 'shape' => 'StepList', ], ], ], 'NetworkProtocol' => [ 'type' => 'string', 'enum' => [ 'TCP', 'UDP', ], ], 'NetworkReachabilityDetails' => [ 'type' => 'structure', 'required' => [ 'networkPath', 'openPortRange', 'protocol', ], 'members' => [ 'networkPath' => [ 'shape' => 'NetworkPath', ], 'openPortRange' => [ 'shape' => 'PortRange', ], 'protocol' => [ 'shape' => 'NetworkProtocol', ], ], ], 'NextToken' => [ 'type' => 'string', 'max' => 1000000, 'min' => 0, ], 'NonEmptyString' => [ 'type' => 'string', 'min' => 1, ], 'NonEmptyStringList' => [ 'type' => 'list', 'member' => [ 'shape' => 'NonEmptyString', ], ], 'NumberFilter' => [ 'type' => 'structure', 'members' => [ 'lowerInclusive' => [ 'shape' => 'Double', ], 'upperInclusive' => [ 'shape' => 'Double', ], ], ], 'NumberFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'NumberFilter', ], 'max' => 10, 'min' => 1, ], 'OneAccountIdFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'CisStringFilter', ], 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'max' => 10, 'min' => 1, ], 'Product' => [ 'type' => 'string', 'max' => 32, 'min' => 0, ], 'Reason' => [ 'type' => 'string', 'max' => 1024, 'min' => 0, ], 'Recommendation' => [ 'type' => 'structure', 'members' => [ 'Url' => [ 'shape' => 'NonEmptyString', ], 'text' => [ 'shape' => 'NonEmptyString', ], ], ], 'ReferenceUrls' => [ 'type' => 'list', 'member' => [ 'shape' => 'NonEmptyString', ], 'max' => 10, 'min' => 1, ], 'RelatedVulnerabilities' => [ 'type' => 'list', 'member' => [ 'shape' => 'RelatedVulnerability', ], 'max' => 100, 'min' => 0, ], 'RelatedVulnerability' => [ 'type' => 'string', 'min' => 0, ], 'RelationshipStatus' => [ 'type' => 'string', 'enum' => [ 'CREATED', 'INVITED', 'DISABLED', 'ENABLED', 'REMOVED', 'RESIGNED', 'DELETED', 'EMAIL_VERIFICATION_IN_PROGRESS', 'EMAIL_VERIFICATION_FAILED', 'REGION_DISABLED', 'ACCOUNT_SUSPENDED', 'CANNOT_CREATE_DETECTOR_IN_ORG_MASTER', ], ], 'Remediation' => [ 'type' => 'structure', 'members' => [ 'recommendation' => [ 'shape' => 'Recommendation', ], ], ], 'ReportFormat' => [ 'type' => 'string', 'enum' => [ 'CSV', 'JSON', ], ], 'ReportId' => [ 'type' => 'string', 'pattern' => '\\b[a-f0-9]{8}\\b-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-\\b[a-f0-9]{12}\\b', ], 'ReportTargetAccounts' => [ 'type' => 'list', 'member' => [ 'shape' => 'AccountId', ], 'max' => 1, 'min' => 0, ], 'ReportingErrorCode' => [ 'type' => 'string', 'enum' => [ 'INTERNAL_ERROR', 'INVALID_PERMISSIONS', 'NO_FINDINGS_FOUND', 'BUCKET_NOT_FOUND', 'INCOMPATIBLE_BUCKET_REGION', 'MALFORMED_KMS_KEY', ], ], 'RepositoryAggregation' => [ 'type' => 'structure', 'members' => [ 'repositories' => [ 'shape' => 'StringFilterList', ], 'sortBy' => [ 'shape' => 'RepositorySortBy', ], 'sortOrder' => [ 'shape' => 'SortOrder', ], ], ], 'RepositoryAggregationResponse' => [ 'type' => 'structure', 'required' => [ 'repository', ], 'members' => [ 'accountId' => [ 'shape' => 'AccountId', ], 'affectedImages' => [ 'shape' => 'Long', ], 'repository' => [ 'shape' => 'NonEmptyString', ], 'severityCounts' => [ 'shape' => 'SeverityCounts', ], ], ], 'RepositorySortBy' => [ 'type' => 'string', 'enum' => [ 'CRITICAL', 'HIGH', 'ALL', 'AFFECTED_IMAGES', ], ], 'ResetEncryptionKeyRequest' => [ 'type' => 'structure', 'required' => [ 'resourceType', 'scanType', ], 'members' => [ 'resourceType' => [ 'shape' => 'ResourceType', ], 'scanType' => [ 'shape' => 'ScanType', ], ], ], 'ResetEncryptionKeyResponse' => [ 'type' => 'structure', 'members' => [], ], 'Resource' => [ 'type' => 'structure', 'required' => [ 'id', 'type', ], 'members' => [ 'details' => [ 'shape' => 'ResourceDetails', ], 'id' => [ 'shape' => 'NonEmptyString', ], 'partition' => [ 'shape' => 'NonEmptyString', ], 'region' => [ 'shape' => 'NonEmptyString', ], 'tags' => [ 'shape' => 'TagMap', ], 'type' => [ 'shape' => 'ResourceType', ], ], ], 'ResourceDetails' => [ 'type' => 'structure', 'members' => [ 'awsEc2Instance' => [ 'shape' => 'AwsEc2InstanceDetails', ], 'awsEcrContainerImage' => [ 'shape' => 'AwsEcrContainerImageDetails', ], 'awsLambdaFunction' => [ 'shape' => 'AwsLambdaFunctionDetails', ], ], ], 'ResourceFilterCriteria' => [ 'type' => 'structure', 'members' => [ 'accountId' => [ 'shape' => 'ResourceStringFilterList', ], 'ec2InstanceTags' => [ 'shape' => 'ResourceMapFilterList', ], 'ecrImageTags' => [ 'shape' => 'ResourceStringFilterList', ], 'ecrRepositoryName' => [ 'shape' => 'ResourceStringFilterList', ], 'lambdaFunctionName' => [ 'shape' => 'ResourceStringFilterList', ], 'lambdaFunctionTags' => [ 'shape' => 'ResourceMapFilterList', ], 'resourceId' => [ 'shape' => 'ResourceStringFilterList', ], 'resourceType' => [ 'shape' => 'ResourceStringFilterList', ], ], ], 'ResourceId' => [ 'type' => 'string', 'max' => 341, 'min' => 10, 'pattern' => 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'ResourceNotFoundException' => [ 'type' => 'structure', 'required' => [ 'message', ], 'members' => [ 'message' => [ 'shape' => 'String', ], ], 'error' => [ 'httpStatusCode' => 404, 'senderFault' => true, ], 'exception' => true, ], 'ResourceScanMetadata' => [ 'type' => 'structure', 'members' => [ 'ec2' => [ 'shape' => 'Ec2Metadata', ], 'ecrImage' => [ 'shape' => 'EcrContainerImageMetadata', ], 'ecrRepository' => [ 'shape' => 'EcrRepositoryMetadata', ], 'lambdaFunction' => [ 'shape' => 'LambdaFunctionMetadata', ], ], ], 'ResourceScanType' => [ 'type' => 'string', 'enum' => [ 'EC2', 'ECR', 'LAMBDA', 'LAMBDA_CODE', ], ], 'ResourceState' => [ 'type' => 'structure', 'required' => [ 'ec2', 'ecr', ], 'members' => [ 'ec2' => [ 'shape' => 'State', ], 'ecr' => [ 'shape' => 'State', ], 'lambda' => [ 'shape' => 'State', ], 'lambdaCode' => [ 'shape' => 'State', ], ], ], 'ResourceStatus' => [ 'type' => 'structure', 'required' => [ 'ec2', 'ecr', ], 'members' => [ 'ec2' => [ 'shape' => 'Status', ], 'ecr' => [ 'shape' => 'Status', ], 'lambda' => [ 'shape' => 'Status', ], 'lambdaCode' => [ 'shape' => 'Status', ], ], ], 'ResourceStringComparison' => [ 'type' => 'string', 'enum' => [ 'EQUALS', 'NOT_EQUALS', ], ], 'ResourceStringFilter' => [ 'type' => 'structure', 'required' => [ 'comparison', 'value', ], 'members' => [ 'comparison' => [ 'shape' => 'ResourceStringComparison', ], 'value' => [ 'shape' => 'ResourceStringInput', ], ], ], 'ResourceStringFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ResourceStringFilter', ], 'max' => 10, 'min' => 1, ], 'ResourceStringInput' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'ResourceTagFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TagFilter', ], 'max' => 10, 'min' => 1, ], 'ResourceType' => [ 'type' => 'string', 'enum' => [ 'AWS_EC2_INSTANCE', 'AWS_ECR_CONTAINER_IMAGE', 'AWS_ECR_REPOSITORY', 'AWS_LAMBDA_FUNCTION', ], ], 'RiskScore' => [ 'type' => 'integer', 'box' => true, ], 'RuleId' => [ 'type' => 'string', 'max' => 500, 'min' => 1, ], 'Runtime' => [ 'type' => 'string', 'enum' => [ 'NODEJS', 'NODEJS_12_X', 'NODEJS_14_X', 'NODEJS_16_X', 'JAVA_8', 'JAVA_8_AL2', 'JAVA_11', 'PYTHON_3_7', 'PYTHON_3_8', 'PYTHON_3_9', 'UNSUPPORTED', 'NODEJS_18_X', 'GO_1_X', 'JAVA_17', 'PYTHON_3_10', ], ], 'SbomReportFormat' => [ 'type' => 'string', 'enum' => [ 'CYCLONEDX_1_4', 'SPDX_2_3', ], ], 'ScanStatus' => [ 'type' => 'structure', 'required' => [ 'reason', 'statusCode', ], 'members' => [ 'reason' => [ 'shape' => 'ScanStatusReason', ], 'statusCode' => [ 'shape' => 'ScanStatusCode', ], ], ], 'ScanStatusCode' => [ 'type' => 'string', 'enum' => [ 'ACTIVE', 'INACTIVE', ], ], 'ScanStatusReason' => [ 'type' => 'string', 'enum' => [ 'PENDING_INITIAL_SCAN', 'ACCESS_DENIED', 'INTERNAL_ERROR', 'UNMANAGED_EC2_INSTANCE', 'UNSUPPORTED_OS', 'SCAN_ELIGIBILITY_EXPIRED', 'RESOURCE_TERMINATED', 'SUCCESSFUL', 'NO_RESOURCES_FOUND', 'IMAGE_SIZE_EXCEEDED', 'SCAN_FREQUENCY_MANUAL', 'SCAN_FREQUENCY_SCAN_ON_PUSH', 'EC2_INSTANCE_STOPPED', 'PENDING_DISABLE', 'NO_INVENTORY', 'STALE_INVENTORY', 'EXCLUDED_BY_TAG', 'UNSUPPORTED_RUNTIME', 'UNSUPPORTED_MEDIA_TYPE', 'UNSUPPORTED_CONFIG_FILE', 'DEEP_INSPECTION_PACKAGE_COLLECTION_LIMIT_EXCEEDED', 'DEEP_INSPECTION_DAILY_SSM_INVENTORY_LIMIT_EXCEEDED', 'DEEP_INSPECTION_COLLECTION_TIME_LIMIT_EXCEEDED', 'DEEP_INSPECTION_NO_INVENTORY', ], ], 'ScanType' => [ 'type' => 'string', 'enum' => [ 'NETWORK', 'PACKAGE', 'CODE', ], ], 'Schedule' => [ 'type' => 'structure', 'members' => [ 'daily' => [ 'shape' => 'DailySchedule', ], 'monthly' => [ 'shape' => 'MonthlySchedule', ], 'oneTime' => [ 'shape' => 'OneTimeSchedule', ], 'weekly' => [ 'shape' => 'WeeklySchedule', ], ], 'union' => true, ], 'SearchVulnerabilitiesFilterCriteria' => [ 'type' => 'structure', 'required' => [ 'vulnerabilityIds', ], 'members' => [ 'vulnerabilityIds' => [ 'shape' => 'VulnIdList', ], ], ], 'SearchVulnerabilitiesRequest' => [ 'type' => 'structure', 'required' => [ 'filterCriteria', ], 'members' => [ 'filterCriteria' => [ 'shape' => 'SearchVulnerabilitiesFilterCriteria', ], 'nextToken' => [ 'shape' => 'NextToken', ], ], ], 'SearchVulnerabilitiesResponse' => [ 'type' => 'structure', 'required' => [ 'vulnerabilities', ], 'members' => [ 'nextToken' => [ 'shape' => 'NextToken', ], 'vulnerabilities' => [ 'shape' => 'Vulnerabilities', ], ], ], 'SecurityGroupId' => [ 'type' => 'string', 'pattern' => '^sg-([a-z0-9]{8}|[a-z0-9]{17}|\\*)$', ], 'SecurityGroupIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityGroupId', ], 'max' => 5, 'min' => 0, ], 'SendCisSessionHealthRequest' => [ 'type' => 'structure', 'required' => [ 'scanJobId', 'sessionToken', ], 'members' => [ 'scanJobId' => [ 'shape' => 'UUID', ], 'sessionToken' => [ 'shape' => 'UUID', ], ], ], 'SendCisSessionHealthResponse' => [ 'type' => 'structure', 'members' => [], ], 'SendCisSessionTelemetryRequest' => [ 'type' => 'structure', 'required' => [ 'messages', 'scanJobId', 'sessionToken', ], 'members' => [ 'messages' => [ 'shape' => 'CisSessionMessages', ], 'scanJobId' => [ 'shape' => 'UUID', ], 'sessionToken' => [ 'shape' => 'UUID', ], ], ], 'SendCisSessionTelemetryResponse' => [ 'type' => 'structure', 'members' => [], ], 'Service' => [ 'type' => 'string', 'enum' => [ 'EC2', 'ECR', 'LAMBDA', ], ], 'ServiceQuotaExceededException' => [ 'type' => 'structure', 'required' => [ 'message', 'resourceId', ], 'members' => [ 'message' => [ 'shape' => 'String', ], 'resourceId' => [ 'shape' => 'String', ], ], 'error' => [ 'httpStatusCode' => 402, 'senderFault' => true, ], 'exception' => true, ], 'Severity' => [ 'type' => 'string', 'enum' => [ 'INFORMATIONAL', 'LOW', 'MEDIUM', 'HIGH', 'CRITICAL', 'UNTRIAGED', ], ], 'SeverityCounts' => [ 'type' => 'structure', 'members' => [ 'all' => [ 'shape' => 'Long', ], 'critical' => [ 'shape' => 'Long', ], 'high' => [ 'shape' => 'Long', ], 'medium' => [ 'shape' => 'Long', ], ], ], 'SortCriteria' => [ 'type' => 'structure', 'required' => [ 'field', 'sortOrder', ], 'members' => [ 'field' => [ 'shape' => 'SortField', ], 'sortOrder' => [ 'shape' => 'SortOrder', ], ], ], 'SortField' => [ 'type' => 'string', 'enum' => [ 'AWS_ACCOUNT_ID', 'FINDING_TYPE', 'SEVERITY', 'FIRST_OBSERVED_AT', 'LAST_OBSERVED_AT', 'FINDING_STATUS', 'RESOURCE_TYPE', 'ECR_IMAGE_PUSHED_AT', 'ECR_IMAGE_REPOSITORY_NAME', 'ECR_IMAGE_REGISTRY', 'NETWORK_PROTOCOL', 'COMPONENT_TYPE', 'VULNERABILITY_ID', 'VULNERABILITY_SOURCE', 'INSPECTOR_SCORE', 'VENDOR_SEVERITY', 'EPSS_SCORE', ], ], 'SortOrder' => [ 'type' => 'string', 'enum' => [ 'ASC', 'DESC', ], ], 'SourceLayerHash' => [ 'type' => 'string', 'max' => 71, 'min' => 71, 'pattern' => '^sha256:[a-z0-9]{64}$', ], 'StartCisSessionMessage' => [ 'type' => 'structure', 'required' => [ 'sessionToken', ], 'members' => [ 'sessionToken' => [ 'shape' => 'UUID', ], ], ], 'StartCisSessionRequest' => [ 'type' => 'structure', 'required' => [ 'message', 'scanJobId', ], 'members' => [ 'message' => [ 'shape' => 'StartCisSessionMessage', ], 'scanJobId' => [ 'shape' => 'UUID', ], ], ], 'StartCisSessionResponse' => [ 'type' => 'structure', 'members' => [], ], 'State' => [ 'type' => 'structure', 'required' => [ 'errorCode', 'errorMessage', 'status', ], 'members' => [ 'errorCode' => [ 'shape' => 'ErrorCode', ], 'errorMessage' => [ 'shape' => 'NonEmptyString', ], 'status' => [ 'shape' => 'Status', ], ], ], 'Status' => [ 'type' => 'string', 'enum' => [ 'ENABLING', 'ENABLED', 'DISABLING', 'DISABLED', 'SUSPENDING', 'SUSPENDED', ], ], 'StatusCounts' => [ 'type' => 'structure', 'members' => [ 'failed' => [ 'shape' => 'Integer', ], 'passed' => [ 'shape' => 'Integer', ], 'skipped' => [ 'shape' => 'Integer', ], ], ], 'Step' => [ 'type' => 'structure', 'required' => [ 'componentId', 'componentType', ], 'members' => [ 'componentId' => [ 'shape' => 'Component', ], 'componentType' => [ 'shape' => 'ComponentType', ], ], ], 'StepList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Step', ], 'max' => 30, 'min' => 1, ], 'StopCisMessageProgress' => [ 'type' => 'structure', 'members' => [ 'errorChecks' => [ 'shape' => 'CheckCount', ], 'failedChecks' => [ 'shape' => 'CheckCount', ], 'informationalChecks' => [ 'shape' => 'CheckCount', ], 'notApplicableChecks' => [ 'shape' => 'CheckCount', ], 'notEvaluatedChecks' => [ 'shape' => 'CheckCount', ], 'successfulChecks' => [ 'shape' => 'CheckCount', ], 'totalChecks' => [ 'shape' => 'CheckCount', ], 'unknownChecks' => [ 'shape' => 'CheckCount', ], ], ], 'StopCisSessionMessage' => [ 'type' => 'structure', 'required' => [ 'progress', 'status', ], 'members' => [ 'benchmarkProfile' => [ 'shape' => 'BenchmarkProfile', ], 'benchmarkVersion' => [ 'shape' => 'BenchmarkVersion', ], 'computePlatform' => [ 'shape' => 'ComputePlatform', ], 'progress' => [ 'shape' => 'StopCisMessageProgress', ], 'reason' => [ 'shape' => 'Reason', ], 'status' => [ 'shape' => 'StopCisSessionStatus', ], ], ], 'StopCisSessionRequest' => [ 'type' => 'structure', 'required' => [ 'message', 'scanJobId', 'sessionToken', ], 'members' => [ 'message' => [ 'shape' => 'StopCisSessionMessage', ], 'scanJobId' => [ 'shape' => 'UUID', ], 'sessionToken' => [ 'shape' => 'UUID', ], ], ], 'StopCisSessionResponse' => [ 'type' => 'structure', 'members' => [], ], 'StopCisSessionStatus' => [ 'type' => 'string', 'enum' => [ 'SUCCESS', 'FAILED', 'INTERRUPTED', 'UNSUPPORTED_OS', ], ], 'String' => [ 'type' => 'string', ], 'StringComparison' => [ 'type' => 'string', 'enum' => [ 'EQUALS', 'PREFIX', 'NOT_EQUALS', ], ], 'StringFilter' => [ 'type' => 'structure', 'required' => [ 'comparison', 'value', ], 'members' => [ 'comparison' => [ 'shape' => 'StringComparison', ], 'value' => [ 'shape' => 'StringInput', ], ], ], 'StringFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'StringFilter', ], 'max' => 10, 'min' => 1, ], 'StringInput' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'StringList' => [ 'type' => 'list', 'member' => [ 'shape' => 'NonEmptyString', ], ], 'SubnetId' => [ 'type' => 'string', 'pattern' => '^subnet-([a-z0-9]{8}|[a-z0-9]{17}|\\*)$', ], 'SubnetIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SubnetId', ], 'max' => 16, 'min' => 0, ], 'SuggestedFix' => [ 'type' => 'structure', 'members' => [ 'code' => [ 'shape' => 'SuggestedFixCodeString', ], 'description' => [ 'shape' => 'SuggestedFixDescriptionString', ], ], ], 'SuggestedFixCodeString' => [ 'type' => 'string', 'max' => 2500, 'min' => 1, ], 'SuggestedFixDescriptionString' => [ 'type' => 'string', 'max' => 1000, 'min' => 1, ], 'SuggestedFixes' => [ 'type' => 'list', 'member' => [ 'shape' => 'SuggestedFix', ], 'max' => 5, 'min' => 1, ], 'TagComparison' => [ 'type' => 'string', 'enum' => [ 'EQUALS', ], ], 'TagFilter' => [ 'type' => 'structure', 'required' => [ 'comparison', 'key', 'value', ], 'members' => [ 'comparison' => [ 'shape' => 'TagComparison', ], 'key' => [ 'shape' => 'NonEmptyString', ], 'value' => [ 'shape' => 'NonEmptyString', ], ], ], 'TagKey' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '^(?!aws:)[a-zA-Z+-=._:/]+$', ], 'TagKeyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TagKey', ], 'max' => 50, 'min' => 0, ], 'TagList' => [ 'type' => 'list', 'member' => [ 'shape' => 'String', ], ], 'TagMap' => [ 'type' => 'map', 'key' => [ 'shape' => 'MapKey', ], 'value' => [ 'shape' => 'MapValue', ], ], 'TagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'resourceArn', 'tags', ], 'members' => [ 'resourceArn' => [ 'shape' => 'Arn', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'tags' => [ 'shape' => 'TagMap', ], ], ], 'TagResourceResponse' => [ 'type' => 'structure', 'members' => [], ], 'TagValueList' => [ 'type' => 'list', 'member' => [ 'shape' => 'String', ], 'max' => 5, 'min' => 1, ], 'Target' => [ 'type' => 'string', 'max' => 50, 'min' => 0, ], 'TargetAccount' => [ 'type' => 'string', 'pattern' => '^\\d{12}|ALL_ACCOUNTS|SELF$', ], 'TargetAccountList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TargetAccount', ], 'max' => 10000, 'min' => 1, ], 'TargetResourceTags' => [ 'type' => 'map', 'key' => [ 'shape' => 'NonEmptyString', ], 'value' => [ 'shape' => 'TagValueList', ], 'max' => 5, 'min' => 1, ], 'TargetStatusFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'CisTargetStatusFilter', ], 'max' => 10, 'min' => 1, ], 'TargetStatusReasonFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'CisTargetStatusReasonFilter', ], 'max' => 10, 'min' => 1, ], 'Targets' => [ 'type' => 'list', 'member' => [ 'shape' => 'Target', ], 'min' => 0, ], 'ThrottlingException' => [ 'type' => 'structure', 'required' => [ 'message', ], 'members' => [ 'message' => [ 'shape' => 'String', ], 'retryAfterSeconds' => [ 'shape' => 'Integer', 'location' => 'header', 'locationName' => 'Retry-After', ], ], 'error' => [ 'httpStatusCode' => 429, 'senderFault' => true, ], 'exception' => true, 'retryable' => [ 'throttling' => true, ], ], 'Time' => [ 'type' => 'structure', 'required' => [ 'timeOfDay', 'timezone', ], 'members' => [ 'timeOfDay' => [ 'shape' => 'TimeOfDay', ], 'timezone' => [ 'shape' => 'Timezone', ], ], ], 'TimeOfDay' => [ 'type' => 'string', 'pattern' => '^([0-1]?[0-9]|2[0-3]):[0-5][0-9]$', ], 'Timestamp' => [ 'type' => 'timestamp', ], 'Timezone' => [ 'type' => 'string', 'max' => 50, 'min' => 1, ], 'TitleAggregation' => [ 'type' => 'structure', 'members' => [ 'findingType' => [ 'shape' => 'AggregationFindingType', ], 'resourceType' => [ 'shape' => 'AggregationResourceType', ], 'sortBy' => [ 'shape' => 'TitleSortBy', ], 'sortOrder' => [ 'shape' => 'SortOrder', ], 'titles' => [ 'shape' => 'StringFilterList', ], 'vulnerabilityIds' => [ 'shape' => 'StringFilterList', ], ], ], 'TitleAggregationResponse' => [ 'type' => 'structure', 'required' => [ 'title', ], 'members' => [ 'accountId' => [ 'shape' => 'AccountId', ], 'severityCounts' => [ 'shape' => 'SeverityCounts', ], 'title' => [ 'shape' => 'NonEmptyString', ], 'vulnerabilityId' => [ 'shape' => 'String', ], ], ], 'TitleFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'CisStringFilter', ], 'max' => 10, 'min' => 1, ], 'TitleSortBy' => [ 'type' => 'string', 'enum' => [ 'CRITICAL', 'HIGH', 'ALL', ], ], 'Tool' => [ 'type' => 'string', 'min' => 0, ], 'Tools' => [ 'type' => 'list', 'member' => [ 'shape' => 'Tool', ], ], 'Ttp' => [ 'type' => 'string', 'max' => 30, 'min' => 0, ], 'Ttps' => [ 'type' => 'list', 'member' => [ 'shape' => 'Ttp', ], 'min' => 0, ], 'UUID' => [ 'type' => 'string', 'pattern' => '^[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}$', ], 'UntagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'resourceArn', 'tagKeys', ], 'members' => [ 'resourceArn' => [ 'shape' => 'Arn', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'tagKeys' => [ 'shape' => 'TagKeyList', 'location' => 'querystring', 'locationName' => 'tagKeys', ], ], ], 'UntagResourceResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateCisScanConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'scanConfigurationArn', ], 'members' => [ 'scanConfigurationArn' => [ 'shape' => 'CisScanConfigurationArn', ], 'scanName' => [ 'shape' => 'CisScanName', ], 'schedule' => [ 'shape' => 'Schedule', ], 'securityLevel' => [ 'shape' => 'CisSecurityLevel', ], 'targets' => [ 'shape' => 'UpdateCisTargets', ], ], ], 'UpdateCisScanConfigurationResponse' => [ 'type' => 'structure', 'required' => [ 'scanConfigurationArn', ], 'members' => [ 'scanConfigurationArn' => [ 'shape' => 'CisScanConfigurationArn', ], ], ], 'UpdateCisTargets' => [ 'type' => 'structure', 'members' => [ 'accountIds' => [ 'shape' => 'TargetAccountList', ], 'targetResourceTags' => [ 'shape' => 'TargetResourceTags', ], ], ], 'UpdateConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'ecrConfiguration', ], 'members' => [ 'ecrConfiguration' => [ 'shape' => 'EcrConfiguration', ], ], ], 'UpdateConfigurationResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateEc2DeepInspectionConfigurationRequest' => [ 'type' => 'structure', 'members' => [ 'activateDeepInspection' => [ 'shape' => 'Boolean', ], 'packagePaths' => [ 'shape' => 'PathList', ], ], ], 'UpdateEc2DeepInspectionConfigurationResponse' => [ 'type' => 'structure', 'members' => [ 'errorMessage' => [ 'shape' => 'NonEmptyString', ], 'orgPackagePaths' => [ 'shape' => 'PathList', ], 'packagePaths' => [ 'shape' => 'PathList', ], 'status' => [ 'shape' => 'Ec2DeepInspectionStatus', ], ], ], 'UpdateEncryptionKeyRequest' => [ 'type' => 'structure', 'required' => [ 'kmsKeyId', 'resourceType', 'scanType', ], 'members' => [ 'kmsKeyId' => [ 'shape' => 'KmsKeyArn', ], 'resourceType' => [ 'shape' => 'ResourceType', ], 'scanType' => [ 'shape' => 'ScanType', ], ], ], 'UpdateEncryptionKeyResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateFilterRequest' => [ 'type' => 'structure', 'required' => [ 'filterArn', ], 'members' => [ 'action' => [ 'shape' => 'FilterAction', ], 'description' => [ 'shape' => 'FilterDescription', ], 'filterArn' => [ 'shape' => 'FilterArn', ], 'filterCriteria' => [ 'shape' => 'FilterCriteria', ], 'name' => [ 'shape' => 'FilterName', ], 'reason' => [ 'shape' => 'FilterReason', ], ], ], 'UpdateFilterResponse' => [ 'type' => 'structure', 'required' => [ 'arn', ], 'members' => [ 'arn' => [ 'shape' => 'FilterArn', ], ], ], 'UpdateOrgEc2DeepInspectionConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'orgPackagePaths', ], 'members' => [ 'orgPackagePaths' => [ 'shape' => 'PathList', ], ], ], 'UpdateOrgEc2DeepInspectionConfigurationResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateOrganizationConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'autoEnable', ], 'members' => [ 'autoEnable' => [ 'shape' => 'AutoEnable', ], ], ], 'UpdateOrganizationConfigurationResponse' => [ 'type' => 'structure', 'required' => [ 'autoEnable', ], 'members' => [ 'autoEnable' => [ 'shape' => 'AutoEnable', ], ], ], 'Usage' => [ 'type' => 'structure', 'members' => [ 'currency' => [ 'shape' => 'Currency', ], 'estimatedMonthlyCost' => [ 'shape' => 'MonthlyCostEstimate', ], 'total' => [ 'shape' => 'UsageValue', ], 'type' => [ 'shape' => 'UsageType', ], ], ], 'UsageAccountId' => [ 'type' => 'string', 'pattern' => '[0-9]{12}', ], 'UsageAccountIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UsageAccountId', ], 'max' => 7000, 'min' => 1, ], 'UsageList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Usage', ], ], 'UsageTotal' => [ 'type' => 'structure', 'members' => [ 'accountId' => [ 'shape' => 'MeteringAccountId', ], 'usage' => [ 'shape' => 'UsageList', ], ], ], 'UsageTotalList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UsageTotal', ], ], 'UsageType' => [ 'type' => 'string', 'enum' => [ 'EC2_INSTANCE_HOURS', 'ECR_INITIAL_SCAN', 'ECR_RESCAN', 'LAMBDA_FUNCTION_HOURS', 'LAMBDA_FUNCTION_CODE_HOURS', ], ], 'UsageValue' => [ 'type' => 'double', 'min' => 0, ], 'ValidationException' => [ 'type' => 'structure', 'required' => [ 'message', 'reason', ], 'members' => [ 'fields' => [ 'shape' => 'ValidationExceptionFields', ], 'message' => [ 'shape' => 'String', ], 'reason' => [ 'shape' => 'ValidationExceptionReason', ], ], 'error' => [ 'httpStatusCode' => 400, 'senderFault' => true, ], 'exception' => true, ], 'ValidationExceptionField' => [ 'type' => 'structure', 'required' => [ 'message', 'name', ], 'members' => [ 'message' => [ 'shape' => 'String', ], 'name' => [ 'shape' => 'String', ], ], ], 'ValidationExceptionFields' => [ 'type' => 'list', 'member' => [ 'shape' => 'ValidationExceptionField', ], ], 'ValidationExceptionReason' => [ 'type' => 'string', 'enum' => [ 'CANNOT_PARSE', 'FIELD_VALIDATION_FAILED', 'OTHER', ], ], 'Vendor' => [ 'type' => 'string', 'max' => 16, 'min' => 0, ], 'VendorCreatedAt' => [ 'type' => 'timestamp', ], 'VendorSeverity' => [ 'type' => 'string', 'max' => 64, 'min' => 1, ], 'VendorUpdatedAt' => [ 'type' => 'timestamp', ], 'Version' => [ 'type' => 'string', 'pattern' => '^\\$LATEST|[0-9]+$', ], 'VpcId' => [ 'type' => 'string', 'pattern' => '^vpc-([a-z0-9]{8}|[a-z0-9]{17}|\\*)$', ], 'VulnId' => [ 'type' => 'string', 'pattern' => '^CVE-[12][0-9]{3}-[0-9]{1,10}$', ], 'VulnIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VulnId', ], 'max' => 1, 'min' => 1, ], 'Vulnerabilities' => [ 'type' => 'list', 'member' => [ 'shape' => 'Vulnerability', ], 'max' => 1, 'min' => 0, ], 'Vulnerability' => [ 'type' => 'structure', 'required' => [ 'id', ], 'members' => [ 'atigData' => [ 'shape' => 'AtigData', ], 'cisaData' => [ 'shape' => 'CisaData', ], 'cvss2' => [ 'shape' => 'Cvss2', ], 'cvss3' => [ 'shape' => 'Cvss3', ], 'cwes' => [ 'shape' => 'Cwes', ], 'description' => [ 'shape' => 'VulnerabilityDescription', ], 'detectionPlatforms' => [ 'shape' => 'DetectionPlatforms', ], 'epss' => [ 'shape' => 'Epss', ], 'exploitObserved' => [ 'shape' => 'ExploitObserved', ], 'id' => [ 'shape' => 'NonEmptyString', ], 'referenceUrls' => [ 'shape' => 'VulnerabilityReferenceUrls', ], 'relatedVulnerabilities' => [ 'shape' => 'RelatedVulnerabilities', ], 'source' => [ 'shape' => 'VulnerabilitySource', ], 'sourceUrl' => [ 'shape' => 'VulnerabilitySourceUrl', ], 'vendorCreatedAt' => [ 'shape' => 'VendorCreatedAt', ], 'vendorSeverity' => [ 'shape' => 'VendorSeverity', ], 'vendorUpdatedAt' => [ 'shape' => 'VendorUpdatedAt', ], ], ], 'VulnerabilityDescription' => [ 'type' => 'string', ], 'VulnerabilityId' => [ 'type' => 'string', 'max' => 128, 'min' => 1, ], 'VulnerabilityIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VulnerabilityId', ], ], 'VulnerabilityReferenceUrl' => [ 'type' => 'string', 'min' => 0, ], 'VulnerabilityReferenceUrls' => [ 'type' => 'list', 'member' => [ 'shape' => 'VulnerabilityReferenceUrl', ], 'max' => 100, 'min' => 0, ], 'VulnerabilitySource' => [ 'type' => 'string', 'enum' => [ 'NVD', ], ], 'VulnerabilitySourceUrl' => [ 'type' => 'string', 'min' => 0, ], 'VulnerablePackage' => [ 'type' => 'structure', 'required' => [ 'name', 'version', ], 'members' => [ 'arch' => [ 'shape' => 'PackageArchitecture', ], 'epoch' => [ 'shape' => 'PackageEpoch', ], 'filePath' => [ 'shape' => 'FilePath', ], 'fixedInVersion' => [ 'shape' => 'PackageVersion', ], 'name' => [ 'shape' => 'PackageName', ], 'packageManager' => [ 'shape' => 'PackageManager', ], 'release' => [ 'shape' => 'PackageRelease', ], 'remediation' => [ 'shape' => 'VulnerablePackageRemediation', ], 'sourceLambdaLayerArn' => [ 'shape' => 'LambdaLayerArn', ], 'sourceLayerHash' => [ 'shape' => 'SourceLayerHash', ], 'version' => [ 'shape' => 'PackageVersion', ], ], ], 'VulnerablePackageList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VulnerablePackage', ], ], 'VulnerablePackageRemediation' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'WeeklySchedule' => [ 'type' => 'structure', 'required' => [ 'days', 'startTime', ], 'members' => [ 'days' => [ 'shape' => 'DaysList', ], 'startTime' => [ 'shape' => 'Time', ], ], ], ],]; +return [ 'version' => '2.0', 'metadata' => [ 'apiVersion' => '2020-06-08', 'endpointPrefix' => 'inspector2', 'jsonVersion' => '1.1', 'protocol' => 'rest-json', 'serviceAbbreviation' => 'Inspector2', 'serviceFullName' => 'Inspector2', 'serviceId' => 'Inspector2', 'signatureVersion' => 'v4', 'signingName' => 'inspector2', 'uid' => 'inspector2-2020-06-08', ], 'operations' => [ 'AssociateMember' => [ 'name' => 'AssociateMember', 'http' => [ 'method' => 'POST', 'requestUri' => '/members/associate', 'responseCode' => 200, ], 'input' => [ 'shape' => 'AssociateMemberRequest', ], 'output' => [ 'shape' => 'AssociateMemberResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetAccountStatus' => [ 'name' => 'BatchGetAccountStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/status/batch/get', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetAccountStatusRequest', ], 'output' => [ 'shape' => 'BatchGetAccountStatusResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ResourceNotFoundException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetCodeSnippet' => [ 'name' => 'BatchGetCodeSnippet', 'http' => [ 'method' => 'POST', 'requestUri' => '/codesnippet/batchget', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetCodeSnippetRequest', ], 'output' => [ 'shape' => 'BatchGetCodeSnippetResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetFindingDetails' => [ 'name' => 'BatchGetFindingDetails', 'http' => [ 'method' => 'POST', 'requestUri' => '/findings/details/batch/get', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetFindingDetailsRequest', ], 'output' => [ 'shape' => 'BatchGetFindingDetailsResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetFreeTrialInfo' => [ 'name' => 'BatchGetFreeTrialInfo', 'http' => [ 'method' => 'POST', 'requestUri' => '/freetrialinfo/batchget', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetFreeTrialInfoRequest', ], 'output' => [ 'shape' => 'BatchGetFreeTrialInfoResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchGetMemberEc2DeepInspectionStatus' => [ 'name' => 'BatchGetMemberEc2DeepInspectionStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/ec2deepinspectionstatus/member/batch/get', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchGetMemberEc2DeepInspectionStatusRequest', ], 'output' => [ 'shape' => 'BatchGetMemberEc2DeepInspectionStatusResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'BatchUpdateMemberEc2DeepInspectionStatus' => [ 'name' => 'BatchUpdateMemberEc2DeepInspectionStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/ec2deepinspectionstatus/member/batch/update', 'responseCode' => 200, ], 'input' => [ 'shape' => 'BatchUpdateMemberEc2DeepInspectionStatusRequest', ], 'output' => [ 'shape' => 'BatchUpdateMemberEc2DeepInspectionStatusResponse', ], 'errors' => [ [ 'shape' => 'ValidationException', ], [ 'shape' => 'AccessDeniedException', ], [ 'shape' => 'ThrottlingException', ], [ 'shape' => 'InternalServerException', ], ], ], 'CancelFindingsReport' => [ 'name' => 'CancelFindingsReport', 'http' => [ 'method' => 'POST', 'requestUri' => '/reporting/cancel', 'responseCode' => 200, ], 'input' => [ 'shape' => 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'enum' => [ 'AWS_EC2_INSTANCE', 'AWS_ECR_CONTAINER_IMAGE', 'AWS_ECR_REPOSITORY', 'AWS_LAMBDA_FUNCTION', ], ], 'RiskScore' => [ 'type' => 'integer', 'box' => true, ], 'RuleId' => [ 'type' => 'string', 'max' => 500, 'min' => 1, ], 'Runtime' => [ 'type' => 'string', 'enum' => [ 'NODEJS', 'NODEJS_12_X', 'NODEJS_14_X', 'NODEJS_16_X', 'JAVA_8', 'JAVA_8_AL2', 'JAVA_11', 'PYTHON_3_7', 'PYTHON_3_8', 'PYTHON_3_9', 'UNSUPPORTED', 'NODEJS_18_X', 'GO_1_X', 'JAVA_17', 'PYTHON_3_10', ], ], 'SbomReportFormat' => [ 'type' => 'string', 'enum' => [ 'CYCLONEDX_1_4', 'SPDX_2_3', ], ], 'ScanStatus' => [ 'type' => 'structure', 'required' => [ 'reason', 'statusCode', ], 'members' => [ 'reason' => [ 'shape' => 'ScanStatusReason', ], 'statusCode' => [ 'shape' => 'ScanStatusCode', ], ], ], 'ScanStatusCode' => [ 'type' => 'string', 'enum' => [ 'ACTIVE', 'INACTIVE', ], ], 'ScanStatusReason' => [ 'type' => 'string', 'enum' => [ 'PENDING_INITIAL_SCAN', 'ACCESS_DENIED', 'INTERNAL_ERROR', 'UNMANAGED_EC2_INSTANCE', 'UNSUPPORTED_OS', 'SCAN_ELIGIBILITY_EXPIRED', 'RESOURCE_TERMINATED', 'SUCCESSFUL', 'NO_RESOURCES_FOUND', 'IMAGE_SIZE_EXCEEDED', 'SCAN_FREQUENCY_MANUAL', 'SCAN_FREQUENCY_SCAN_ON_PUSH', 'EC2_INSTANCE_STOPPED', 'PENDING_DISABLE', 'NO_INVENTORY', 'STALE_INVENTORY', 'EXCLUDED_BY_TAG', 'UNSUPPORTED_RUNTIME', 'UNSUPPORTED_MEDIA_TYPE', 'UNSUPPORTED_CONFIG_FILE', 'DEEP_INSPECTION_PACKAGE_COLLECTION_LIMIT_EXCEEDED', 'DEEP_INSPECTION_DAILY_SSM_INVENTORY_LIMIT_EXCEEDED', 'DEEP_INSPECTION_COLLECTION_TIME_LIMIT_EXCEEDED', 'DEEP_INSPECTION_NO_INVENTORY', ], ], 'ScanType' => [ 'type' => 'string', 'enum' => [ 'NETWORK', 'PACKAGE', 'CODE', ], ], 'Schedule' => [ 'type' => 'structure', 'members' => [ 'daily' => [ 'shape' => 'DailySchedule', ], 'monthly' => [ 'shape' => 'MonthlySchedule', ], 'oneTime' => [ 'shape' => 'OneTimeSchedule', ], 'weekly' => [ 'shape' => 'WeeklySchedule', ], ], 'union' => true, ], 'SearchVulnerabilitiesFilterCriteria' => [ 'type' => 'structure', 'required' => [ 'vulnerabilityIds', ], 'members' => [ 'vulnerabilityIds' => [ 'shape' => 'VulnIdList', ], ], ], 'SearchVulnerabilitiesRequest' => [ 'type' => 'structure', 'required' => [ 'filterCriteria', ], 'members' => [ 'filterCriteria' => [ 'shape' => 'SearchVulnerabilitiesFilterCriteria', ], 'nextToken' => [ 'shape' => 'NextToken', ], ], ], 'SearchVulnerabilitiesResponse' => [ 'type' => 'structure', 'required' => [ 'vulnerabilities', ], 'members' => [ 'nextToken' => [ 'shape' => 'NextToken', ], 'vulnerabilities' => [ 'shape' => 'Vulnerabilities', ], ], ], 'SecurityGroupId' => [ 'type' => 'string', 'pattern' => '^sg-([a-z0-9]{8}|[a-z0-9]{17}|\\*)$', ], 'SecurityGroupIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityGroupId', ], 'max' => 5, 'min' => 0, ], 'SendCisSessionHealthRequest' => [ 'type' => 'structure', 'required' => [ 'scanJobId', 'sessionToken', ], 'members' => [ 'scanJobId' => [ 'shape' => 'UUID', ], 'sessionToken' => [ 'shape' => 'UUID', ], ], ], 'SendCisSessionHealthResponse' => [ 'type' => 'structure', 'members' => [], ], 'SendCisSessionTelemetryRequest' => [ 'type' => 'structure', 'required' => [ 'messages', 'scanJobId', 'sessionToken', ], 'members' => [ 'messages' => [ 'shape' => 'CisSessionMessages', ], 'scanJobId' => [ 'shape' => 'UUID', ], 'sessionToken' => [ 'shape' => 'UUID', ], ], ], 'SendCisSessionTelemetryResponse' => [ 'type' => 'structure', 'members' => [], ], 'Service' => [ 'type' => 'string', 'enum' => [ 'EC2', 'ECR', 'LAMBDA', ], ], 'ServiceQuotaExceededException' => [ 'type' => 'structure', 'required' => [ 'message', 'resourceId', ], 'members' => [ 'message' => [ 'shape' => 'String', ], 'resourceId' => [ 'shape' => 'String', ], ], 'error' => [ 'httpStatusCode' => 402, 'senderFault' => true, ], 'exception' => true, ], 'Severity' => [ 'type' => 'string', 'enum' => [ 'INFORMATIONAL', 'LOW', 'MEDIUM', 'HIGH', 'CRITICAL', 'UNTRIAGED', ], ], 'SeverityCounts' => [ 'type' => 'structure', 'members' => [ 'all' => [ 'shape' => 'Long', ], 'critical' => [ 'shape' => 'Long', ], 'high' => [ 'shape' => 'Long', ], 'medium' => [ 'shape' => 'Long', ], ], ], 'SortCriteria' => [ 'type' => 'structure', 'required' => [ 'field', 'sortOrder', ], 'members' => [ 'field' => [ 'shape' => 'SortField', ], 'sortOrder' => [ 'shape' => 'SortOrder', ], ], ], 'SortField' => [ 'type' => 'string', 'enum' => [ 'AWS_ACCOUNT_ID', 'FINDING_TYPE', 'SEVERITY', 'FIRST_OBSERVED_AT', 'LAST_OBSERVED_AT', 'FINDING_STATUS', 'RESOURCE_TYPE', 'ECR_IMAGE_PUSHED_AT', 'ECR_IMAGE_REPOSITORY_NAME', 'ECR_IMAGE_REGISTRY', 'NETWORK_PROTOCOL', 'COMPONENT_TYPE', 'VULNERABILITY_ID', 'VULNERABILITY_SOURCE', 'INSPECTOR_SCORE', 'VENDOR_SEVERITY', 'EPSS_SCORE', ], ], 'SortOrder' => [ 'type' => 'string', 'enum' => [ 'ASC', 'DESC', ], ], 'SourceLayerHash' => [ 'type' => 'string', 'max' => 71, 'min' => 71, 'pattern' => '^sha256:[a-z0-9]{64}$', ], 'StartCisSessionMessage' => [ 'type' => 'structure', 'required' => [ 'sessionToken', ], 'members' => [ 'sessionToken' => [ 'shape' => 'UUID', ], ], ], 'StartCisSessionRequest' => [ 'type' => 'structure', 'required' => [ 'message', 'scanJobId', ], 'members' => [ 'message' => [ 'shape' => 'StartCisSessionMessage', ], 'scanJobId' => [ 'shape' => 'UUID', ], ], ], 'StartCisSessionResponse' => [ 'type' => 'structure', 'members' => [], ], 'State' => [ 'type' => 'structure', 'required' => [ 'errorCode', 'errorMessage', 'status', ], 'members' => [ 'errorCode' => [ 'shape' => 'ErrorCode', ], 'errorMessage' => [ 'shape' => 'NonEmptyString', ], 'status' => [ 'shape' => 'Status', ], ], ], 'Status' => [ 'type' => 'string', 'enum' => [ 'ENABLING', 'ENABLED', 'DISABLING', 'DISABLED', 'SUSPENDING', 'SUSPENDED', ], ], 'StatusCounts' => [ 'type' => 'structure', 'members' => [ 'failed' => [ 'shape' => 'Integer', ], 'passed' => [ 'shape' => 'Integer', ], 'skipped' => [ 'shape' => 'Integer', ], ], ], 'Step' => [ 'type' => 'structure', 'required' => [ 'componentId', 'componentType', ], 'members' => [ 'componentId' => [ 'shape' => 'Component', ], 'componentType' => [ 'shape' => 'ComponentType', ], ], ], 'StepList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Step', ], 'max' => 30, 'min' => 1, ], 'StopCisMessageProgress' => [ 'type' => 'structure', 'members' => [ 'errorChecks' => [ 'shape' => 'CheckCount', ], 'failedChecks' => [ 'shape' => 'CheckCount', ], 'informationalChecks' => [ 'shape' => 'CheckCount', ], 'notApplicableChecks' => [ 'shape' => 'CheckCount', ], 'notEvaluatedChecks' => [ 'shape' => 'CheckCount', ], 'successfulChecks' => [ 'shape' => 'CheckCount', ], 'totalChecks' => [ 'shape' => 'CheckCount', ], 'unknownChecks' => [ 'shape' => 'CheckCount', ], ], ], 'StopCisSessionMessage' => [ 'type' => 'structure', 'required' => [ 'progress', 'status', ], 'members' => [ 'benchmarkProfile' => [ 'shape' => 'BenchmarkProfile', ], 'benchmarkVersion' => [ 'shape' => 'BenchmarkVersion', ], 'computePlatform' => [ 'shape' => 'ComputePlatform', ], 'progress' => [ 'shape' => 'StopCisMessageProgress', ], 'reason' => [ 'shape' => 'Reason', ], 'status' => [ 'shape' => 'StopCisSessionStatus', ], ], ], 'StopCisSessionRequest' => [ 'type' => 'structure', 'required' => [ 'message', 'scanJobId', 'sessionToken', ], 'members' => [ 'message' => [ 'shape' => 'StopCisSessionMessage', ], 'scanJobId' => [ 'shape' => 'UUID', ], 'sessionToken' => [ 'shape' => 'UUID', ], ], ], 'StopCisSessionResponse' => [ 'type' => 'structure', 'members' => [], ], 'StopCisSessionStatus' => [ 'type' => 'string', 'enum' => [ 'SUCCESS', 'FAILED', 'INTERRUPTED', 'UNSUPPORTED_OS', ], ], 'String' => [ 'type' => 'string', ], 'StringComparison' => [ 'type' => 'string', 'enum' => [ 'EQUALS', 'PREFIX', 'NOT_EQUALS', ], ], 'StringFilter' => [ 'type' => 'structure', 'required' => [ 'comparison', 'value', ], 'members' => [ 'comparison' => [ 'shape' => 'StringComparison', ], 'value' => [ 'shape' => 'StringInput', ], ], ], 'StringFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'StringFilter', ], 'max' => 10, 'min' => 1, ], 'StringInput' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'StringList' => [ 'type' => 'list', 'member' => [ 'shape' => 'NonEmptyString', ], ], 'SubnetId' => [ 'type' => 'string', 'pattern' => '^subnet-([a-z0-9]{8}|[a-z0-9]{17}|\\*)$', ], 'SubnetIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'SubnetId', ], 'max' => 16, 'min' => 0, ], 'SuggestedFix' => [ 'type' => 'structure', 'members' => [ 'code' => [ 'shape' => 'SuggestedFixCodeString', ], 'description' => [ 'shape' => 'SuggestedFixDescriptionString', ], ], ], 'SuggestedFixCodeString' => [ 'type' => 'string', 'max' => 2500, 'min' => 1, ], 'SuggestedFixDescriptionString' => [ 'type' => 'string', 'max' => 1000, 'min' => 1, ], 'SuggestedFixes' => [ 'type' => 'list', 'member' => [ 'shape' => 'SuggestedFix', ], 'max' => 5, 'min' => 1, ], 'TagComparison' => [ 'type' => 'string', 'enum' => [ 'EQUALS', ], ], 'TagFilter' => [ 'type' => 'structure', 'required' => [ 'comparison', 'key', 'value', ], 'members' => [ 'comparison' => [ 'shape' => 'TagComparison', ], 'key' => [ 'shape' => 'NonEmptyString', ], 'value' => [ 'shape' => 'NonEmptyString', ], ], ], 'TagKey' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '^(?!aws:)[a-zA-Z+-=._:/]+$', ], 'TagKeyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TagKey', ], 'max' => 50, 'min' => 0, ], 'TagList' => [ 'type' => 'list', 'member' => [ 'shape' => 'String', ], ], 'TagMap' => [ 'type' => 'map', 'key' => [ 'shape' => 'MapKey', ], 'value' => [ 'shape' => 'MapValue', ], ], 'TagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'resourceArn', 'tags', ], 'members' => [ 'resourceArn' => [ 'shape' => 'Arn', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'tags' => [ 'shape' => 'TagMap', ], ], ], 'TagResourceResponse' => [ 'type' => 'structure', 'members' => [], ], 'TagValueList' => [ 'type' => 'list', 'member' => [ 'shape' => 'String', ], 'max' => 5, 'min' => 1, ], 'Target' => [ 'type' => 'string', 'max' => 50, 'min' => 0, ], 'TargetAccount' => [ 'type' => 'string', 'pattern' => '^\\d{12}|ALL_ACCOUNTS|SELF$', ], 'TargetAccountList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TargetAccount', ], 'max' => 10000, 'min' => 1, ], 'TargetResourceTags' => [ 'type' => 'map', 'key' => [ 'shape' => 'NonEmptyString', ], 'value' => [ 'shape' => 'TagValueList', ], 'max' => 5, 'min' => 1, ], 'TargetStatusFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'CisTargetStatusFilter', ], 'max' => 10, 'min' => 1, ], 'TargetStatusReasonFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'CisTargetStatusReasonFilter', ], 'max' => 10, 'min' => 1, ], 'Targets' => [ 'type' => 'list', 'member' => [ 'shape' => 'Target', ], 'min' => 0, ], 'ThrottlingException' => [ 'type' => 'structure', 'required' => [ 'message', ], 'members' => [ 'message' => [ 'shape' => 'String', ], 'retryAfterSeconds' => [ 'shape' => 'Integer', 'location' => 'header', 'locationName' => 'Retry-After', ], ], 'error' => [ 'httpStatusCode' => 429, 'senderFault' => true, ], 'exception' => true, 'retryable' => [ 'throttling' => true, ], ], 'Time' => [ 'type' => 'structure', 'required' => [ 'timeOfDay', 'timezone', ], 'members' => [ 'timeOfDay' => [ 'shape' => 'TimeOfDay', ], 'timezone' => [ 'shape' => 'Timezone', ], ], ], 'TimeOfDay' => [ 'type' => 'string', 'pattern' => '^([0-1]?[0-9]|2[0-3]):[0-5][0-9]$', ], 'Timestamp' => [ 'type' => 'timestamp', ], 'Timezone' => [ 'type' => 'string', 'max' => 50, 'min' => 1, ], 'TitleAggregation' => [ 'type' => 'structure', 'members' => [ 'findingType' => [ 'shape' => 'AggregationFindingType', ], 'resourceType' => [ 'shape' => 'AggregationResourceType', ], 'sortBy' => [ 'shape' => 'TitleSortBy', ], 'sortOrder' => [ 'shape' => 'SortOrder', ], 'titles' => [ 'shape' => 'StringFilterList', ], 'vulnerabilityIds' => [ 'shape' => 'StringFilterList', ], ], ], 'TitleAggregationResponse' => [ 'type' => 'structure', 'required' => [ 'title', ], 'members' => [ 'accountId' => [ 'shape' => 'AccountId', ], 'severityCounts' => [ 'shape' => 'SeverityCounts', ], 'title' => [ 'shape' => 'NonEmptyString', ], 'vulnerabilityId' => [ 'shape' => 'String', ], ], ], 'TitleFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'CisStringFilter', ], 'max' => 10, 'min' => 1, ], 'TitleSortBy' => [ 'type' => 'string', 'enum' => [ 'CRITICAL', 'HIGH', 'ALL', ], ], 'Tool' => [ 'type' => 'string', 'min' => 0, ], 'Tools' => [ 'type' => 'list', 'member' => [ 'shape' => 'Tool', ], ], 'Ttp' => [ 'type' => 'string', 'max' => 30, 'min' => 0, ], 'Ttps' => [ 'type' => 'list', 'member' => [ 'shape' => 'Ttp', ], 'min' => 0, ], 'UUID' => [ 'type' => 'string', 'pattern' => '^[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}$', ], 'UntagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'resourceArn', 'tagKeys', ], 'members' => [ 'resourceArn' => [ 'shape' => 'Arn', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'tagKeys' => [ 'shape' => 'TagKeyList', 'location' => 'querystring', 'locationName' => 'tagKeys', ], ], ], 'UntagResourceResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateCisScanConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'scanConfigurationArn', ], 'members' => [ 'scanConfigurationArn' => [ 'shape' => 'CisScanConfigurationArn', ], 'scanName' => [ 'shape' => 'CisScanName', ], 'schedule' => [ 'shape' => 'Schedule', ], 'securityLevel' => [ 'shape' => 'CisSecurityLevel', ], 'targets' => [ 'shape' => 'UpdateCisTargets', ], ], ], 'UpdateCisScanConfigurationResponse' => [ 'type' => 'structure', 'required' => [ 'scanConfigurationArn', ], 'members' => [ 'scanConfigurationArn' => [ 'shape' => 'CisScanConfigurationArn', ], ], ], 'UpdateCisTargets' => [ 'type' => 'structure', 'members' => [ 'accountIds' => [ 'shape' => 'TargetAccountList', ], 'targetResourceTags' => [ 'shape' => 'TargetResourceTags', ], ], ], 'UpdateConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'ecrConfiguration', ], 'members' => [ 'ecrConfiguration' => [ 'shape' => 'EcrConfiguration', ], ], ], 'UpdateConfigurationResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateEc2DeepInspectionConfigurationRequest' => [ 'type' => 'structure', 'members' => [ 'activateDeepInspection' => [ 'shape' => 'Boolean', ], 'packagePaths' => [ 'shape' => 'PathList', ], ], ], 'UpdateEc2DeepInspectionConfigurationResponse' => [ 'type' => 'structure', 'members' => [ 'errorMessage' => [ 'shape' => 'NonEmptyString', ], 'orgPackagePaths' => [ 'shape' => 'PathList', ], 'packagePaths' => [ 'shape' => 'PathList', ], 'status' => [ 'shape' => 'Ec2DeepInspectionStatus', ], ], ], 'UpdateEncryptionKeyRequest' => [ 'type' => 'structure', 'required' => [ 'kmsKeyId', 'resourceType', 'scanType', ], 'members' => [ 'kmsKeyId' => [ 'shape' => 'KmsKeyArn', ], 'resourceType' => [ 'shape' => 'ResourceType', ], 'scanType' => [ 'shape' => 'ScanType', ], ], ], 'UpdateEncryptionKeyResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateFilterRequest' => [ 'type' => 'structure', 'required' => [ 'filterArn', ], 'members' => [ 'action' => [ 'shape' => 'FilterAction', ], 'description' => [ 'shape' => 'FilterDescription', ], 'filterArn' => [ 'shape' => 'FilterArn', ], 'filterCriteria' => [ 'shape' => 'FilterCriteria', ], 'name' => [ 'shape' => 'FilterName', ], 'reason' => [ 'shape' => 'FilterReason', ], ], ], 'UpdateFilterResponse' => [ 'type' => 'structure', 'required' => [ 'arn', ], 'members' => [ 'arn' => [ 'shape' => 'FilterArn', ], ], ], 'UpdateOrgEc2DeepInspectionConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'orgPackagePaths', ], 'members' => [ 'orgPackagePaths' => [ 'shape' => 'PathList', ], ], ], 'UpdateOrgEc2DeepInspectionConfigurationResponse' => [ 'type' => 'structure', 'members' => [], ], 'UpdateOrganizationConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'autoEnable', ], 'members' => [ 'autoEnable' => [ 'shape' => 'AutoEnable', ], ], ], 'UpdateOrganizationConfigurationResponse' => [ 'type' => 'structure', 'required' => [ 'autoEnable', ], 'members' => [ 'autoEnable' => [ 'shape' => 'AutoEnable', ], ], ], 'Usage' => [ 'type' => 'structure', 'members' => [ 'currency' => [ 'shape' => 'Currency', ], 'estimatedMonthlyCost' => [ 'shape' => 'MonthlyCostEstimate', ], 'total' => [ 'shape' => 'UsageValue', ], 'type' => [ 'shape' => 'UsageType', ], ], ], 'UsageAccountId' => [ 'type' => 'string', 'pattern' => '[0-9]{12}', ], 'UsageAccountIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UsageAccountId', ], 'max' => 7000, 'min' => 1, ], 'UsageList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Usage', ], ], 'UsageTotal' => [ 'type' => 'structure', 'members' => [ 'accountId' => [ 'shape' => 'MeteringAccountId', ], 'usage' => [ 'shape' => 'UsageList', ], ], ], 'UsageTotalList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UsageTotal', ], ], 'UsageType' => [ 'type' => 'string', 'enum' => [ 'EC2_INSTANCE_HOURS', 'ECR_INITIAL_SCAN', 'ECR_RESCAN', 'LAMBDA_FUNCTION_HOURS', 'LAMBDA_FUNCTION_CODE_HOURS', ], ], 'UsageValue' => [ 'type' => 'double', 'min' => 0, ], 'ValidationException' => [ 'type' => 'structure', 'required' => [ 'message', 'reason', ], 'members' => [ 'fields' => [ 'shape' => 'ValidationExceptionFields', ], 'message' => [ 'shape' => 'String', ], 'reason' => [ 'shape' => 'ValidationExceptionReason', ], ], 'error' => [ 'httpStatusCode' => 400, 'senderFault' => true, ], 'exception' => true, ], 'ValidationExceptionField' => [ 'type' => 'structure', 'required' => [ 'message', 'name', ], 'members' => [ 'message' => [ 'shape' => 'String', ], 'name' => [ 'shape' => 'String', ], ], ], 'ValidationExceptionFields' => [ 'type' => 'list', 'member' => [ 'shape' => 'ValidationExceptionField', ], ], 'ValidationExceptionReason' => [ 'type' => 'string', 'enum' => [ 'CANNOT_PARSE', 'FIELD_VALIDATION_FAILED', 'OTHER', ], ], 'Vendor' => [ 'type' => 'string', 'max' => 16, 'min' => 0, ], 'VendorCreatedAt' => [ 'type' => 'timestamp', ], 'VendorSeverity' => [ 'type' => 'string', 'max' => 64, 'min' => 1, ], 'VendorUpdatedAt' => [ 'type' => 'timestamp', ], 'Version' => [ 'type' => 'string', 'pattern' => '^\\$LATEST|[0-9]+$', ], 'VpcId' => [ 'type' => 'string', 'pattern' => '^vpc-([a-z0-9]{8}|[a-z0-9]{17}|\\*)$', ], 'VulnId' => [ 'type' => 'string', 'pattern' => '^CVE-[12][0-9]{3}-[0-9]{1,10}$', ], 'VulnIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VulnId', ], 'max' => 1, 'min' => 1, ], 'Vulnerabilities' => [ 'type' => 'list', 'member' => [ 'shape' => 'Vulnerability', ], 'max' => 1, 'min' => 0, ], 'Vulnerability' => [ 'type' => 'structure', 'required' => [ 'id', ], 'members' => [ 'atigData' => [ 'shape' => 'AtigData', ], 'cisaData' => [ 'shape' => 'CisaData', ], 'cvss2' => [ 'shape' => 'Cvss2', ], 'cvss3' => [ 'shape' => 'Cvss3', ], 'cwes' => [ 'shape' => 'Cwes', ], 'description' => [ 'shape' => 'VulnerabilityDescription', ], 'detectionPlatforms' => [ 'shape' => 'DetectionPlatforms', ], 'epss' => [ 'shape' => 'Epss', ], 'exploitObserved' => [ 'shape' => 'ExploitObserved', ], 'id' => [ 'shape' => 'NonEmptyString', ], 'referenceUrls' => [ 'shape' => 'VulnerabilityReferenceUrls', ], 'relatedVulnerabilities' => [ 'shape' => 'RelatedVulnerabilities', ], 'source' => [ 'shape' => 'VulnerabilitySource', ], 'sourceUrl' => [ 'shape' => 'VulnerabilitySourceUrl', ], 'vendorCreatedAt' => [ 'shape' => 'VendorCreatedAt', ], 'vendorSeverity' => [ 'shape' => 'VendorSeverity', ], 'vendorUpdatedAt' => [ 'shape' => 'VendorUpdatedAt', ], ], ], 'VulnerabilityDescription' => [ 'type' => 'string', ], 'VulnerabilityId' => [ 'type' => 'string', 'max' => 128, 'min' => 1, ], 'VulnerabilityIdList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VulnerabilityId', ], ], 'VulnerabilityReferenceUrl' => [ 'type' => 'string', 'min' => 0, ], 'VulnerabilityReferenceUrls' => [ 'type' => 'list', 'member' => [ 'shape' => 'VulnerabilityReferenceUrl', ], 'max' => 100, 'min' => 0, ], 'VulnerabilitySource' => [ 'type' => 'string', 'enum' => [ 'NVD', ], ], 'VulnerabilitySourceUrl' => [ 'type' => 'string', 'min' => 0, ], 'VulnerablePackage' => [ 'type' => 'structure', 'required' => [ 'name', 'version', ], 'members' => [ 'arch' => [ 'shape' => 'PackageArchitecture', ], 'epoch' => [ 'shape' => 'PackageEpoch', ], 'filePath' => [ 'shape' => 'FilePath', ], 'fixedInVersion' => [ 'shape' => 'PackageVersion', ], 'name' => [ 'shape' => 'PackageName', ], 'packageManager' => [ 'shape' => 'PackageManager', ], 'release' => [ 'shape' => 'PackageRelease', ], 'remediation' => [ 'shape' => 'VulnerablePackageRemediation', ], 'sourceLambdaLayerArn' => [ 'shape' => 'LambdaLayerArn', ], 'sourceLayerHash' => [ 'shape' => 'SourceLayerHash', ], 'version' => [ 'shape' => 'PackageVersion', ], ], ], 'VulnerablePackageList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VulnerablePackage', ], ], 'VulnerablePackageRemediation' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'WeeklySchedule' => [ 'type' => 'structure', 'required' => [ 'days', 'startTime', ], 'members' => [ 'days' => [ 'shape' => 'DaysList', ], 'startTime' => [ 'shape' => 'Time', ], ], ], ],]; diff --git a/src/data/inspector2/2020-06-08/docs-2.json b/src/data/inspector2/2020-06-08/docs-2.json index d48b2741ef..c0326181bd 100644 --- a/src/data/inspector2/2020-06-08/docs-2.json +++ b/src/data/inspector2/2020-06-08/docs-2.json @@ -57,7 +57,7 @@ "UpdateCisScanConfiguration": "
Updates a CIS scan configuration.
", "UpdateConfiguration": "Updates setting configurations for your Amazon Inspector account. When you use this API as an Amazon Inspector delegated administrator this updates the setting for all accounts you manage. Member accounts in an organization cannot update this setting.
", "UpdateEc2DeepInspectionConfiguration": "Activates, deactivates Amazon Inspector deep inspection, or updates custom paths for your account.
", - "UpdateEncryptionKey": "Updates an encryption key. A ResourceNotFoundException
means that an AWS owned key is being used for encryption.
Updates an encryption key. A ResourceNotFoundException
means that an Amazon Web Services owned key is being used for encryption.
Specifies the action that is to be applied to the findings that match the filter.
", "UpdateOrgEc2DeepInspectionConfiguration": "Updates the Amazon Inspector deep inspection custom paths for your organization. You must be an Amazon Inspector delegated administrator to use this API.
", "UpdateOrganizationConfiguration": "Updates the configurations for your Amazon Inspector organization.
" @@ -117,8 +117,8 @@ "GetCisScanResultDetailsRequest$accountId": "The account ID.
", "GetMemberRequest$accountId": "The Amazon Web Services account ID of the member account to retrieve information on.
", "ImageLayerAggregationResponse$accountId": "The ID of the Amazon Web Services account that owns the container image hosting the layer image.
", - "LambdaFunctionAggregationResponse$accountId": "The ID of the AWS account that owns the AWS Lambda function.
", - "LambdaLayerAggregationResponse$accountId": "The account ID of the AWS Lambda function layer.
", + "LambdaFunctionAggregationResponse$accountId": "The ID of the Amazon Web Services account that owns the Amazon Web Services Lambda function.
", + "LambdaLayerAggregationResponse$accountId": "The account ID of the Amazon Web Services Lambda function layer.
", "Member$accountId": "The Amazon Web Services account ID of the member account.
", "Member$delegatedAdminAccountId": "The Amazon Web Services account ID of the Amazon Inspector delegated administrator for this member account.
", "MemberAccountEc2DeepInspectionStatus$accountId": "The unique identifier for the Amazon Web Services account of the organization member.
", @@ -252,7 +252,7 @@ "ArchitectureList": { "base": null, "refs": { - "AwsLambdaFunctionDetails$architectures": "The instruction set architecture that the AWS Lambda function supports. Architecture is a string array with one of the valid values. The default architecture value is x86_64
.
The instruction set architecture that the Amazon Web Services Lambda function supports. Architecture is a string array with one of the valid values. The default architecture value is x86_64
.
A summary of information about the AWS Lambda function.
", + "base": "A summary of information about the Amazon Web Services Lambda function.
", "refs": { - "ResourceDetails$awsLambdaFunction": "A summary of the information about an AWS Lambda function affected by a finding.
" + "ResourceDetails$awsLambdaFunction": "A summary of the information about an Amazon Web Services Lambda function affected by a finding.
" } }, "BadRequestException": { @@ -417,8 +417,8 @@ "refs": { "AutoEnable$ec2": "Represents whether Amazon EC2 scans are automatically enabled for new members of your Amazon Inspector organization.
", "AutoEnable$ecr": "Represents whether Amazon ECR scans are automatically enabled for new members of your Amazon Inspector organization.
", - "AutoEnable$lambda": "Represents whether AWS Lambda standard scans are automatically enabled for new members of your Amazon Inspector organization.
", - "AutoEnable$lambdaCode": "Represents whether AWS Lambda code scans are automatically enabled for new members of your Amazon Inspector organization.
</p>
",
+ "AutoEnable$lambda": "Represents whether Amazon Web Services Lambda standard scans are automatically enabled for new members of your Amazon Inspector organization.
", + "AutoEnable$lambdaCode": "Represents whether Lambda code scans are automatically enabled for new members of your Amazon Inspector organization.
</p>
",
"DescribeOrganizationConfigurationResponse$maxAccountLimitReached": "Represents whether your organization has reached the maximum Amazon Web Services account limit for Amazon Inspector.
", "ListMembersRequest$onlyAssociated": "Specifies whether to list only currently associated members if True
or to list all members within the organization if False
.
Whether Amazon Inspector deep inspection is active in the account. If TRUE
Amazon Inspector deep inspection is active, if FALSE
it is not active.
The date an image was last pulled at.
", "CoverageFilterCriteria$lastScannedAt": "Filters Amazon Web Services resources based on whether Amazon Inspector has checked them for vulnerabilities within the specified time range.
" } }, @@ -1061,7 +1062,7 @@ "base": null, "refs": { "CoverageFilterCriteria$ec2InstanceTags": "The Amazon EC2 instance tags to filter on.
", - "CoverageFilterCriteria$lambdaFunctionTags": "Returns coverage statistics for AWS Lambda functions filtered by tag.
" + "CoverageFilterCriteria$lambdaFunctionTags": "Returns coverage statistics for Amazon Web Services Lambda functions filtered by tag.
" } }, "CoverageResourceType": { @@ -1088,8 +1089,8 @@ "CoverageFilterCriteria$accountId": "An array of Amazon Web Services account IDs to return coverage statistics for.
", "CoverageFilterCriteria$ecrImageTags": "The Amazon ECR image tags to filter on.
", "CoverageFilterCriteria$ecrRepositoryName": "The Amazon ECR repository name to filter on.
", - "CoverageFilterCriteria$lambdaFunctionName": "Returns coverage statistics for AWS Lambda functions filtered by function names.
", - "CoverageFilterCriteria$lambdaFunctionRuntime": "Returns coverage statistics for AWS Lambda functions filtered by runtime.
", + "CoverageFilterCriteria$lambdaFunctionName": "Returns coverage statistics for Amazon Web Services Lambda functions filtered by function names.
", + "CoverageFilterCriteria$lambdaFunctionRuntime": "Returns coverage statistics for Amazon Web Services Lambda functions filtered by runtime.
", "CoverageFilterCriteria$resourceId": "An array of Amazon Web Services resource IDs to return coverage statistics for.
", "CoverageFilterCriteria$resourceType": "An array of Amazon Web Services resource types to return coverage statistics for. The values can be AWS_EC2_INSTANCE
, AWS_LAMBDA_FUNCTION
, AWS_ECR_CONTAINER_IMAGE
, AWS_ECR_REPOSITORY
or AWS_ACCOUNT
.
The scan status code to filter on. Valid values are: ValidationException
, InternalServerException
, ResourceNotFoundException
, BadRequestException
, and ThrottlingException
.
Details on the Amazon ECR image push date and time used to filter findings.
", "FilterCriteria$firstObservedAt": "Details on the date and time a finding was first seen used to filter findings.
", - "FilterCriteria$lambdaFunctionLastModifiedAt": "Filters the list of AWS Lambda functions by the date and time that a user last updated the configuration, in ISO 8601 format
", + "FilterCriteria$lambdaFunctionLastModifiedAt": "Filters the list of Amazon Web Services Lambda functions by the date and time that a user last updated the configuration, in ISO 8601 format
", "FilterCriteria$lastObservedAt": "Details on the date and time a finding was last seen used to filter findings.
", "FilterCriteria$updatedAt": "Details on the date and time a finding was last updated at used to filter findings.
" } @@ -1282,6 +1283,7 @@ "CoverageDateFilter$endInclusive": "A timestamp representing the end of the time period to filter results by.
", "CoverageDateFilter$startInclusive": "A timestamp representing the start of the time period to filter results by.
", "CoveredResource$lastScannedAt": "The date and time the resource was last checked for vulnerabilities.
", + "EcrContainerImageMetadata$imagePulledAt": "The date an image was last pulled at.
", "EcrRescanDurationState$updatedAt": "A timestamp representing when the last time the ECR scan duration setting was changed.
", "ExploitabilityDetails$lastKnownExploitAt": "The date and time of the last exploit associated with a finding discovered in your environment.
", "Filter$createdAt": "The date and time this filter was created at.
", @@ -1289,7 +1291,7 @@ "Finding$firstObservedAt": "The date and time that the finding was first observed.
", "Finding$lastObservedAt": "The date and time that the finding was last observed.
", "Finding$updatedAt": "The date and time the finding was last updated at.
", - "LambdaFunctionAggregationResponse$lastModifiedAt": "The date that the AWS Lambda function included in the aggregation results was last changed.
", + "LambdaFunctionAggregationResponse$lastModifiedAt": "The date that the Amazon Web Services Lambda function included in the aggregation results was last changed.
", "Member$updatedAt": "A timestamp showing when the status of this member was last updated.
", "PackageVulnerabilityDetails$vendorCreatedAt": "The date and time that this vulnerability was first added to the vendor's database.
", "PackageVulnerabilityDetails$vendorUpdatedAt": "The date and time the vendor last updated this vulnerability in their database.
" @@ -1486,6 +1488,13 @@ "ResourceScanMetadata$ecrImage": "An object that contains details about the container metadata for an Amazon ECR image.
" } }, + "EcrPullDateRescanDuration": { + "base": null, + "refs": { + "EcrConfiguration$pullDateRescanDuration": "The rescan duration configured for image pull date.
", + "EcrRescanDurationState$pullDateRescanDuration": "The rescan duration configured for image pull date.
" + } + }, "EcrRepositoryMetadata": { "base": "Information on the Amazon ECR repository metadata associated with a finding.
", "refs": { @@ -1495,14 +1504,14 @@ "EcrRescanDuration": { "base": null, "refs": { - "EcrConfiguration$rescanDuration": "The ECR automated re-scan duration defines how long an ECR image will be actively scanned by Amazon Inspector. When the number of days since an image was last pushed exceeds the automated re-scan duration the monitoring state of that image becomes inactive
and all associated findings are scheduled for closure.
The ECR automated re-scan duration defines how long an ECR image will be actively scanned by Amazon Inspector. When the number of days since an image was last pushed exceeds the automated re-scan duration the monitoring state of that image becomes inactive
and all associated findings are scheduled for closure.
The rescan duration configured for image push date.
", + "EcrRescanDurationState$rescanDuration": "The rescan duration configured for image push date.
</p>
"
}
},
"EcrRescanDurationState": {
- "base": "Details about the state of any changes to the ECR automated re-scan duration setting.
", + "base": "Details about the state of your ECR re-scan duration settings. The ECR re-scan duration defines how long an ECR image will be actively scanned by Amazon Inspector. When the number of days since an image was last pushed exceeds the duration configured for image pull date, and the duration configured for image pull date, the monitoring state of that image becomes inactive
and all associated findings are scheduled for closure.
An object that contains details about the state of the ECR automated re-scan setting.
" + "EcrConfigurationState$rescanDurationState": "An object that contains details about the state of the ECR re-scan settings.
" } }, "EcrRescanDurationStatus": { @@ -1613,7 +1622,7 @@ "ExecutionRoleArn": { "base": null, "refs": { - "AwsLambdaFunctionDetails$executionRoleArn": "The AWS Lambda function's execution role.
" + "AwsLambdaFunctionDetails$executionRoleArn": "The Amazon Web Services Lambda function's execution role.
" } }, "ExploitAvailable": { @@ -1921,7 +1930,7 @@ "FunctionName": { "base": null, "refs": { - "AwsLambdaFunctionDetails$functionName": "The name of the AWS Lambda function.
" + "AwsLambdaFunctionDetails$functionName": "The name of the Amazon Web Services Lambda function.
" } }, "GetCisScanReportRequest": { @@ -2119,21 +2128,21 @@ } }, "LambdaFunctionAggregation": { - "base": "The details that define a findings aggregation based on AWS Lambda functions.
", + "base": "The details that define a findings aggregation based on Amazon Web Services Lambda functions.
", "refs": { - "AggregationRequest$lambdaFunctionAggregation": "Returns an object with findings aggregated by AWS Lambda function.
" + "AggregationRequest$lambdaFunctionAggregation": "Returns an object with findings aggregated by Amazon Web Services Lambda function.
" } }, "LambdaFunctionAggregationResponse": { - "base": "A response that contains the results of an AWS Lambda function finding aggregation.
", + "base": "A response that contains the results of an Amazon Web Services Lambda function finding aggregation.
", "refs": { - "AggregationResponse$lambdaFunctionAggregation": "An aggregation of findings by AWS Lambda function.
" + "AggregationResponse$lambdaFunctionAggregation": "An aggregation of findings by Amazon Web Services Lambda function.
" } }, "LambdaFunctionMetadata": { - "base": "The AWS Lambda function metadata.
", + "base": "The Amazon Web Services Lambda function metadata.
", "refs": { - "ResourceScanMetadata$lambdaFunction": "An object that contains metadata details for an AWS Lambda function.
" + "ResourceScanMetadata$lambdaFunction": "An object that contains metadata details for an Amazon Web Services Lambda function.
" } }, "LambdaFunctionSortBy": { @@ -2143,15 +2152,15 @@ } }, "LambdaLayerAggregation": { - "base": "The details that define a findings aggregation based on an AWS Lambda function's layers.
", + "base": "The details that define a findings aggregation based on an Amazon Web Services Lambda function's layers.
", "refs": { - "AggregationRequest$lambdaLayerAggregation": "Returns an object with findings aggregated by AWS Lambda layer.
" + "AggregationRequest$lambdaLayerAggregation": "Returns an object with findings aggregated by Amazon Web Services Lambda layer.
" } }, "LambdaLayerAggregationResponse": { - "base": "A response that contains the results of an AWS Lambda function layer finding aggregation.
", + "base": "A response that contains the results of an Amazon Web Services Lambda function layer finding aggregation.
", "refs": { - "AggregationResponse$lambdaLayerAggregation": "An aggregation of findings by AWS Lambda layer.
" + "AggregationResponse$lambdaLayerAggregation": "An aggregation of findings by Amazon Web Services Lambda layer.
" } }, "LambdaLayerArn": { @@ -2159,13 +2168,13 @@ "refs": { "CodeVulnerabilityDetails$sourceLambdaLayerArn": "The Amazon Resource Name (ARN) of the Lambda layer that the code vulnerability was detected in.
", "LayerList$member": null, - "VulnerablePackage$sourceLambdaLayerArn": "The Amazon Resource Number (ARN) of the AWS Lambda function affected by a finding.
" + "VulnerablePackage$sourceLambdaLayerArn": "The Amazon Resource Number (ARN) of the Amazon Web Services Lambda function affected by a finding.
" } }, "LambdaLayerList": { "base": null, "refs": { - "LambdaFunctionMetadata$layers": "The layers for an AWS Lambda function. A Lambda function can have up to five layers.
" + "LambdaFunctionMetadata$layers": "The layers for an Amazon Web Services Lambda function. A Lambda function can have up to five layers.
" } }, "LambdaLayerSortBy": { @@ -2175,9 +2184,9 @@ } }, "LambdaVpcConfig": { - "base": "The VPC security groups and subnets that are attached to an AWS Lambda function. For more information, see VPC Settings.
", + "base": "The VPC security groups and subnets that are attached to an Amazon Web Services Lambda function. For more information, see VPC Settings.
", "refs": { - "AwsLambdaFunctionDetails$vpcConfig": "The AWS Lambda function's networking configuration.
" + "AwsLambdaFunctionDetails$vpcConfig": "The Amazon Web Services Lambda function's networking configuration.
" } }, "LastSeen": { @@ -2190,7 +2199,7 @@ "LayerList": { "base": null, "refs": { - "AwsLambdaFunctionDetails$layers": "The AWS Lambda function's layers. A Lambda function can have up to five layers.
" + "AwsLambdaFunctionDetails$layers": "The Amazon Web Services Lambda function's layers. A Lambda function can have up to five layers.
" } }, "ListAccountPermissionsMaxResults": { @@ -2596,7 +2605,7 @@ "AwsEcrContainerImageDetails$architecture": "The architecture of the Amazon ECR container image.
", "AwsEcrContainerImageDetails$registry": "The registry for the Amazon ECR container image.
", "AwsEcrContainerImageDetails$repositoryName": "The name of the repository the Amazon ECR container image resides in.
", - "AwsLambdaFunctionDetails$codeSha256": "The SHA256 hash of the AWS Lambda function's deployment package.
", + "AwsLambdaFunctionDetails$codeSha256": "The SHA256 hash of the Amazon Web Services Lambda function's deployment package.
", "CodeFilePath$fileName": "The name of the file the code vulnerability was found in.
", "CodeFilePath$filePath": "The file path to the code that a vulnerability was found in.
", "CodeSnippetError$errorMessage": "The error message received when Amazon Inspector failed to retrieve a code snippet.
", @@ -2628,9 +2637,9 @@ "ImageLayerAggregationResponse$resourceId": "The resource ID of the container image layer.
", "ImageTagList$member": null, "LambdaFunctionAggregationResponse$resourceId": "The resource IDs included in the aggregation results.
", - "LambdaLayerAggregationResponse$functionName": "The names of the AWS Lambda functions associated with the layers.
", - "LambdaLayerAggregationResponse$layerArn": "The Amazon Resource Name (ARN) of the AWS Lambda function layer.
", - "LambdaLayerAggregationResponse$resourceId": "The Resource ID of the AWS Lambda function layer.
", + "LambdaLayerAggregationResponse$functionName": "The names of the Amazon Web Services Lambda functions associated with the layers.
", + "LambdaLayerAggregationResponse$layerArn": "The Amazon Resource Name (ARN) of the Amazon Web Services Lambda function layer.
", + "LambdaLayerAggregationResponse$resourceId": "The Resource ID of the Amazon Web Services Lambda function layer.
", "MemberAccountEc2DeepInspectionStatusState$errorMessage": "The error message explaining why the account failed to activate Amazon Inspector deep inspection.
", "NonEmptyStringList$member": null, "PackageAggregationResponse$packageName": "The name of the operating system package.
", @@ -3023,7 +3032,7 @@ "base": null, "refs": { "ResourceFilterCriteria$ec2InstanceTags": "The EC2 instance tags used as resource filter criteria.
", - "ResourceFilterCriteria$lambdaFunctionTags": "The AWS Lambda function tags used as resource filter criteria.
" + "ResourceFilterCriteria$lambdaFunctionTags": "The Amazon Web Services Lambda function tags used as resource filter criteria.
" } }, "ResourceNotFoundException": { @@ -3075,7 +3084,7 @@ "ResourceFilterCriteria$accountId": "The account IDs used as resource filter criteria.
", "ResourceFilterCriteria$ecrImageTags": "The ECR image tags used as resource filter criteria.
", "ResourceFilterCriteria$ecrRepositoryName": "The ECR repository names used as resource filter criteria.
", - "ResourceFilterCriteria$lambdaFunctionName": "The AWS Lambda function name used as resource filter criteria.
", + "ResourceFilterCriteria$lambdaFunctionName": "The Amazon Web Services Lambda function name used as resource filter criteria.
", "ResourceFilterCriteria$resourceId": "The resource IDs used as resource filter criteria.
", "ResourceFilterCriteria$resourceType": "The resource types used as resource filter criteria.
" } @@ -3118,8 +3127,8 @@ "Runtime": { "base": null, "refs": { - "AwsLambdaFunctionDetails$runtime": "The runtime environment for the AWS Lambda function.
", - "LambdaFunctionMetadata$runtime": "An AWS Lambda function's runtime.
" + "AwsLambdaFunctionDetails$runtime": "The runtime environment for the Amazon Web Services Lambda function.
", + "LambdaFunctionMetadata$runtime": "An Amazon Web Services Lambda function's runtime.
" } }, "SbomReportFormat": { @@ -3189,7 +3198,7 @@ "SecurityGroupIdList": { "base": null, "refs": { - "LambdaVpcConfig$securityGroupIds": "The VPC security groups and subnets that are attached to an AWS Lambda function. For more information, see VPC Settings.
" + "LambdaVpcConfig$securityGroupIds": "The VPC security groups and subnets that are attached to an Amazon Web Services Lambda function. For more information, see VPC Settings.
" } }, "SendCisSessionHealthRequest": { @@ -3315,7 +3324,7 @@ "FailedMemberAccountEc2DeepInspectionStatusState$ec2ScanStatus": "The status of EC2 scanning in the account that failed to activate Amazon Inspector deep inspection.
", "ResourceStatus$ec2": "The status of Amazon Inspector scanning for Amazon EC2 resources.
", "ResourceStatus$ecr": "The status of Amazon Inspector scanning for Amazon ECR resources.
", - "ResourceStatus$lambda": "The status of Amazon Inspector scanning for AWS Lambda function.
", + "ResourceStatus$lambda": "The status of Amazon Inspector scanning for Amazon Web Services Lambda function.
", "ResourceStatus$lambdaCode": "The status of Amazon Inspector scanning for custom application code for Amazon Web Services Lambda functions.
", "State$status": "The status of Amazon Inspector for the account.
" } @@ -3401,7 +3410,7 @@ "FreeTrialInfoError$message": "The error message returned.
", "GetCisScanReportResponse$url": "The URL where the CIS scan report PDF can be downloaded.
", "InternalServerException$message": null, - "LambdaFunctionAggregationResponse$functionName": "The AWS Lambda function names included in the aggregation results.
", + "LambdaFunctionAggregationResponse$functionName": "The Amazon Web Services Lambda function names included in the aggregation results.
", "LambdaFunctionAggregationResponse$runtime": "The runtimes included in the aggregation results.
", "LambdaFunctionMetadata$functionName": "The name of a function.
", "LambdaLayerList$member": null, @@ -3461,15 +3470,15 @@ "FilterCriteria$ecrImageRegistry": "Details on the Amazon ECR registry used to filter findings.
", "FilterCriteria$ecrImageRepositoryName": "Details on the name of the Amazon ECR repository used to filter findings.
", "FilterCriteria$ecrImageTags": "The tags attached to the Amazon ECR container image.
", - "FilterCriteria$exploitAvailable": "Filters the list of AWS Lambda findings by the availability of exploits.
", + "FilterCriteria$exploitAvailable": "Filters the list of Amazon Web Services Lambda findings by the availability of exploits.
", "FilterCriteria$findingArn": "Details on the finding ARNs used to filter findings.
", "FilterCriteria$findingStatus": "Details on the finding status types used to filter findings.
", "FilterCriteria$findingType": "Details on the finding types used to filter findings.
", "FilterCriteria$fixAvailable": "Details on whether a fix is available through a version update. This value can be YES
, NO
, or PARTIAL
. A PARTIAL
fix means that some, but not all, of the packages identified in the finding have fixes available through updated versions.
Filters the list of AWS Lambda functions by execution role.
", - "FilterCriteria$lambdaFunctionLayers": "Filters the list of AWS Lambda functions by the function's layers. A Lambda function can have up to five layers.
", - "FilterCriteria$lambdaFunctionName": "Filters the list of AWS Lambda functions by the name of the function.
", - "FilterCriteria$lambdaFunctionRuntime": "Filters the list of AWS Lambda functions by the runtime environment for the Lambda function.
", + "FilterCriteria$lambdaFunctionExecutionRoleArn": "Filters the list of Amazon Web Services Lambda functions by execution role.
", + "FilterCriteria$lambdaFunctionLayers": "Filters the list of Amazon Web Services Lambda functions by the function's layers. A Lambda function can have up to five layers.
", + "FilterCriteria$lambdaFunctionName": "Filters the list of Amazon Web Services Lambda functions by the name of the function.
", + "FilterCriteria$lambdaFunctionRuntime": "Filters the list of Amazon Web Services Lambda functions by the runtime environment for the Lambda function.
", "FilterCriteria$networkProtocol": "Details on network protocol used to filter findings.
", "FilterCriteria$relatedVulnerabilities": "Details on the related vulnerabilities used to filter findings.
", "FilterCriteria$resourceId": "Details on the resource IDs used to filter findings.
", @@ -3482,12 +3491,12 @@ "ImageLayerAggregation$layerHashes": "The hashes associated with the layers.
", "ImageLayerAggregation$repositories": "The repository associated with the container image hosting the layers.
", "ImageLayerAggregation$resourceIds": "The ID of the container image layer.
", - "LambdaFunctionAggregation$functionNames": "The AWS Lambda function names to include in the aggregation results.
", + "LambdaFunctionAggregation$functionNames": "The Amazon Web Services Lambda function names to include in the aggregation results.
", "LambdaFunctionAggregation$resourceIds": "The resource IDs to include in the aggregation results.
", - "LambdaFunctionAggregation$runtimes": "Returns findings aggregated by AWS Lambda function runtime environments.
", - "LambdaLayerAggregation$functionNames": "The names of the AWS Lambda functions associated with the layers.
", - "LambdaLayerAggregation$layerArns": "The Amazon Resource Name (ARN) of the AWS Lambda function layer.
", - "LambdaLayerAggregation$resourceIds": "The resource IDs for the AWS Lambda function layers.
", + "LambdaFunctionAggregation$runtimes": "Returns findings aggregated by Amazon Web Services Lambda function runtime environments.
", + "LambdaLayerAggregation$functionNames": "The names of the Amazon Web Services Lambda functions associated with the layers.
", + "LambdaLayerAggregation$layerArns": "The Amazon Resource Name (ARN) of the Amazon Web Services Lambda function layer.
", + "LambdaLayerAggregation$resourceIds": "The resource IDs for the Amazon Web Services Lambda function layers.
", "ListFindingAggregationsRequest$accountIds": "The Amazon Web Services account IDs to retrieve finding aggregation data for.
", "PackageAggregation$packageNames": "The names of packages to aggregate findings on.
", "RepositoryAggregation$repositories": "The names of repositories to aggregate findings on.
", @@ -3581,7 +3590,7 @@ "Ec2Metadata$tags": "The tags attached to the instance.
", "Filter$tags": "The tags attached to the filter.
", "LambdaFunctionAggregationResponse$lambdaTags": "The tags included in the aggregation results.
", - "LambdaFunctionMetadata$functionTags": "The resource tags on an AWS Lambda function.
", + "LambdaFunctionMetadata$functionTags": "The resource tags on an Amazon Web Services Lambda function.
", "ListTagsForResourceResponse$tags": "The tags associated with the resource.
", "Resource$tags": "The tags attached to the resource.
", "TagResourceRequest$tags": "The tags to be added to a resource.
" @@ -3934,7 +3943,7 @@ "Version": { "base": null, "refs": { - "AwsLambdaFunctionDetails$version": "The version of the AWS Lambda function.
" + "AwsLambdaFunctionDetails$version": "The version of the Amazon Web Services Lambda function.
" } }, "VpcId": { diff --git a/src/data/inspector2/2020-06-08/docs-2.json.php b/src/data/inspector2/2020-06-08/docs-2.json.php index 47c111d3ec..37b2dd9d44 100644 --- a/src/data/inspector2/2020-06-08/docs-2.json.php +++ b/src/data/inspector2/2020-06-08/docs-2.json.php @@ -1,3 +1,3 @@ '2.0', 'service' => 'Amazon Inspector is a vulnerability discovery service that automates continuous scanning for security vulnerabilities within your Amazon EC2, Amazon ECR, and Amazon Web Services Lambda environments.
', 'operations' => [ 'AssociateMember' => 'Associates an Amazon Web Services account with an Amazon Inspector delegated administrator. An HTTP 200 response indicates the association was successfully started, but doesn’t indicate whether it was completed. You can check if the association completed by using ListMembers for multiple accounts or GetMembers for a single account.
', 'BatchGetAccountStatus' => 'Retrieves the Amazon Inspector status of multiple Amazon Web Services accounts within your environment.
', 'BatchGetCodeSnippet' => 'Retrieves code snippets from findings that Amazon Inspector detected code vulnerabilities in.
', 'BatchGetFindingDetails' => 'Gets vulnerability details for findings.
', 'BatchGetFreeTrialInfo' => 'Gets free trial status for multiple Amazon Web Services accounts.
', 'BatchGetMemberEc2DeepInspectionStatus' => 'Retrieves Amazon Inspector deep inspection activation status of multiple member accounts within your organization. You must be the delegated administrator of an organization in Amazon Inspector to use this API.
', 'BatchUpdateMemberEc2DeepInspectionStatus' => 'Activates or deactivates Amazon Inspector deep inspection for the provided member accounts in your organization. You must be the delegated administrator of an organization in Amazon Inspector to use this API.
', 'CancelFindingsReport' => 'Cancels the given findings report.
', 'CancelSbomExport' => 'Cancels a software bill of materials (SBOM) report.
', 'CreateCisScanConfiguration' => 'Creates a CIS scan configuration.
', 'CreateFilter' => 'Creates a filter resource using specified filter criteria. When the filter action is set to SUPPRESS
this action creates a suppression rule.
Creates a finding report. By default only ACTIVE
findings are returned in the report. To see SUPRESSED
or CLOSED
findings you must specify a value for the findingStatus
filter criteria.
Creates a software bill of materials (SBOM) report.
', 'DeleteCisScanConfiguration' => 'Deletes a CIS scan configuration.
', 'DeleteFilter' => 'Deletes a filter resource.
', 'DescribeOrganizationConfiguration' => 'Describe Amazon Inspector configuration settings for an Amazon Web Services organization.
', 'Disable' => 'Disables Amazon Inspector scans for one or more Amazon Web Services accounts. Disabling all scan types in an account disables the Amazon Inspector service.
', 'DisableDelegatedAdminAccount' => 'Disables the Amazon Inspector delegated administrator for your organization.
', 'DisassociateMember' => 'Disassociates a member account from an Amazon Inspector delegated administrator.
', 'Enable' => 'Enables Amazon Inspector scans for one or more Amazon Web Services accounts.
', 'EnableDelegatedAdminAccount' => 'Enables the Amazon Inspector delegated administrator for your Organizations organization.
', 'GetCisScanReport' => 'Retrieves a CIS scan report.
', 'GetCisScanResultDetails' => 'Retrieves CIS scan result details.
', 'GetConfiguration' => 'Retrieves setting configurations for Inspector scans.
', 'GetDelegatedAdminAccount' => 'Retrieves information about the Amazon Inspector delegated administrator for your organization.
', 'GetEc2DeepInspectionConfiguration' => 'Retrieves the activation status of Amazon Inspector deep inspection and custom paths associated with your account.
', 'GetEncryptionKey' => 'Gets an encryption key.
', 'GetFindingsReportStatus' => 'Gets the status of a findings report.
', 'GetMember' => 'Gets member information for your organization.
', 'GetSbomExport' => 'Gets details of a software bill of materials (SBOM) report.
', 'ListAccountPermissions' => 'Lists the permissions an account has to configure Amazon Inspector.
', 'ListCisScanConfigurations' => 'Lists CIS scan configurations.
', 'ListCisScanResultsAggregatedByChecks' => 'Lists scan results aggregated by checks.
', 'ListCisScanResultsAggregatedByTargetResource' => 'Lists scan results aggregated by a target resource.
', 'ListCisScans' => 'Returns a CIS scan list.
', 'ListCoverage' => 'Lists coverage details for you environment.
', 'ListCoverageStatistics' => 'Lists Amazon Inspector coverage statistics for your environment.
', 'ListDelegatedAdminAccounts' => 'Lists information about the Amazon Inspector delegated administrator of your organization.
', 'ListFilters' => 'Lists the filters associated with your account.
', 'ListFindingAggregations' => 'Lists aggregated finding data for your environment based on specific criteria.
', 'ListFindings' => 'Lists findings for your environment.
', 'ListMembers' => 'List members associated with the Amazon Inspector delegated administrator for your organization.
', 'ListTagsForResource' => 'Lists all tags attached to a given resource.
', 'ListUsageTotals' => 'Lists the Amazon Inspector usage totals over the last 30 days.
', 'ResetEncryptionKey' => 'Resets an encryption key. After the key is reset your resources will be encrypted by an Amazon Web Services owned key.
', 'SearchVulnerabilities' => 'Lists Amazon Inspector coverage details for a specific vulnerability.
', 'SendCisSessionHealth' => 'Sends a CIS session health. This API is used by the Amazon Inspector SSM plugin to communicate with the Amazon Inspector service. The Amazon Inspector SSM plugin calls this API to start a CIS scan session for the scan ID supplied by the service.
', 'SendCisSessionTelemetry' => 'Sends a CIS session telemetry. This API is used by the Amazon Inspector SSM plugin to communicate with the Amazon Inspector service. The Amazon Inspector SSM plugin calls this API to start a CIS scan session for the scan ID supplied by the service.
', 'StartCisSession' => 'Starts a CIS session. This API is used by the Amazon Inspector SSM plugin to communicate with the Amazon Inspector service. The Amazon Inspector SSM plugin calls this API to start a CIS scan session for the scan ID supplied by the service.
', 'StopCisSession' => 'Stops a CIS session. This API is used by the Amazon Inspector SSM plugin to communicate with the Amazon Inspector service. The Amazon Inspector SSM plugin calls this API to start a CIS scan session for the scan ID supplied by the service.
', 'TagResource' => 'Adds tags to a resource.
', 'UntagResource' => 'Removes tags from a resource.
', 'UpdateCisScanConfiguration' => 'Updates a CIS scan configuration.
', 'UpdateConfiguration' => 'Updates setting configurations for your Amazon Inspector account. When you use this API as an Amazon Inspector delegated administrator this updates the setting for all accounts you manage. Member accounts in an organization cannot update this setting.
', 'UpdateEc2DeepInspectionConfiguration' => 'Activates, deactivates Amazon Inspector deep inspection, or updates custom paths for your account.
', 'UpdateEncryptionKey' => 'Updates an encryption key. A ResourceNotFoundException
means that an AWS owned key is being used for encryption.
Specifies the action that is to be applied to the findings that match the filter.
', 'UpdateOrgEc2DeepInspectionConfiguration' => 'Updates the Amazon Inspector deep inspection custom paths for your organization. You must be an Amazon Inspector delegated administrator to use this API.
', 'UpdateOrganizationConfiguration' => 'Updates the configurations for your Amazon Inspector organization.
', ], 'shapes' => [ 'AccessDeniedException' => [ 'base' => 'You do not have sufficient access to perform this action.
', 'refs' => [], ], 'Account' => [ 'base' => 'An Amazon Web Services account within your environment that Amazon Inspector has been enabled for.
', 'refs' => [ 'AccountList$member' => NULL, ], ], 'AccountAggregation' => [ 'base' => 'An object that contains details about an aggregation response based on Amazon Web Services accounts.
', 'refs' => [ 'AggregationRequest$accountAggregation' => 'An object that contains details about an aggregation request based on Amazon Web Services account IDs.
', ], ], 'AccountAggregationResponse' => [ 'base' => 'An aggregation of findings by Amazon Web Services account ID.
', 'refs' => [ 'AggregationResponse$accountAggregation' => 'An object that contains details about an aggregation response based on Amazon Web Services account IDs.
', ], ], 'AccountId' => [ 'base' => NULL, 'refs' => [ 'Account$accountId' => 'The ID of the Amazon Web Services account.
', 'AccountAggregationResponse$accountId' => 'The Amazon Web Services account ID.
', 'AccountIdSet$member' => NULL, 'AccountState$accountId' => 'The Amazon Web Services account ID.
', 'AmiAggregationResponse$accountId' => 'The Amazon Web Services account ID for the AMI.
', 'AssociateMemberRequest$accountId' => 'The Amazon Web Services account ID of the member account to be associated.
', 'AssociateMemberResponse$accountId' => 'The Amazon Web Services account ID of the successfully associated member account.
', 'AwsEcrContainerAggregationResponse$accountId' => 'The Amazon Web Services account ID of the account that owns the container.
', 'CisAccountIdList$member' => NULL, 'CisCheckAggregation$accountId' => 'The account ID for the CIS check.
', 'CisScanResultDetails$accountId' => 'The CIS scan result details\' account ID.
', 'CisTargetResourceAggregation$accountId' => 'The account ID for the CIS target resource.
', 'CoveredResource$accountId' => 'The Amazon Web Services account ID of the covered resource.
', 'DelegatedAdmin$accountId' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator for your organization.
', 'DelegatedAdminAccount$accountId' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator for your organization.
', 'DisableDelegatedAdminAccountRequest$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the current Amazon Inspector delegated administrator.
', 'DisableDelegatedAdminAccountResponse$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the successfully disabled delegated administrator.
', 'DisassociateMemberRequest$accountId' => 'The Amazon Web Services account ID of the member account to disassociate.
', 'DisassociateMemberResponse$accountId' => 'The Amazon Web Services account ID of the successfully disassociated member.
', 'EnableDelegatedAdminAccountRequest$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator.
', 'EnableDelegatedAdminAccountResponse$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the successfully Amazon Inspector delegated administrator.
', 'FailedAccount$accountId' => 'The Amazon Web Services account ID.
', 'FailedMemberAccountEc2DeepInspectionStatusState$accountId' => 'The unique identifier for the Amazon Web Services account of the organization member that failed to activate Amazon Inspector deep inspection.
', 'Finding$awsAccountId' => 'The Amazon Web Services account ID associated with the finding.
', 'FindingTypeAggregationResponse$accountId' => 'The ID of the Amazon Web Services account associated with the findings.
', 'GetCisScanResultDetailsRequest$accountId' => 'The account ID.
', 'GetMemberRequest$accountId' => 'The Amazon Web Services account ID of the member account to retrieve information on.
', 'ImageLayerAggregationResponse$accountId' => 'The ID of the Amazon Web Services account that owns the container image hosting the layer image.
', 'LambdaFunctionAggregationResponse$accountId' => 'The ID of the AWS account that owns the AWS Lambda function.
', 'LambdaLayerAggregationResponse$accountId' => 'The account ID of the AWS Lambda function layer.
', 'Member$accountId' => 'The Amazon Web Services account ID of the member account.
', 'Member$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator for this member account.
', 'MemberAccountEc2DeepInspectionStatus$accountId' => 'The unique identifier for the Amazon Web Services account of the organization member.
', 'MemberAccountEc2DeepInspectionStatusState$accountId' => 'The unique identifier for the Amazon Web Services account of the organization member
', 'PackageAggregationResponse$accountId' => 'The ID of the Amazon Web Services account associated with the findings.
', 'ReportTargetAccounts$member' => NULL, 'RepositoryAggregationResponse$accountId' => 'The ID of the Amazon Web Services account associated with the findings.
', 'TitleAggregationResponse$accountId' => 'The ID of the Amazon Web Services account associated with the findings.
', ], ], 'AccountIdFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$accountIdFilters' => 'The criteria\'s account ID filters.
', 'ListCisScansFilterCriteria$targetAccountIdFilters' => 'The list of target account ID filters.
', ], ], 'AccountIdSet' => [ 'base' => NULL, 'refs' => [ 'BatchGetAccountStatusRequest$accountIds' => 'The 12-digit Amazon Web Services account IDs of the accounts to retrieve Amazon Inspector status for.
', 'BatchGetMemberEc2DeepInspectionStatusRequest$accountIds' => 'The unique identifiers for the Amazon Web Services accounts to retrieve Amazon Inspector deep inspection activation status for.
</p>
', 'DisableRequest$accountIds' => 'An array of account IDs you want to disable Amazon Inspector scans for.
', 'EnableRequest$accountIds' => 'A list of account IDs you want to enable Amazon Inspector scans for.
', ], ], 'AccountList' => [ 'base' => NULL, 'refs' => [ 'DisableResponse$accounts' => 'Information on the accounts that have had Amazon Inspector scans successfully disabled. Details are provided for each account.
', 'EnableResponse$accounts' => 'Information on the accounts that have had Amazon Inspector scans successfully enabled. Details are provided for each account.
', ], ], 'AccountSortBy' => [ 'base' => NULL, 'refs' => [ 'AccountAggregation$sortBy' => 'The value to sort by.
', ], ], 'AccountState' => [ 'base' => 'An object with details the status of an Amazon Web Services account within your Amazon Inspector environment.
', 'refs' => [ 'AccountStateList$member' => NULL, ], ], 'AccountStateList' => [ 'base' => NULL, 'refs' => [ 'BatchGetAccountStatusResponse$accounts' => 'An array of objects that provide details on the status of Amazon Inspector for each of the requested accounts.
', ], ], 'AggCounts' => [ 'base' => NULL, 'refs' => [ 'Counts$count' => 'The number of resources.
', ], ], 'AggregationFindingType' => [ 'base' => NULL, 'refs' => [ 'AccountAggregation$findingType' => 'The type of finding.
', 'FindingTypeAggregation$findingType' => 'The finding type to aggregate.
', 'TitleAggregation$findingType' => 'The type of finding to aggregate on.
', ], ], 'AggregationRequest' => [ 'base' => 'Contains details about an aggregation request.
', 'refs' => [ 'ListFindingAggregationsRequest$aggregationRequest' => 'Details of the aggregation request that is used to filter your aggregation results.
', ], ], 'AggregationResourceType' => [ 'base' => NULL, 'refs' => [ 'AccountAggregation$resourceType' => 'The type of resource.
', 'FindingTypeAggregation$resourceType' => 'The resource type to aggregate.
', 'TitleAggregation$resourceType' => 'The resource type to aggregate on.
', ], ], 'AggregationResponse' => [ 'base' => 'A structure that contains details about the results of an aggregation type.
', 'refs' => [ 'AggregationResponseList$member' => NULL, ], ], 'AggregationResponseList' => [ 'base' => NULL, 'refs' => [ 'ListFindingAggregationsResponse$responses' => 'Objects that contain the results of an aggregation operation.
', ], ], 'AggregationType' => [ 'base' => NULL, 'refs' => [ 'ListFindingAggregationsRequest$aggregationType' => 'The type of the aggregation request.
', 'ListFindingAggregationsResponse$aggregationType' => 'The type of aggregation to perform.
', ], ], 'AmiAggregation' => [ 'base' => 'The details that define an aggregation based on Amazon machine images (AMIs).
', 'refs' => [ 'AggregationRequest$amiAggregation' => 'An object that contains details about an aggregation request based on Amazon Machine Images (AMIs).
', ], ], 'AmiAggregationResponse' => [ 'base' => 'A response that contains the results of a finding aggregation by AMI.
', 'refs' => [ 'AggregationResponse$amiAggregation' => 'An object that contains details about an aggregation response based on Amazon Machine Images (AMIs).
', ], ], 'AmiId' => [ 'base' => NULL, 'refs' => [ 'AmiAggregationResponse$ami' => 'The ID of the AMI that findings were aggregated for.
', 'Ec2InstanceAggregationResponse$ami' => 'The Amazon Machine Image (AMI) of the Amazon EC2 instance.
', 'Ec2Metadata$amiId' => 'The ID of the Amazon Machine Image (AMI) used to launch the instance.
', ], ], 'AmiSortBy' => [ 'base' => NULL, 'refs' => [ 'AmiAggregation$sortBy' => 'The value to sort results by.
', ], ], 'Architecture' => [ 'base' => NULL, 'refs' => [ 'ArchitectureList$member' => NULL, ], ], 'ArchitectureList' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$architectures' => 'The instruction set architecture that the AWS Lambda function supports. Architecture is a string array with one of the valid values. The default architecture value is x86_64
.
The Amazon resource number (ARN) of the resource to list tags of.
', 'TagResourceRequest$resourceArn' => 'The Amazon Resource Name (ARN) of the resource to apply a tag to.
', 'UntagResourceRequest$resourceArn' => 'The Amazon Resource Name (ARN) for the resource to remove tags from.
', ], ], 'AssociateMemberRequest' => [ 'base' => NULL, 'refs' => [], ], 'AssociateMemberResponse' => [ 'base' => NULL, 'refs' => [], ], 'AtigData' => [ 'base' => 'The Amazon Web Services Threat Intel Group (ATIG) details for a specific vulnerability.
', 'refs' => [ 'Vulnerability$atigData' => 'An object that contains information about the Amazon Web Services Threat Intel Group (ATIG) details for the vulnerability.
', ], ], 'AutoEnable' => [ 'base' => 'Represents which scan types are automatically enabled for new members of your Amazon Inspector organization.
', 'refs' => [ 'DescribeOrganizationConfigurationResponse$autoEnable' => 'The scan types are automatically enabled for new members of your organization.
', 'UpdateOrganizationConfigurationRequest$autoEnable' => 'Defines which scan types are enabled automatically for new members of your Amazon Inspector organization.
', 'UpdateOrganizationConfigurationResponse$autoEnable' => 'The updated status of scan types automatically enabled for new members of your Amazon Inspector organization.
', ], ], 'AwsEc2InstanceDetails' => [ 'base' => 'Details of the Amazon EC2 instance involved in a finding.
', 'refs' => [ 'ResourceDetails$awsEc2Instance' => 'An object that contains details about the Amazon EC2 instance involved in the finding.
', ], ], 'AwsEcrContainerAggregation' => [ 'base' => 'An aggregation of information about Amazon ECR containers.
', 'refs' => [ 'AggregationRequest$awsEcrContainerAggregation' => 'An object that contains details about an aggregation request based on Amazon ECR container images.
', ], ], 'AwsEcrContainerAggregationResponse' => [ 'base' => 'An aggregation of information about Amazon ECR containers.
', 'refs' => [ 'AggregationResponse$awsEcrContainerAggregation' => 'An object that contains details about an aggregation response based on Amazon ECR container images.
', ], ], 'AwsEcrContainerImageDetails' => [ 'base' => 'The image details of the Amazon ECR container image.
', 'refs' => [ 'ResourceDetails$awsEcrContainerImage' => 'An object that contains details about the Amazon ECR container image involved in the finding.
', ], ], 'AwsEcrContainerSortBy' => [ 'base' => NULL, 'refs' => [ 'AwsEcrContainerAggregation$sortBy' => 'The value to sort by.
', ], ], 'AwsLambdaFunctionDetails' => [ 'base' => 'A summary of information about the AWS Lambda function.
', 'refs' => [ 'ResourceDetails$awsLambdaFunction' => 'A summary of the information about an AWS Lambda function affected by a finding.
', ], ], 'BadRequestException' => [ 'base' => 'One or more tags submitted as part of the request is not valid.
', 'refs' => [], ], 'BatchGetAccountStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetAccountStatusResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetCodeSnippetRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetCodeSnippetRequestFindingArnsList' => [ 'base' => NULL, 'refs' => [ 'BatchGetCodeSnippetRequest$findingArns' => 'An array of finding ARNs for the findings you want to retrieve code snippets from.
', ], ], 'BatchGetCodeSnippetResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetFindingDetailsRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetFindingDetailsResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetFreeTrialInfoRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetFreeTrialInfoRequestAccountIdsList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFreeTrialInfoRequest$accountIds' => 'The account IDs to get free trial status for.
', ], ], 'BatchGetFreeTrialInfoResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetMemberEc2DeepInspectionStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetMemberEc2DeepInspectionStatusResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchUpdateMemberEc2DeepInspectionStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchUpdateMemberEc2DeepInspectionStatusResponse' => [ 'base' => NULL, 'refs' => [], ], 'BenchmarkProfile' => [ 'base' => NULL, 'refs' => [ 'StopCisSessionMessage$benchmarkProfile' => 'The message benchmark profile.
', ], ], 'BenchmarkVersion' => [ 'base' => NULL, 'refs' => [ 'StopCisSessionMessage$benchmarkVersion' => 'The message benchmark version.
', ], ], 'Boolean' => [ 'base' => NULL, 'refs' => [ 'AutoEnable$ec2' => 'Represents whether Amazon EC2 scans are automatically enabled for new members of your Amazon Inspector organization.
', 'AutoEnable$ecr' => 'Represents whether Amazon ECR scans are automatically enabled for new members of your Amazon Inspector organization.
', 'AutoEnable$lambda' => 'Represents whether AWS Lambda standard scans are automatically enabled for new members of your Amazon Inspector organization.
', 'AutoEnable$lambdaCode' => 'Represents whether AWS Lambda code scans are automatically enabled for new members of your Amazon Inspector organization.
</p>
', 'DescribeOrganizationConfigurationResponse$maxAccountLimitReached' => 'Represents whether your organization has reached the maximum Amazon Web Services account limit for Amazon Inspector.
', 'ListMembersRequest$onlyAssociated' => 'Specifies whether to list only currently associated members if True
or to list all members within the organization if False
.
Whether Amazon Inspector deep inspection is active in the account. If TRUE
Amazon Inspector deep inspection is active, if FALSE
it is not active.
Specify TRUE
to activate Amazon Inspector deep inspection in your account, or FALSE
to deactivate. Member accounts in an organization cannot deactivate deep inspection, instead the delegated administrator for the organization can deactivate a member account using BatchUpdateMemberEc2DeepInspectionStatus.
The progress\' error checks.
', 'StopCisMessageProgress$failedChecks' => 'The progress\' failed checks.
', 'StopCisMessageProgress$informationalChecks' => 'The progress\' informational checks.
', 'StopCisMessageProgress$notApplicableChecks' => 'The progress\' not applicable checks.
', 'StopCisMessageProgress$notEvaluatedChecks' => 'The progress\' not evaluated checks.
', 'StopCisMessageProgress$successfulChecks' => 'The progress\' successful checks.
', 'StopCisMessageProgress$totalChecks' => 'The progress\' total checks.
', 'StopCisMessageProgress$unknownChecks' => 'The progress\' unknown checks.
', ], ], 'CheckIdFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$checkIdFilters' => 'The criteria\'s check ID filters.
', 'CisScanResultsAggregatedByChecksFilterCriteria$checkIdFilters' => 'The criteria\'s check ID filters.
', 'CisScanResultsAggregatedByTargetResourceFilterCriteria$checkIdFilters' => 'The criteria\'s check ID filters.
', ], ], 'CisAccountIdList' => [ 'base' => NULL, 'refs' => [ 'CisTargets$accountIds' => 'The CIS target account ids.
', ], ], 'CisCheckAggregation' => [ 'base' => 'A CIS check.
', 'refs' => [ 'CisCheckAggregationList$member' => NULL, ], ], 'CisCheckAggregationList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByChecksResponse$checkAggregations' => 'The check aggregations.
', ], ], 'CisDateFilter' => [ 'base' => 'The CIS date filter.
', 'refs' => [ 'CisScanDateFilterList$member' => NULL, ], ], 'CisFindingArn' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetails$findingArn' => 'The CIS scan result details\' finding ARN.
', ], ], 'CisFindingArnFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$findingArnFilters' => 'The criteria\'s finding ARN filters.
', ], ], 'CisFindingStatus' => [ 'base' => NULL, 'refs' => [ 'CisFindingStatusFilter$value' => 'The value of the CIS finding status filter.
', 'CisScanResultDetails$status' => 'The CIS scan result details\' status.
', ], ], 'CisFindingStatusComparison' => [ 'base' => NULL, 'refs' => [ 'CisFindingStatusFilter$comparison' => 'The comparison value of the CIS finding status filter.
', ], ], 'CisFindingStatusFilter' => [ 'base' => 'The CIS finding status filter.
', 'refs' => [ 'CisFindingStatusFilterList$member' => NULL, ], ], 'CisFindingStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$findingStatusFilters' => 'The criteria\'s finding status filters.
', ], ], 'CisNumberFilter' => [ 'base' => 'The CIS number filter.
', 'refs' => [ 'CisNumberFilterList$member' => NULL, ], ], 'CisNumberFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByChecksFilterCriteria$failedResourcesFilters' => 'The criteria\'s failed resources filters.
', 'CisScanResultsAggregatedByTargetResourceFilterCriteria$failedChecksFilters' => 'The criteria\'s failed checks filters.
', 'ListCisScansFilterCriteria$failedChecksFilters' => 'The list of failed checks filters.
', ], ], 'CisOwnerId' => [ 'base' => NULL, 'refs' => [ 'CisScanConfiguration$ownerId' => 'The CIS scan configuration\'s owner ID.
', ], ], 'CisReportStatus' => [ 'base' => NULL, 'refs' => [ 'GetCisScanReportResponse$status' => 'The status.
', ], ], 'CisResultStatus' => [ 'base' => NULL, 'refs' => [ 'CisResultStatusFilter$value' => 'The value of the CIS result status filter.
', ], ], 'CisResultStatusComparison' => [ 'base' => NULL, 'refs' => [ 'CisResultStatusFilter$comparison' => 'The comparison value of the CIS result status filter.
', ], ], 'CisResultStatusFilter' => [ 'base' => 'The CIS result status filter.
', 'refs' => [ 'CisResultStatusFilterList$member' => NULL, ], ], 'CisResultStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$statusFilters' => 'The criteria\'s status filter.
', ], ], 'CisRuleDetails' => [ 'base' => NULL, 'refs' => [ 'CisSessionMessage$cisRuleDetails' => 'The CIS rule details for the CIS session message.
', ], ], 'CisRuleStatus' => [ 'base' => NULL, 'refs' => [ 'CisSessionMessage$status' => 'The status of the CIS session message.
', ], ], 'CisScan' => [ 'base' => 'The CIS scan.
', 'refs' => [ 'CisScanList$member' => NULL, ], ], 'CisScanArn' => [ 'base' => NULL, 'refs' => [ 'CisCheckAggregation$scanArn' => 'The scan ARN for the CIS check scan ARN.
', 'CisScan$scanArn' => 'The CIS scan\'s ARN.
', 'CisScanResultDetails$scanArn' => 'The CIS scan result details\' scan ARN.
', 'CisTargetResourceAggregation$scanArn' => 'The scan ARN for the CIS target resource.
', 'GetCisScanReportRequest$scanArn' => 'The scan ARN.
', 'GetCisScanResultDetailsRequest$scanArn' => 'The scan ARN.
', 'ListCisScanResultsAggregatedByChecksRequest$scanArn' => 'The scan ARN.
', 'ListCisScanResultsAggregatedByTargetResourceRequest$scanArn' => 'The scan ARN.
', ], ], 'CisScanArnFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansFilterCriteria$scanArnFilters' => 'The list of scan ARN filters.
', ], ], 'CisScanConfiguration' => [ 'base' => 'The CIS scan configuration.
', 'refs' => [ 'CisScanConfigurationList$member' => NULL, ], ], 'CisScanConfigurationArn' => [ 'base' => NULL, 'refs' => [ 'CisScan$scanConfigurationArn' => 'The CIS scan\'s configuration ARN.
', 'CisScanConfiguration$scanConfigurationArn' => 'The CIS scan configuration\'s scan configuration ARN.
', 'CreateCisScanConfigurationResponse$scanConfigurationArn' => 'The scan configuration ARN for the CIS scan configuration.
', 'DeleteCisScanConfigurationRequest$scanConfigurationArn' => 'The ARN of the CIS scan configuration.
', 'DeleteCisScanConfigurationResponse$scanConfigurationArn' => 'The ARN of the CIS scan configuration.
', 'UpdateCisScanConfigurationRequest$scanConfigurationArn' => 'The CIS scan configuration ARN.
', 'UpdateCisScanConfigurationResponse$scanConfigurationArn' => 'The CIS scan configuration ARN.
', ], ], 'CisScanConfigurationArnFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsFilterCriteria$scanConfigurationArnFilters' => 'The list of scan configuration ARN filters.
', 'ListCisScansFilterCriteria$scanConfigurationArnFilters' => 'The list of scan configuration ARN filters.
', ], ], 'CisScanConfigurationList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsResponse$scanConfigurations' => 'The CIS scan configuration scan configurations.
', ], ], 'CisScanConfigurationsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsRequest$sortBy' => 'The CIS scan configuration sort by order.
', ], ], 'CisScanDateFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansFilterCriteria$scanAtFilters' => 'The list of scan at filters.
', ], ], 'CisScanList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansResponse$scans' => 'The CIS scans.
', ], ], 'CisScanName' => [ 'base' => NULL, 'refs' => [ 'CisScan$scanName' => 'The the name of the scan configuration that\'s associated with this scan.
', 'CisScanConfiguration$scanName' => 'The name of the CIS scan configuration.
', 'CreateCisScanConfigurationRequest$scanName' => 'The scan name for the CIS scan configuration.
', 'UpdateCisScanConfigurationRequest$scanName' => 'The scan name for the CIS scan configuration.
', ], ], 'CisScanNameFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsFilterCriteria$scanNameFilters' => 'The list of scan name filters.
', 'ListCisScansFilterCriteria$scanNameFilters' => 'The list of scan name filters.
', ], ], 'CisScanResultDetails' => [ 'base' => 'The CIS scan result details.
', 'refs' => [ 'CisScanResultDetailsList$member' => NULL, ], ], 'CisScanResultDetailsFilterCriteria' => [ 'base' => 'The CIS scan result details filter criteria.
', 'refs' => [ 'GetCisScanResultDetailsRequest$filterCriteria' => 'The filter criteria.
', ], ], 'CisScanResultDetailsList' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsResponse$scanResultDetails' => 'The scan result details.
', ], ], 'CisScanResultDetailsSortBy' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsRequest$sortBy' => 'The sort by order.
', ], ], 'CisScanResultsAggregatedByChecksFilterCriteria' => [ 'base' => 'The scan results aggregated by checks filter criteria.
', 'refs' => [ 'ListCisScanResultsAggregatedByChecksRequest$filterCriteria' => 'The filter criteria.
', ], ], 'CisScanResultsAggregatedByChecksSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByChecksRequest$sortBy' => 'The sort by order.
', ], ], 'CisScanResultsAggregatedByTargetResourceFilterCriteria' => [ 'base' => 'The scan results aggregated by target resource filter criteria.
', 'refs' => [ 'ListCisScanResultsAggregatedByTargetResourceRequest$filterCriteria' => 'The filter criteria.
', ], ], 'CisScanResultsAggregatedByTargetResourceSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByTargetResourceRequest$sortBy' => 'The sort by order.
', ], ], 'CisScanResultsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByChecksRequest$maxResults' => 'The maximum number of scan results aggregated by checks to be returned in a single page of results.
', 'ListCisScanResultsAggregatedByTargetResourceRequest$maxResults' => 'The maximum number of scan results aggregated by a target resource to be returned in a single page of results.
', ], ], 'CisScanStatus' => [ 'base' => NULL, 'refs' => [ 'CisScan$status' => 'The CIS scan\'s status.
', 'CisScanStatusFilter$value' => 'The filter value.
', ], ], 'CisScanStatusComparison' => [ 'base' => NULL, 'refs' => [ 'CisScanStatusFilter$comparison' => 'The filter comparison value.
', ], ], 'CisScanStatusFilter' => [ 'base' => 'The CIS scan status filter.
', 'refs' => [ 'CisScanStatusFilterList$member' => NULL, ], ], 'CisScanStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansFilterCriteria$scanStatusFilters' => 'The list of scan status filters.
', ], ], 'CisScheduledByFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansFilterCriteria$scheduledByFilters' => 'The list of scheduled by filters.
', ], ], 'CisSecurityLevel' => [ 'base' => NULL, 'refs' => [ 'CisCheckAggregation$level' => 'The CIS check level.
', 'CisScan$securityLevel' => 'The security level for the CIS scan. Security level refers to the Benchmark levels that CIS assigns to a profile.
', 'CisScanConfiguration$securityLevel' => 'The CIS scan configuration\'s security level.
', 'CisScanResultDetails$level' => 'The CIS scan result details\' level.
', 'CisSecurityLevelFilter$value' => 'The CIS security filter value.
', 'CreateCisScanConfigurationRequest$securityLevel' => 'The security level for the CIS scan configuration. Security level refers to the Benchmark levels that CIS assigns to a profile.
', 'UpdateCisScanConfigurationRequest$securityLevel' => 'The security level for the CIS scan configuration. Security level refers to the Benchmark levels that CIS assigns to a profile.
', ], ], 'CisSecurityLevelComparison' => [ 'base' => NULL, 'refs' => [ 'CisSecurityLevelFilter$comparison' => 'The CIS security filter comparison value.
', ], ], 'CisSecurityLevelFilter' => [ 'base' => 'The CIS security level filter. Security level refers to the Benchmark levels that CIS assigns to a profile.
', 'refs' => [ 'CisSecurityLevelFilterList$member' => NULL, ], ], 'CisSecurityLevelFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$securityLevelFilters' => 'The criteria\'s security level filters. . Security level refers to the Benchmark levels that CIS assigns to a profile.
', 'CisScanResultsAggregatedByChecksFilterCriteria$securityLevelFilters' => 'The criteria\'s security level filters.
', ], ], 'CisSessionMessage' => [ 'base' => 'The CIS session message.
', 'refs' => [ 'CisSessionMessages$member' => NULL, ], ], 'CisSessionMessages' => [ 'base' => NULL, 'refs' => [ 'SendCisSessionTelemetryRequest$messages' => 'The CIS session telemetry messages.
', ], ], 'CisSortOrder' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsRequest$sortOrder' => 'The sort order.
', 'ListCisScanConfigurationsRequest$sortOrder' => 'The CIS scan configuration sort order order.
', 'ListCisScanResultsAggregatedByChecksRequest$sortOrder' => 'The sort order.
', 'ListCisScanResultsAggregatedByTargetResourceRequest$sortOrder' => 'The sort order.
', 'ListCisScansRequest$sortOrder' => 'The CIS scans sort order.
', ], ], 'CisStringComparison' => [ 'base' => NULL, 'refs' => [ 'CisStringFilter$comparison' => 'The comparison value of the CIS string filter.
', ], ], 'CisStringFilter' => [ 'base' => 'The CIS string filter.
', 'refs' => [ 'AccountIdFilterList$member' => NULL, 'CheckIdFilterList$member' => NULL, 'CisFindingArnFilterList$member' => NULL, 'CisScanArnFilterList$member' => NULL, 'CisScanConfigurationArnFilterList$member' => NULL, 'CisScanNameFilterList$member' => NULL, 'CisScheduledByFilterList$member' => NULL, 'OneAccountIdFilterList$member' => NULL, 'PlatformFilterList$member' => NULL, 'ResourceIdFilterList$member' => NULL, 'TitleFilterList$member' => NULL, ], ], 'CisTagMap' => [ 'base' => NULL, 'refs' => [ 'CisScanConfiguration$tags' => 'The CIS scan configuration\'s tags.
', 'CreateCisScanConfigurationRequest$tags' => 'The tags for the CIS scan configuration.
', ], ], 'CisTargetResourceAggregation' => [ 'base' => 'The CIS target resource aggregation.
', 'refs' => [ 'CisTargetResourceAggregationList$member' => NULL, ], ], 'CisTargetResourceAggregationList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByTargetResourceResponse$targetResourceAggregations' => 'The resource aggregations.
', ], ], 'CisTargetStatus' => [ 'base' => NULL, 'refs' => [ 'CisTargetResourceAggregation$targetStatus' => 'The status of the target resource.
', 'CisTargetStatusFilter$value' => 'The value of the CIS target status filter.
', ], ], 'CisTargetStatusComparison' => [ 'base' => NULL, 'refs' => [ 'CisTargetStatusFilter$comparison' => 'The comparison value of the CIS target status filter.
', 'CisTargetStatusReasonFilter$comparison' => 'The comparison value of the CIS target status reason filter.
', ], ], 'CisTargetStatusFilter' => [ 'base' => 'The CIS target status filter.
', 'refs' => [ 'TargetStatusFilterList$member' => NULL, ], ], 'CisTargetStatusReason' => [ 'base' => NULL, 'refs' => [ 'CisTargetResourceAggregation$targetStatusReason' => 'The reason for the target resource.
', 'CisTargetStatusReasonFilter$value' => 'The value of the CIS target status reason filter.
', ], ], 'CisTargetStatusReasonFilter' => [ 'base' => 'The CIS target status reason filter.
', 'refs' => [ 'TargetStatusReasonFilterList$member' => NULL, ], ], 'CisTargets' => [ 'base' => 'The CIS targets.
', 'refs' => [ 'CisScan$targets' => 'The CIS scan\'s targets.
', 'CisScanConfiguration$targets' => 'The CIS scan configuration\'s targets.
', ], ], 'CisaAction' => [ 'base' => NULL, 'refs' => [ 'CisaData$action' => 'The remediation action recommended by CISA for this vulnerability.
', ], ], 'CisaData' => [ 'base' => 'The Cybersecurity and Infrastructure Security Agency (CISA) details for a specific vulnerability.
', 'refs' => [ 'FindingDetail$cisaData' => NULL, 'Vulnerability$cisaData' => 'An object that contains the Cybersecurity and Infrastructure Security Agency (CISA) details for the vulnerability.
', ], ], 'CisaDateAdded' => [ 'base' => NULL, 'refs' => [ 'CisaData$dateAdded' => 'The date and time CISA added this vulnerability to their catalogue.
', ], ], 'CisaDateDue' => [ 'base' => NULL, 'refs' => [ 'CisaData$dateDue' => 'The date and time CISA expects a fix to have been provided vulnerability.
', ], ], 'ClientToken' => [ 'base' => NULL, 'refs' => [ 'EnableDelegatedAdminAccountRequest$clientToken' => 'The idempotency token for the request.
', 'EnableRequest$clientToken' => 'The idempotency token for the request.
', ], ], 'CodeFilePath' => [ 'base' => 'Contains information on where a code vulnerability is located in your Lambda function.
', 'refs' => [ 'CodeVulnerabilityDetails$filePath' => 'Contains information on where the code vulnerability is located in your code.
', ], ], 'CodeLine' => [ 'base' => 'Contains information on the lines of code associated with a code snippet.
', 'refs' => [ 'CodeLineList$member' => NULL, ], ], 'CodeLineContentString' => [ 'base' => NULL, 'refs' => [ 'CodeLine$content' => 'The content of a line of code
', ], ], 'CodeLineList' => [ 'base' => NULL, 'refs' => [ 'CodeSnippetResult$codeSnippet' => 'Contains information on the retrieved code snippet.
', ], ], 'CodeSnippetError' => [ 'base' => 'Contains information about any errors encountered while trying to retrieve a code snippet.
', 'refs' => [ 'CodeSnippetErrorList$member' => NULL, ], ], 'CodeSnippetErrorCode' => [ 'base' => NULL, 'refs' => [ 'CodeSnippetError$errorCode' => 'The error code for the error that prevented a code snippet from being retrieved.
', ], ], 'CodeSnippetErrorList' => [ 'base' => NULL, 'refs' => [ 'BatchGetCodeSnippetResponse$errors' => 'Any errors Amazon Inspector encountered while trying to retrieve the requested code snippets.
', ], ], 'CodeSnippetResult' => [ 'base' => 'Contains information on a code snippet retrieved by Amazon Inspector from a code vulnerability finding.
', 'refs' => [ 'CodeSnippetResultList$member' => NULL, ], ], 'CodeSnippetResultList' => [ 'base' => NULL, 'refs' => [ 'BatchGetCodeSnippetResponse$codeSnippetResults' => 'The retrieved code snippets associated with the provided finding ARNs.
', ], ], 'CodeVulnerabilityDetails' => [ 'base' => 'Contains information on the code vulnerability identified in your Lambda function.
', 'refs' => [ 'Finding$codeVulnerabilityDetails' => 'Details about the code vulnerability identified in a Lambda function used to filter findings.
', ], ], 'Component' => [ 'base' => NULL, 'refs' => [ 'Step$componentId' => 'The component ID.
', ], ], 'ComponentType' => [ 'base' => NULL, 'refs' => [ 'Step$componentType' => 'The component type.
', ], ], 'ComputePlatform' => [ 'base' => 'A compute platform.
', 'refs' => [ 'StopCisSessionMessage$computePlatform' => 'The message compute platform.
', ], ], 'ConflictException' => [ 'base' => 'A conflict occurred.
', 'refs' => [], ], 'Counts' => [ 'base' => 'a structure that contains information on the count of resources within a group.
', 'refs' => [ 'CountsList$member' => NULL, ], ], 'CountsList' => [ 'base' => NULL, 'refs' => [ 'ListCoverageStatisticsResponse$countsByGroup' => 'An array with the number for each group.
', ], ], 'CoverageDateFilter' => [ 'base' => 'Contains details of a coverage date filter.
', 'refs' => [ 'CoverageDateFilterList$member' => NULL, ], ], 'CoverageDateFilterList' => [ 'base' => NULL, 'refs' => [ 'CoverageFilterCriteria$lastScannedAt' => 'Filters Amazon Web Services resources based on whether Amazon Inspector has checked them for vulnerabilities within the specified time range.
', ], ], 'CoverageFilterCriteria' => [ 'base' => 'A structure that identifies filter criteria for GetCoverageStatistics
.
An object that contains details on the filters to apply to the coverage data for your environment.
', 'ListCoverageStatisticsRequest$filterCriteria' => 'An object that contains details on the filters to apply to the coverage data for your environment.
', ], ], 'CoverageMapComparison' => [ 'base' => NULL, 'refs' => [ 'CoverageMapFilter$comparison' => 'The operator to compare coverage on.
', ], ], 'CoverageMapFilter' => [ 'base' => 'Contains details of a coverage map filter.
', 'refs' => [ 'CoverageMapFilterList$member' => NULL, ], ], 'CoverageMapFilterList' => [ 'base' => NULL, 'refs' => [ 'CoverageFilterCriteria$ec2InstanceTags' => 'The Amazon EC2 instance tags to filter on.
', 'CoverageFilterCriteria$lambdaFunctionTags' => 'Returns coverage statistics for AWS Lambda functions filtered by tag.
', ], ], 'CoverageResourceType' => [ 'base' => NULL, 'refs' => [ 'CoveredResource$resourceType' => 'The type of the covered resource.
', ], ], 'CoverageStringComparison' => [ 'base' => NULL, 'refs' => [ 'CoverageStringFilter$comparison' => 'The operator to compare strings on.
', ], ], 'CoverageStringFilter' => [ 'base' => 'Contains details of a coverage string filter.
', 'refs' => [ 'CoverageStringFilterList$member' => NULL, ], ], 'CoverageStringFilterList' => [ 'base' => NULL, 'refs' => [ 'CoverageFilterCriteria$accountId' => 'An array of Amazon Web Services account IDs to return coverage statistics for.
', 'CoverageFilterCriteria$ecrImageTags' => 'The Amazon ECR image tags to filter on.
', 'CoverageFilterCriteria$ecrRepositoryName' => 'The Amazon ECR repository name to filter on.
', 'CoverageFilterCriteria$lambdaFunctionName' => 'Returns coverage statistics for AWS Lambda functions filtered by function names.
', 'CoverageFilterCriteria$lambdaFunctionRuntime' => 'Returns coverage statistics for AWS Lambda functions filtered by runtime.
', 'CoverageFilterCriteria$resourceId' => 'An array of Amazon Web Services resource IDs to return coverage statistics for.
', 'CoverageFilterCriteria$resourceType' => 'An array of Amazon Web Services resource types to return coverage statistics for. The values can be AWS_EC2_INSTANCE
, AWS_LAMBDA_FUNCTION
, AWS_ECR_CONTAINER_IMAGE
, AWS_ECR_REPOSITORY
or AWS_ACCOUNT
.
The scan status code to filter on. Valid values are: ValidationException
, InternalServerException
, ResourceNotFoundException
, BadRequestException
, and ThrottlingException
.
The scan status reason to filter on.
', 'CoverageFilterCriteria$scanType' => 'An array of Amazon Inspector scan types to return coverage statistics for.
', ], ], 'CoverageStringInput' => [ 'base' => NULL, 'refs' => [ 'CoverageStringFilter$value' => 'The value to compare strings on.
', ], ], 'CoveredResource' => [ 'base' => 'An object that contains details about a resource covered by Amazon Inspector.
', 'refs' => [ 'CoveredResources$member' => NULL, ], ], 'CoveredResources' => [ 'base' => NULL, 'refs' => [ 'ListCoverageResponse$coveredResources' => 'An object that contains details on the covered resources in your environment.
', ], ], 'CreateCisScanConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateCisScanConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateCisTargets' => [ 'base' => 'Creates CIS targets.
', 'refs' => [ 'CreateCisScanConfigurationRequest$targets' => 'The targets for the CIS scan configuration.
', ], ], 'CreateFilterRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFilterResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFindingsReportRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFindingsReportResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateSbomExportRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateSbomExportResponse' => [ 'base' => NULL, 'refs' => [], ], 'Currency' => [ 'base' => NULL, 'refs' => [ 'Usage$currency' => 'The currency type used when calculating usage data.
', ], ], 'Cvss2' => [ 'base' => 'The Common Vulnerability Scoring System (CVSS) version 2 details for the vulnerability.
', 'refs' => [ 'Vulnerability$cvss2' => 'An object that contains the Common Vulnerability Scoring System (CVSS) Version 2 details for the vulnerability.
', ], ], 'Cvss2BaseScore' => [ 'base' => NULL, 'refs' => [ 'Cvss2$baseScore' => 'The CVSS v2 base score for the vulnerability.
', ], ], 'Cvss2ScoringVector' => [ 'base' => NULL, 'refs' => [ 'Cvss2$scoringVector' => 'The scoring vector associated with the CVSS v2 score.
', ], ], 'Cvss3' => [ 'base' => 'The Common Vulnerability Scoring System (CVSS) version 3 details for the vulnerability.
', 'refs' => [ 'Vulnerability$cvss3' => 'An object that contains the Common Vulnerability Scoring System (CVSS) Version 3 details for the vulnerability.
', ], ], 'Cvss3BaseScore' => [ 'base' => NULL, 'refs' => [ 'Cvss3$baseScore' => 'The CVSS v3 base score for the vulnerability.
', ], ], 'Cvss3ScoringVector' => [ 'base' => NULL, 'refs' => [ 'Cvss3$scoringVector' => 'The scoring vector associated with the CVSS v3 score.
', ], ], 'CvssScore' => [ 'base' => 'The CVSS score for a finding.
', 'refs' => [ 'CvssScoreList$member' => NULL, ], ], 'CvssScoreAdjustment' => [ 'base' => 'Details on adjustments Amazon Inspector made to the CVSS score for a finding.
', 'refs' => [ 'CvssScoreAdjustmentList$member' => NULL, ], ], 'CvssScoreAdjustmentList' => [ 'base' => NULL, 'refs' => [ 'CvssScoreDetails$adjustments' => 'An object that contains details about adjustment Amazon Inspector made to the CVSS score.
', ], ], 'CvssScoreDetails' => [ 'base' => 'Information about the CVSS score.
', 'refs' => [ 'InspectorScoreDetails$adjustedCvss' => 'An object that contains details about the CVSS score given to a finding.
', ], ], 'CvssScoreList' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$cvss' => 'An object that contains details about the CVSS score of a finding.
', ], ], 'Cwe' => [ 'base' => NULL, 'refs' => [ 'Cwes$member' => NULL, ], ], 'CweList' => [ 'base' => NULL, 'refs' => [ 'CodeVulnerabilityDetails$cwes' => 'The Common Weakness Enumeration (CWE) item associated with the detected vulnerability.
', ], ], 'Cwes' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$cwes' => 'The Common Weakness Enumerations (CWEs) associated with the vulnerability.
', 'Vulnerability$cwes' => 'The Common Weakness Enumeration (CWE) associated with the vulnerability.
', ], ], 'DailySchedule' => [ 'base' => 'A daily schedule.
', 'refs' => [ 'Schedule$daily' => 'The schedule\'s daily.
', ], ], 'DateFilter' => [ 'base' => 'Contains details on the time range used to filter findings.
', 'refs' => [ 'DateFilterList$member' => NULL, ], ], 'DateFilterList' => [ 'base' => NULL, 'refs' => [ 'FilterCriteria$ecrImagePushedAt' => 'Details on the Amazon ECR image push date and time used to filter findings.
', 'FilterCriteria$firstObservedAt' => 'Details on the date and time a finding was first seen used to filter findings.
', 'FilterCriteria$lambdaFunctionLastModifiedAt' => 'Filters the list of AWS Lambda functions by the date and time that a user last updated the configuration, in ISO 8601 format
', 'FilterCriteria$lastObservedAt' => 'Details on the date and time a finding was last seen used to filter findings.
', 'FilterCriteria$updatedAt' => 'Details on the date and time a finding was last updated at used to filter findings.
', ], ], 'DateTimeTimestamp' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$launchedAt' => 'The date and time the Amazon EC2 instance was launched at.
', 'AwsEcrContainerImageDetails$pushedAt' => 'The date and time the Amazon ECR container image was pushed.
', 'CoverageDateFilter$endInclusive' => 'A timestamp representing the end of the time period to filter results by.
', 'CoverageDateFilter$startInclusive' => 'A timestamp representing the start of the time period to filter results by.
', 'CoveredResource$lastScannedAt' => 'The date and time the resource was last checked for vulnerabilities.
', 'EcrRescanDurationState$updatedAt' => 'A timestamp representing when the last time the ECR scan duration setting was changed.
', 'ExploitabilityDetails$lastKnownExploitAt' => 'The date and time of the last exploit associated with a finding discovered in your environment.
', 'Filter$createdAt' => 'The date and time this filter was created at.
', 'Filter$updatedAt' => 'The date and time the filter was last updated at.
', 'Finding$firstObservedAt' => 'The date and time that the finding was first observed.
', 'Finding$lastObservedAt' => 'The date and time that the finding was last observed.
', 'Finding$updatedAt' => 'The date and time the finding was last updated at.
', 'LambdaFunctionAggregationResponse$lastModifiedAt' => 'The date that the AWS Lambda function included in the aggregation results was last changed.
', 'Member$updatedAt' => 'A timestamp showing when the status of this member was last updated.
', 'PackageVulnerabilityDetails$vendorCreatedAt' => 'The date and time that this vulnerability was first added to the vendor\'s database.
', 'PackageVulnerabilityDetails$vendorUpdatedAt' => 'The date and time the vendor last updated this vulnerability in their database.
', ], ], 'Day' => [ 'base' => NULL, 'refs' => [ 'DaysList$member' => NULL, 'MonthlySchedule$day' => 'The monthly schedule\'s day.
', ], ], 'DaysList' => [ 'base' => NULL, 'refs' => [ 'WeeklySchedule$days' => 'The weekly schedule\'s days.
', ], ], 'DelegatedAdmin' => [ 'base' => 'Details of the Amazon Inspector delegated administrator for your organization.
', 'refs' => [ 'GetDelegatedAdminAccountResponse$delegatedAdmin' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator.
', ], ], 'DelegatedAdminAccount' => [ 'base' => 'Details of the Amazon Inspector delegated administrator for your organization.
', 'refs' => [ 'DelegatedAdminAccountList$member' => NULL, ], ], 'DelegatedAdminAccountList' => [ 'base' => NULL, 'refs' => [ 'ListDelegatedAdminAccountsResponse$delegatedAdminAccounts' => 'Details of the Amazon Inspector delegated administrator of your organization.
', ], ], 'DelegatedAdminStatus' => [ 'base' => NULL, 'refs' => [ 'DelegatedAdminAccount$status' => 'The status of the Amazon Inspector delegated administrator.
', ], ], 'DeleteCisScanConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteCisScanConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'DeleteFilterRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteFilterResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeOrganizationConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeOrganizationConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'Destination' => [ 'base' => 'Contains details of the Amazon S3 bucket and KMS key used to export findings.
', 'refs' => [ 'CreateFindingsReportRequest$s3Destination' => 'The Amazon S3 export destination for the report.
', 'CreateSbomExportRequest$s3Destination' => NULL, 'GetFindingsReportStatusResponse$destination' => 'The destination of the report.
', 'GetSbomExportResponse$s3Destination' => NULL, ], ], 'DetectionPlatforms' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$detectionPlatforms' => 'Platforms that the vulnerability can be detected on.
', ], ], 'DetectorTagList' => [ 'base' => NULL, 'refs' => [ 'CodeVulnerabilityDetails$detectorTags' => 'The detector tag associated with the vulnerability. Detector tags group related vulnerabilities by common themes or tactics. For a list of available tags by programming language, see Java tags, or Python tags.
', ], ], 'DisableDelegatedAdminAccountRequest' => [ 'base' => NULL, 'refs' => [], ], 'DisableDelegatedAdminAccountResponse' => [ 'base' => NULL, 'refs' => [], ], 'DisableRequest' => [ 'base' => NULL, 'refs' => [], ], 'DisableResourceTypeList' => [ 'base' => NULL, 'refs' => [ 'DisableRequest$resourceTypes' => 'The resource scan types you want to disable.
', ], ], 'DisableResponse' => [ 'base' => NULL, 'refs' => [], ], 'DisassociateMemberRequest' => [ 'base' => NULL, 'refs' => [], ], 'DisassociateMemberResponse' => [ 'base' => NULL, 'refs' => [], ], 'Double' => [ 'base' => NULL, 'refs' => [ 'CvssScore$baseScore' => 'The base CVSS score used for the finding.
', 'CvssScoreDetails$score' => 'The CVSS score.
', 'Finding$inspectorScore' => 'The Amazon Inspector score given to the finding.
', 'FindingDetail$epssScore' => 'The Exploit Prediction Scoring System (EPSS) score of the vulnerability.
', 'NumberFilter$lowerInclusive' => 'The lowest number to be included in the filter.
', 'NumberFilter$upperInclusive' => 'The highest number to be included in the filter.
', ], ], 'Ec2DeepInspectionStatus' => [ 'base' => NULL, 'refs' => [ 'GetEc2DeepInspectionConfigurationResponse$status' => 'The activation status of Amazon Inspector deep inspection in your account.
', 'MemberAccountEc2DeepInspectionStatusState$status' => 'The state of Amazon Inspector deep inspection in the member account.
', 'UpdateEc2DeepInspectionConfigurationResponse$status' => 'The status of Amazon Inspector deep inspection in your account.
', ], ], 'Ec2InstanceAggregation' => [ 'base' => 'The details that define an aggregation based on Amazon EC2 instances.
', 'refs' => [ 'AggregationRequest$ec2InstanceAggregation' => 'An object that contains details about an aggregation request based on Amazon EC2 instances.
', ], ], 'Ec2InstanceAggregationResponse' => [ 'base' => 'A response that contains the results of a finding aggregation by Amazon EC2 instance.
', 'refs' => [ 'AggregationResponse$ec2InstanceAggregation' => 'An object that contains details about an aggregation response based on Amazon EC2 instances.
', ], ], 'Ec2InstanceSortBy' => [ 'base' => NULL, 'refs' => [ 'Ec2InstanceAggregation$sortBy' => 'The value to sort results by.
', ], ], 'Ec2Metadata' => [ 'base' => 'Meta data details of an Amazon EC2 instance.
', 'refs' => [ 'ResourceScanMetadata$ec2' => 'An object that contains metadata details for an Amazon EC2 instance.
', ], ], 'Ec2Platform' => [ 'base' => NULL, 'refs' => [ 'Ec2Metadata$platform' => 'The platform of the instance.
', ], ], 'EcrConfiguration' => [ 'base' => 'Details about the ECR automated re-scan duration setting for your environment.
', 'refs' => [ 'UpdateConfigurationRequest$ecrConfiguration' => 'Specifies how the ECR automated re-scan will be updated for your environment.
', ], ], 'EcrConfigurationState' => [ 'base' => 'Details about the state of the ECR scans for your environment.
', 'refs' => [ 'GetConfigurationResponse$ecrConfiguration' => 'Specifies how the ECR automated re-scan duration is currently configured for your environment.
', ], ], 'EcrContainerImageMetadata' => [ 'base' => 'Information on the Amazon ECR image metadata associated with a finding.
', 'refs' => [ 'ResourceScanMetadata$ecrImage' => 'An object that contains details about the container metadata for an Amazon ECR image.
', ], ], 'EcrRepositoryMetadata' => [ 'base' => 'Information on the Amazon ECR repository metadata associated with a finding.
', 'refs' => [ 'ResourceScanMetadata$ecrRepository' => 'An object that contains details about the repository an Amazon ECR image resides in.
', ], ], 'EcrRescanDuration' => [ 'base' => NULL, 'refs' => [ 'EcrConfiguration$rescanDuration' => 'The ECR automated re-scan duration defines how long an ECR image will be actively scanned by Amazon Inspector. When the number of days since an image was last pushed exceeds the automated re-scan duration the monitoring state of that image becomes inactive
and all associated findings are scheduled for closure.
The ECR automated re-scan duration defines how long an ECR image will be actively scanned by Amazon Inspector. When the number of days since an image was last pushed exceeds the automated re-scan duration the monitoring state of that image becomes inactive
and all associated findings are scheduled for closure.
Details about the state of any changes to the ECR automated re-scan duration setting.
', 'refs' => [ 'EcrConfigurationState$rescanDurationState' => 'An object that contains details about the state of the ECR automated re-scan setting.
', ], ], 'EcrRescanDurationStatus' => [ 'base' => NULL, 'refs' => [ 'EcrRescanDurationState$status' => 'The status of changes to the ECR automated re-scan duration.
', ], ], 'EcrScanFrequency' => [ 'base' => NULL, 'refs' => [ 'EcrRepositoryMetadata$scanFrequency' => 'The frequency of scans.
', ], ], 'EnableDelegatedAdminAccountRequest' => [ 'base' => NULL, 'refs' => [], ], 'EnableDelegatedAdminAccountResponse' => [ 'base' => NULL, 'refs' => [], ], 'EnableRequest' => [ 'base' => NULL, 'refs' => [], ], 'EnableResourceTypeList' => [ 'base' => NULL, 'refs' => [ 'EnableRequest$resourceTypes' => 'The resource scan types you want to enable.
', ], ], 'EnableResponse' => [ 'base' => NULL, 'refs' => [], ], 'Epss' => [ 'base' => 'Details about the Exploit Prediction Scoring System (EPSS) score.
', 'refs' => [ 'Vulnerability$epss' => 'An object that contains the Exploit Prediction Scoring System (EPSS) score for a vulnerability.
', ], ], 'EpssDetails' => [ 'base' => 'Details about the Exploit Prediction Scoring System (EPSS) score for a finding.
', 'refs' => [ 'Finding$epss' => 'The finding\'s EPSS score.
', ], ], 'EpssScore' => [ 'base' => NULL, 'refs' => [ 'Epss$score' => 'The Exploit Prediction Scoring System (EPSS) score.
', ], ], 'EpssScoreValue' => [ 'base' => NULL, 'refs' => [ 'EpssDetails$score' => 'The EPSS score.
', ], ], 'ErrorCode' => [ 'base' => NULL, 'refs' => [ 'FailedAccount$errorCode' => 'The error code explaining why the account failed to enable Amazon Inspector.
', 'State$errorCode' => 'The error code explaining why the account failed to enable Amazon Inspector.
', ], ], 'ErrorMessage' => [ 'base' => NULL, 'refs' => [ 'GetFindingsReportStatusResponse$errorMessage' => 'The error message of the report.
', ], ], 'Evidence' => [ 'base' => 'Details of the evidence for a vulnerability identified in a finding.
', 'refs' => [ 'EvidenceList$member' => NULL, ], ], 'EvidenceDetail' => [ 'base' => NULL, 'refs' => [ 'Evidence$evidenceDetail' => 'The evidence details.
', ], ], 'EvidenceList' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$evidences' => 'Information on the evidence of the vulnerability.
', ], ], 'EvidenceRule' => [ 'base' => NULL, 'refs' => [ 'Evidence$evidenceRule' => 'The evidence rule.
', ], ], 'EvidenceSeverity' => [ 'base' => NULL, 'refs' => [ 'Evidence$severity' => 'The evidence severity.
', ], ], 'ExecutionRoleArn' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$executionRoleArn' => 'The AWS Lambda function\'s execution role.
', ], ], 'ExploitAvailable' => [ 'base' => NULL, 'refs' => [ 'Finding$exploitAvailable' => 'If a finding discovered in your environment has an exploit available.
', ], ], 'ExploitObserved' => [ 'base' => 'Contains information on when this exploit was observed.
', 'refs' => [ 'FindingDetail$exploitObserved' => NULL, 'Vulnerability$exploitObserved' => 'An object that contains details on when the exploit was observed.
', ], ], 'ExploitabilityDetails' => [ 'base' => 'The details of an exploit available for a finding discovered in your environment.
', 'refs' => [ 'Finding$exploitabilityDetails' => 'The details of an exploit available for a finding discovered in your environment.
', ], ], 'ExternalReportStatus' => [ 'base' => NULL, 'refs' => [ 'GetFindingsReportStatusResponse$status' => 'The status of the report.
', 'GetSbomExportResponse$status' => 'The status of the software bill of materials (SBOM) report.
', ], ], 'FailedAccount' => [ 'base' => 'An object with details on why an account failed to enable Amazon Inspector.
', 'refs' => [ 'FailedAccountList$member' => NULL, ], ], 'FailedAccountList' => [ 'base' => NULL, 'refs' => [ 'BatchGetAccountStatusResponse$failedAccounts' => 'An array of objects detailing any accounts that failed to enable Amazon Inspector and why.
', 'DisableResponse$failedAccounts' => 'Information on any accounts for which Amazon Inspector scans could not be disabled. Details are provided for each account.
', 'EnableResponse$failedAccounts' => 'Information on any accounts for which Amazon Inspector scans could not be enabled. Details are provided for each account.
', ], ], 'FailedMemberAccountEc2DeepInspectionStatusState' => [ 'base' => 'An object that contains details about a member account in your organization that failed to activate Amazon Inspector deep inspection.
', 'refs' => [ 'FailedMemberAccountEc2DeepInspectionStatusStateList$member' => NULL, ], ], 'FailedMemberAccountEc2DeepInspectionStatusStateList' => [ 'base' => NULL, 'refs' => [ 'BatchGetMemberEc2DeepInspectionStatusResponse$failedAccountIds' => 'An array of objects that provide details on any accounts that failed to activate Amazon Inspector deep inspection and why.
</p>
', 'BatchUpdateMemberEc2DeepInspectionStatusResponse$failedAccountIds' => 'An array of objects that provide details for each of the accounts that Amazon Inspector deep inspection status could not be successfully changed for.
', ], ], 'FilePath' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$filePath' => 'The file path of the vulnerable package.
', ], ], 'Filter' => [ 'base' => 'Details about a filter.
', 'refs' => [ 'FilterList$member' => NULL, ], ], 'FilterAction' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$action' => 'Defines the action that is to be applied to the findings that match the filter.
', 'Filter$action' => 'The action that is to be applied to the findings that match the filter.
', 'ListFiltersRequest$action' => 'The action the filter applies to matched findings.
', 'UpdateFilterRequest$action' => 'Specifies the action that is to be applied to the findings that match the filter.
', ], ], 'FilterArn' => [ 'base' => NULL, 'refs' => [ 'CreateFilterResponse$arn' => 'The Amazon Resource Number (ARN) of the successfully created filter.
', 'DeleteFilterRequest$arn' => 'The Amazon Resource Number (ARN) of the filter to be deleted.
', 'DeleteFilterResponse$arn' => 'The Amazon Resource Number (ARN) of the filter that has been deleted.
', 'Filter$arn' => 'The Amazon Resource Number (ARN) associated with this filter.
', 'FilterArnList$member' => NULL, 'UpdateFilterRequest$filterArn' => 'The Amazon Resource Number (ARN) of the filter to update.
', 'UpdateFilterResponse$arn' => 'The Amazon Resource Number (ARN) of the successfully updated filter.
', ], ], 'FilterArnList' => [ 'base' => NULL, 'refs' => [ 'ListFiltersRequest$arns' => 'The Amazon resource number (ARN) of the filter.
', ], ], 'FilterCriteria' => [ 'base' => 'Details on the criteria used to define the filter.
', 'refs' => [ 'CreateFilterRequest$filterCriteria' => 'Defines the criteria to be used in the filter for querying findings.
', 'CreateFindingsReportRequest$filterCriteria' => 'The filter criteria to apply to the results of the finding report.
', 'Filter$criteria' => 'Details on the filter criteria associated with this filter.
', 'GetFindingsReportStatusResponse$filterCriteria' => 'The filter criteria associated with the report.
', 'ListFindingsRequest$filterCriteria' => 'Details on the filters to apply to your finding results.
', 'UpdateFilterRequest$filterCriteria' => 'Defines the criteria to be update in the filter.
', ], ], 'FilterDescription' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$description' => 'A description of the filter.
', 'Filter$description' => 'A description of the filter.
', 'UpdateFilterRequest$description' => 'A description of the filter.
', ], ], 'FilterList' => [ 'base' => NULL, 'refs' => [ 'ListFiltersResponse$filters' => 'Contains details on the filters associated with your account.
', ], ], 'FilterName' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$name' => 'The name of the filter. Minimum length of 3. Maximum length of 64. Valid characters include alphanumeric characters, dot (.), underscore (_), and dash (-). Spaces are not allowed.
', 'Filter$name' => 'The name of the filter.
', 'UpdateFilterRequest$name' => 'The name of the filter.
', ], ], 'FilterReason' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$reason' => 'The reason for creating the filter.
', 'Filter$reason' => 'The reason for the filter.
', 'UpdateFilterRequest$reason' => 'The reason the filter was updated.
', ], ], 'Finding' => [ 'base' => 'Details about an Amazon Inspector finding.
', 'refs' => [ 'FindingList$member' => NULL, ], ], 'FindingArn' => [ 'base' => NULL, 'refs' => [ 'BatchGetCodeSnippetRequestFindingArnsList$member' => NULL, 'CodeSnippetError$findingArn' => 'The ARN of the finding that a code snippet couldn\'t be retrieved for.
', 'CodeSnippetResult$findingArn' => 'The ARN of a finding that the code snippet is associated with.
', 'Finding$findingArn' => 'The Amazon Resource Number (ARN) of the finding.
', 'FindingArnList$member' => NULL, 'FindingDetail$findingArn' => 'The finding ARN that the vulnerability details are associated with.
', 'FindingDetailsError$findingArn' => 'The finding ARN that returned an error.
', ], ], 'FindingArnList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFindingDetailsRequest$findingArns' => 'A list of finding ARNs.
', ], ], 'FindingDescription' => [ 'base' => NULL, 'refs' => [ 'Finding$description' => 'The description of the finding.
', ], ], 'FindingDetail' => [ 'base' => 'Details of the vulnerability identified in a finding.
', 'refs' => [ 'FindingDetails$member' => NULL, ], ], 'FindingDetails' => [ 'base' => NULL, 'refs' => [ 'BatchGetFindingDetailsResponse$findingDetails' => 'A finding\'s vulnerability details.
', ], ], 'FindingDetailsError' => [ 'base' => 'Details about an error encountered when trying to return vulnerability data for a finding.
', 'refs' => [ 'FindingDetailsErrorList$member' => NULL, ], ], 'FindingDetailsErrorCode' => [ 'base' => NULL, 'refs' => [ 'FindingDetailsError$errorCode' => 'The error code.
', ], ], 'FindingDetailsErrorList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFindingDetailsResponse$errors' => 'Error information for findings that details could not be returned for.
', ], ], 'FindingList' => [ 'base' => NULL, 'refs' => [ 'ListFindingsResponse$findings' => 'Contains details on the findings in your environment.
', ], ], 'FindingStatus' => [ 'base' => NULL, 'refs' => [ 'Finding$status' => 'The status of the finding.
', ], ], 'FindingTitle' => [ 'base' => NULL, 'refs' => [ 'Finding$title' => 'The title of the finding.
', ], ], 'FindingType' => [ 'base' => NULL, 'refs' => [ 'Finding$type' => 'The type of the finding. The type
value determines the valid values for resource
in your request. For more information, see Finding types in the Amazon Inspector user guide.
The details that define an aggregation based on finding type.
', 'refs' => [ 'AggregationRequest$findingTypeAggregation' => 'An object that contains details about an aggregation request based on finding types.
', ], ], 'FindingTypeAggregationResponse' => [ 'base' => 'A response that contains the results of a finding type aggregation.
', 'refs' => [ 'AggregationResponse$findingTypeAggregation' => 'An object that contains details about an aggregation response based on finding types.
', ], ], 'FindingTypeSortBy' => [ 'base' => NULL, 'refs' => [ 'FindingTypeAggregation$sortBy' => 'The value to sort results by.
', ], ], 'FirstSeen' => [ 'base' => NULL, 'refs' => [ 'AtigData$firstSeen' => 'The date and time this vulnerability was first observed.
', 'ExploitObserved$firstSeen' => 'The date an time when the exploit was first seen.
', ], ], 'FixAvailable' => [ 'base' => NULL, 'refs' => [ 'Finding$fixAvailable' => 'Details on whether a fix is available through a version update. This value can be YES
, NO
, or PARTIAL
. A PARTIAL
fix means that some, but not all, of the packages identified in the finding have fixes available through updated versions.
Information about the Amazon Inspector free trial for an account.
', 'refs' => [ 'FreeTrialAccountInfoList$member' => NULL, ], ], 'FreeTrialAccountInfoList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFreeTrialInfoResponse$accounts' => 'An array of objects that provide Amazon Inspector free trial details for each of the requested accounts.
', ], ], 'FreeTrialInfo' => [ 'base' => 'An object that contains information about the Amazon Inspector free trial for an account.
', 'refs' => [ 'FreeTrialInfoList$member' => NULL, ], ], 'FreeTrialInfoError' => [ 'base' => 'Information about an error received while accessing free trail data for an account.
', 'refs' => [ 'FreeTrialInfoErrorList$member' => NULL, ], ], 'FreeTrialInfoErrorCode' => [ 'base' => NULL, 'refs' => [ 'FreeTrialInfoError$code' => 'The error code.
', ], ], 'FreeTrialInfoErrorList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFreeTrialInfoResponse$failedAccounts' => 'An array of objects detailing any accounts that free trial data could not be returned for.
', ], ], 'FreeTrialInfoList' => [ 'base' => NULL, 'refs' => [ 'FreeTrialAccountInfo$freeTrialInfo' => 'Contains information about the Amazon Inspector free trial for an account.
', ], ], 'FreeTrialStatus' => [ 'base' => NULL, 'refs' => [ 'FreeTrialInfo$status' => 'The order to sort results by.
', ], ], 'FreeTrialType' => [ 'base' => NULL, 'refs' => [ 'FreeTrialInfo$type' => 'The type of scan covered by the Amazon Inspector free trail.
', ], ], 'FunctionName' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$functionName' => 'The name of the AWS Lambda function.
', ], ], 'GetCisScanReportRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetCisScanReportResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetCisScanResultDetailsMaxResults' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsRequest$maxResults' => 'The maximum number of CIS scan result details to be returned in a single page of results.
', ], ], 'GetCisScanResultDetailsRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetCisScanResultDetailsResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetDelegatedAdminAccountRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetDelegatedAdminAccountResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetEc2DeepInspectionConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetEc2DeepInspectionConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetEncryptionKeyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetEncryptionKeyResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetFindingsReportStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetFindingsReportStatusResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetMemberRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMemberResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetSbomExportRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetSbomExportResponse' => [ 'base' => NULL, 'refs' => [], ], 'GroupKey' => [ 'base' => NULL, 'refs' => [ 'Counts$groupKey' => 'The key associated with this group
', 'ListCoverageStatisticsRequest$groupBy' => 'The value to group the results by.
', ], ], 'ImageHash' => [ 'base' => NULL, 'refs' => [ 'AwsEcrContainerImageDetails$imageHash' => 'The image hash of the Amazon ECR container image.
', ], ], 'ImageLayerAggregation' => [ 'base' => 'The details that define an aggregation based on container image layers.
', 'refs' => [ 'AggregationRequest$imageLayerAggregation' => 'An object that contains details about an aggregation request based on container image layers.
', ], ], 'ImageLayerAggregationResponse' => [ 'base' => 'A response that contains the results of a finding aggregation by image layer.
', 'refs' => [ 'AggregationResponse$imageLayerAggregation' => 'An object that contains details about an aggregation response based on container image layers.
', ], ], 'ImageLayerSortBy' => [ 'base' => NULL, 'refs' => [ 'ImageLayerAggregation$sortBy' => 'The value to sort results by.
', ], ], 'ImageTagList' => [ 'base' => NULL, 'refs' => [ 'AwsEcrContainerImageDetails$imageTags' => 'The image tags attached to the Amazon ECR container image.
', ], ], 'InspectorScoreDetails' => [ 'base' => 'Information about the Amazon Inspector score given to a finding.
', 'refs' => [ 'Finding$inspectorScoreDetails' => 'An object that contains details of the Amazon Inspector score.
', ], ], 'Integer' => [ 'base' => NULL, 'refs' => [ 'CisNumberFilter$lowerInclusive' => 'The CIS number filter\'s lower inclusive.
', 'CisNumberFilter$upperInclusive' => 'The CIS number filter\'s upper inclusive.
', 'CisScan$failedChecks' => 'The CIS scan\'s failed checks.
', 'CisScan$totalChecks' => 'The CIS scan\'s total checks.
', 'CodeFilePath$endLine' => 'The line number of the last line of code that a vulnerability was found in.
', 'CodeFilePath$startLine' => 'The line number of the first line of code that a vulnerability was found in.
', 'CodeLine$lineNumber' => 'The line number that a section of code is located at.
', 'CodeSnippetResult$endLine' => 'The line number of the last line of a code snippet.
', 'CodeSnippetResult$startLine' => 'The line number of the first line of a code snippet.
', 'InternalServerException$retryAfterSeconds' => 'The number of seconds to wait before retrying the request.
', 'StatusCounts$failed' => 'The number of checks that failed.
', 'StatusCounts$passed' => 'The number of checks that passed.
', 'StatusCounts$skipped' => 'The number of checks that were skipped.
', 'ThrottlingException$retryAfterSeconds' => 'The number of seconds to wait before retrying the request.
', ], ], 'InternalServerException' => [ 'base' => 'The request has failed due to an internal failure of the Amazon Inspector service.
', 'refs' => [], ], 'IpV4Address' => [ 'base' => NULL, 'refs' => [ 'IpV4AddressList$member' => NULL, ], ], 'IpV4AddressList' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$ipV4Addresses' => 'The IPv4 addresses of the Amazon EC2 instance.
', ], ], 'IpV6Address' => [ 'base' => NULL, 'refs' => [ 'IpV6AddressList$member' => NULL, ], ], 'IpV6AddressList' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$ipV6Addresses' => 'The IPv6 addresses of the Amazon EC2 instance.
', ], ], 'KmsKeyArn' => [ 'base' => NULL, 'refs' => [ 'GetEncryptionKeyResponse$kmsKeyId' => 'A kms key ID.
', 'UpdateEncryptionKeyRequest$kmsKeyId' => 'A KMS key ID for the encryption key.
', ], ], 'LambdaFunctionAggregation' => [ 'base' => 'The details that define a findings aggregation based on AWS Lambda functions.
', 'refs' => [ 'AggregationRequest$lambdaFunctionAggregation' => 'Returns an object with findings aggregated by AWS Lambda function.
', ], ], 'LambdaFunctionAggregationResponse' => [ 'base' => 'A response that contains the results of an AWS Lambda function finding aggregation.
', 'refs' => [ 'AggregationResponse$lambdaFunctionAggregation' => 'An aggregation of findings by AWS Lambda function.
', ], ], 'LambdaFunctionMetadata' => [ 'base' => 'The AWS Lambda function metadata.
', 'refs' => [ 'ResourceScanMetadata$lambdaFunction' => 'An object that contains metadata details for an AWS Lambda function.
', ], ], 'LambdaFunctionSortBy' => [ 'base' => NULL, 'refs' => [ 'LambdaFunctionAggregation$sortBy' => 'The finding severity to use for sorting the results.
', ], ], 'LambdaLayerAggregation' => [ 'base' => 'The details that define a findings aggregation based on an AWS Lambda function\'s layers.
', 'refs' => [ 'AggregationRequest$lambdaLayerAggregation' => 'Returns an object with findings aggregated by AWS Lambda layer.
', ], ], 'LambdaLayerAggregationResponse' => [ 'base' => 'A response that contains the results of an AWS Lambda function layer finding aggregation.
', 'refs' => [ 'AggregationResponse$lambdaLayerAggregation' => 'An aggregation of findings by AWS Lambda layer.
', ], ], 'LambdaLayerArn' => [ 'base' => NULL, 'refs' => [ 'CodeVulnerabilityDetails$sourceLambdaLayerArn' => 'The Amazon Resource Name (ARN) of the Lambda layer that the code vulnerability was detected in.
', 'LayerList$member' => NULL, 'VulnerablePackage$sourceLambdaLayerArn' => 'The Amazon Resource Number (ARN) of the AWS Lambda function affected by a finding.
', ], ], 'LambdaLayerList' => [ 'base' => NULL, 'refs' => [ 'LambdaFunctionMetadata$layers' => 'The layers for an AWS Lambda function. A Lambda function can have up to five layers.
', ], ], 'LambdaLayerSortBy' => [ 'base' => NULL, 'refs' => [ 'LambdaLayerAggregation$sortBy' => 'The finding severity to use for sorting the results.
', ], ], 'LambdaVpcConfig' => [ 'base' => 'The VPC security groups and subnets that are attached to an AWS Lambda function. For more information, see VPC Settings.
', 'refs' => [ 'AwsLambdaFunctionDetails$vpcConfig' => 'The AWS Lambda function\'s networking configuration.
', ], ], 'LastSeen' => [ 'base' => NULL, 'refs' => [ 'AtigData$lastSeen' => 'The date and time this vulnerability was last observed.
', 'ExploitObserved$lastSeen' => 'The date an time when the exploit was last seen.
', ], ], 'LayerList' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$layers' => 'The AWS Lambda function\'s layers. A Lambda function can have up to five layers.
', ], ], 'ListAccountPermissionsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListAccountPermissionsRequest$maxResults' => 'The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
A list of CIS scan configurations filter criteria.
', 'refs' => [ 'ListCisScanConfigurationsRequest$filterCriteria' => 'The CIS scan configuration filter criteria.
', ], ], 'ListCisScanConfigurationsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsRequest$maxResults' => 'The maximum number of CIS scan configurations to be returned in a single page of results.
', ], ], 'ListCisScanConfigurationsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanConfigurationsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanResultsAggregatedByChecksRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanResultsAggregatedByChecksResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanResultsAggregatedByTargetResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanResultsAggregatedByTargetResourceResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScansDetailLevel' => [ 'base' => NULL, 'refs' => [ 'ListCisScansRequest$detailLevel' => 'The detail applied to the CIS scan.
', ], ], 'ListCisScansFilterCriteria' => [ 'base' => 'A list of CIS scans filter criteria.
', 'refs' => [ 'ListCisScansRequest$filterCriteria' => 'The CIS scan filter criteria.
', ], ], 'ListCisScansMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListCisScansRequest$maxResults' => 'The maximum number of results to be returned.
', ], ], 'ListCisScansRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScansResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScansSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCisScansRequest$sortBy' => 'The CIS scans sort by order.
', ], ], 'ListCoverageMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListCoverageRequest$maxResults' => 'The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
The pagination parameter to be used on the next list operation to retrieve more items.
', ], ], 'ListUsageTotalsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListUsageTotalsResponse' => [ 'base' => NULL, 'refs' => [], ], 'Long' => [ 'base' => NULL, 'refs' => [ 'AmiAggregationResponse$affectedInstances' => 'The IDs of Amazon EC2 instances using this AMI.
', 'Ec2InstanceAggregationResponse$networkFindings' => 'The number of network findings for the Amazon EC2 instance.
', 'ListCoverageStatisticsResponse$totalCounts' => 'The total number for all groups.
', 'RepositoryAggregationResponse$affectedImages' => 'The number of container images impacted by the findings.
', 'SeverityCounts$all' => 'The total count of findings from all severities.
', 'SeverityCounts$critical' => 'The total count of critical severity findings.
', 'SeverityCounts$high' => 'The total count of high severity findings.
', 'SeverityCounts$medium' => 'The total count of medium severity findings.
', ], ], 'MapComparison' => [ 'base' => NULL, 'refs' => [ 'MapFilter$comparison' => 'The operator to use when comparing values in the filter.
', ], ], 'MapFilter' => [ 'base' => 'An object that describes details of a map filter.
', 'refs' => [ 'MapFilterList$member' => NULL, ], ], 'MapFilterList' => [ 'base' => NULL, 'refs' => [ 'Ec2InstanceAggregation$instanceTags' => 'The Amazon EC2 instance tags to aggregate findings for.
', 'FilterCriteria$resourceTags' => 'Details on the resource tags used to filter findings.
', 'LambdaFunctionAggregation$functionTags' => 'The tags to include in the aggregation results.
', ], ], 'MapKey' => [ 'base' => NULL, 'refs' => [ 'CisTagMap$key' => NULL, 'MapFilter$key' => 'The tag key used in the filter.
', 'TagMap$key' => NULL, ], ], 'MapValue' => [ 'base' => NULL, 'refs' => [ 'CisTagMap$value' => NULL, 'MapFilter$value' => 'The tag value used in the filter.
', 'TagMap$value' => NULL, ], ], 'Member' => [ 'base' => 'Details on a member account in your organization.
', 'refs' => [ 'GetMemberResponse$member' => 'Details of the retrieved member account.
', 'MemberList$member' => NULL, ], ], 'MemberAccountEc2DeepInspectionStatus' => [ 'base' => 'An object that contains details about the status of Amazon Inspector deep inspection for a member account in your organization.
', 'refs' => [ 'MemberAccountEc2DeepInspectionStatusList$member' => NULL, ], ], 'MemberAccountEc2DeepInspectionStatusList' => [ 'base' => NULL, 'refs' => [ 'BatchUpdateMemberEc2DeepInspectionStatusRequest$accountIds' => 'The unique identifiers for the Amazon Web Services accounts to change Amazon Inspector deep inspection status for.
', ], ], 'MemberAccountEc2DeepInspectionStatusState' => [ 'base' => 'An object that contains details about the state of Amazon Inspector deep inspection for a member account.
', 'refs' => [ 'MemberAccountEc2DeepInspectionStatusStateList$member' => NULL, ], ], 'MemberAccountEc2DeepInspectionStatusStateList' => [ 'base' => NULL, 'refs' => [ 'BatchGetMemberEc2DeepInspectionStatusResponse$accountIds' => 'An array of objects that provide details on the activation status of Amazon Inspector deep inspection for each of the requested accounts.
</p>
', 'BatchUpdateMemberEc2DeepInspectionStatusResponse$accountIds' => 'An array of objects that provide details for each of the accounts that Amazon Inspector deep inspection status was successfully changed for.
', ], ], 'MemberList' => [ 'base' => NULL, 'refs' => [ 'ListMembersResponse$members' => 'An object that contains details for each member account.
', ], ], 'MeteringAccountId' => [ 'base' => NULL, 'refs' => [ 'BatchGetFreeTrialInfoRequestAccountIdsList$member' => NULL, 'FreeTrialAccountInfo$accountId' => 'The account associated with the Amazon Inspector free trial information.
', 'FreeTrialInfoError$accountId' => 'The account associated with the Amazon Inspector free trial information.
', 'UsageTotal$accountId' => 'The account ID of the account that usage data was retrieved for.
', ], ], 'MonthlyCostEstimate' => [ 'base' => NULL, 'refs' => [ 'Usage$estimatedMonthlyCost' => 'The estimated monthly cost of Amazon Inspector.
', ], ], 'MonthlySchedule' => [ 'base' => 'A monthly schedule.
', 'refs' => [ 'Schedule$monthly' => 'The schedule\'s monthly.
', ], ], 'NetworkPath' => [ 'base' => 'Information on the network path associated with a finding.
', 'refs' => [ 'NetworkReachabilityDetails$networkPath' => 'An object that contains details about a network path associated with a finding.
', ], ], 'NetworkProtocol' => [ 'base' => NULL, 'refs' => [ 'NetworkReachabilityDetails$protocol' => 'The protocol associated with a finding.
', ], ], 'NetworkReachabilityDetails' => [ 'base' => 'Contains the details of a network reachability finding.
', 'refs' => [ 'Finding$networkReachabilityDetails' => 'An object that contains the details of a network reachability finding.
', ], ], 'NextToken' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsRequest$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'GetCisScanResultDetailsResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListAccountPermissionsRequest$nextToken' => 'A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the NextToken value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanConfigurationsResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanResultsAggregatedByChecksRequest$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanResultsAggregatedByChecksResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanResultsAggregatedByTargetResourceRequest$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanResultsAggregatedByTargetResourceResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScansRequest$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScansResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCoverageRequest$nextToken' => 'A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
The pagination parameter to be used on the next list operation to retrieve more items.
', 'SearchVulnerabilitiesRequest$nextToken' => 'A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
The pagination parameter to be used on the next list operation to retrieve more items.
', ], ], 'NonEmptyString' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$iamInstanceProfileArn' => 'The IAM instance profile ARN of the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$imageId' => 'The image ID of the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$keyName' => 'The name of the key pair used to launch the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$subnetId' => 'The subnet ID of the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$type' => 'The type of the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$vpcId' => 'The VPC ID of the Amazon EC2 instance.
', 'AwsEcrContainerAggregationResponse$resourceId' => 'The resource ID of the container.
', 'AwsEcrContainerImageDetails$architecture' => 'The architecture of the Amazon ECR container image.
', 'AwsEcrContainerImageDetails$registry' => 'The registry for the Amazon ECR container image.
', 'AwsEcrContainerImageDetails$repositoryName' => 'The name of the repository the Amazon ECR container image resides in.
', 'AwsLambdaFunctionDetails$codeSha256' => 'The SHA256 hash of the AWS Lambda function\'s deployment package.
', 'CodeFilePath$fileName' => 'The name of the file the code vulnerability was found in.
', 'CodeFilePath$filePath' => 'The file path to the code that a vulnerability was found in.
', 'CodeSnippetError$errorMessage' => 'The error message received when Amazon Inspector failed to retrieve a code snippet.
', 'CodeVulnerabilityDetails$detectorId' => 'The ID for the Amazon CodeGuru detector associated with the finding. For more information on detectors see Amazon CodeGuru Detector Library.
', 'CodeVulnerabilityDetails$detectorName' => 'The name of the detector used to identify the code vulnerability. For more information on detectors see CodeGuru Detector Library.
', 'CodeVulnerabilityDetails$ruleId' => 'The identifier for a rule that was used to detect the code vulnerability.
', 'CoverageMapFilter$key' => 'The tag key associated with the coverage map filter.
', 'CoverageMapFilter$value' => 'The tag value associated with the coverage map filter.
', 'CvssScore$scoringVector' => 'The vector string of the CVSS score.
', 'CvssScore$source' => 'The source of the CVSS score.
', 'CvssScore$version' => 'The version of CVSS used for the score.
', 'CvssScoreAdjustment$metric' => 'The metric used to adjust the CVSS score.
', 'CvssScoreAdjustment$reason' => 'The reason the CVSS score has been adjustment.
', 'CvssScoreDetails$cvssSource' => 'The source of the CVSS data.
', 'CvssScoreDetails$scoreSource' => 'The source for the CVSS score.
', 'CvssScoreDetails$scoringVector' => 'The vector for the CVSS score.
', 'CvssScoreDetails$version' => 'The CVSS version used in scoring.
', 'CweList$member' => NULL, 'DetectionPlatforms$member' => NULL, 'DetectorTagList$member' => NULL, 'Ec2InstanceAggregationResponse$instanceId' => 'The Amazon EC2 instance ID.
', 'FailedAccount$errorMessage' => 'The error message received when the account failed to enable Amazon Inspector.
', 'FailedMemberAccountEc2DeepInspectionStatusState$errorMessage' => 'The error message explaining why the account failed to activate Amazon Inspector deep inspection.
', 'FindingDetailsError$errorMessage' => 'The error message.
', 'GetEc2DeepInspectionConfigurationResponse$errorMessage' => 'An error message explaining why Amazon Inspector deep inspection configurations could not be retrieved for your account.
', 'GetSbomExportResponse$errorMessage' => 'An error message.
', 'ImageLayerAggregationResponse$layerHash' => 'The layer hash.
', 'ImageLayerAggregationResponse$repository' => 'The repository the layer resides in.
', 'ImageLayerAggregationResponse$resourceId' => 'The resource ID of the container image layer.
', 'ImageTagList$member' => NULL, 'LambdaFunctionAggregationResponse$resourceId' => 'The resource IDs included in the aggregation results.
', 'LambdaLayerAggregationResponse$functionName' => 'The names of the AWS Lambda functions associated with the layers.
', 'LambdaLayerAggregationResponse$layerArn' => 'The Amazon Resource Name (ARN) of the AWS Lambda function layer.
', 'LambdaLayerAggregationResponse$resourceId' => 'The Resource ID of the AWS Lambda function layer.
', 'MemberAccountEc2DeepInspectionStatusState$errorMessage' => 'The error message explaining why the account failed to activate Amazon Inspector deep inspection.
', 'NonEmptyStringList$member' => NULL, 'PackageAggregationResponse$packageName' => 'The name of the operating system package.
', 'PackageVulnerabilityDetails$source' => 'The source of the vulnerability information.
', 'PackageVulnerabilityDetails$sourceUrl' => 'A URL to the source of the vulnerability information.
', 'PackageVulnerabilityDetails$vendorSeverity' => 'The severity the vendor has given to this vulnerability type.
', 'Recommendation$Url' => 'The URL address to the CVE remediation recommendations.
', 'Recommendation$text' => 'The recommended course of action to remediate the finding.
', 'ReferenceUrls$member' => NULL, 'RepositoryAggregationResponse$repository' => 'The name of the repository associated with the findings.
', 'Resource$id' => 'The ID of the resource.
', 'Resource$partition' => 'The partition of the resource.
', 'Resource$region' => 'The Amazon Web Services Region the impacted resource is located in.
', 'ResourceMapFilter$key' => 'The filter\'s key.
', 'ResourceMapFilter$value' => 'The filter\'s value.
', 'State$errorMessage' => 'The error message received when the account failed to enable Amazon Inspector.
', 'StringList$member' => NULL, 'TagFilter$key' => 'The tag filter key.
', 'TagFilter$value' => 'The tag filter value.
', 'TargetResourceTags$key' => NULL, 'TitleAggregationResponse$title' => 'The title that the findings were aggregated on.
', 'UpdateEc2DeepInspectionConfigurationResponse$errorMessage' => 'An error message explaining why new Amazon Inspector deep inspection custom paths could not be added.
', 'Vulnerability$id' => 'The ID for the specific vulnerability.
', ], ], 'NonEmptyStringList' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$referenceUrls' => 'One or more URLs that contain details about this vulnerability type.
', ], ], 'NumberFilter' => [ 'base' => 'An object that describes the details of a number filter.
', 'refs' => [ 'NumberFilterList$member' => NULL, 'PackageFilter$epoch' => 'An object that contains details on the package epoch to filter on.
', ], ], 'NumberFilterList' => [ 'base' => NULL, 'refs' => [ 'FilterCriteria$epssScore' => 'The EPSS score used to filter findings.
', 'FilterCriteria$inspectorScore' => 'The Amazon Inspector score to filter on.
', ], ], 'OneAccountIdFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByChecksFilterCriteria$accountIdFilters' => 'The criteria\'s account ID filters.
', ], ], 'OneTimeSchedule' => [ 'base' => 'A one time schedule.
', 'refs' => [ 'Schedule$oneTime' => 'The schedule\'s one time.
', ], ], 'Operation' => [ 'base' => NULL, 'refs' => [ 'Permission$operation' => 'The operations that can be performed with the given permissions.
', ], ], 'OwnerId' => [ 'base' => NULL, 'refs' => [ 'Filter$ownerId' => 'The Amazon Web Services account ID of the account that created the filter.
', ], ], 'PackageAggregation' => [ 'base' => 'The details that define an aggregation based on operating system package type.
', 'refs' => [ 'AggregationRequest$packageAggregation' => 'An object that contains details about an aggregation request based on operating system package type.
', ], ], 'PackageAggregationResponse' => [ 'base' => 'A response that contains the results of a finding aggregation by image layer.
', 'refs' => [ 'AggregationResponse$packageAggregation' => 'An object that contains details about an aggregation response based on operating system package type.
', ], ], 'PackageArchitecture' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$arch' => 'The architecture of the vulnerable package.
', ], ], 'PackageEpoch' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$epoch' => 'The epoch of the vulnerable package.
', ], ], 'PackageFilter' => [ 'base' => 'Contains information on the details of a package filter.
', 'refs' => [ 'PackageFilterList$member' => NULL, ], ], 'PackageFilterList' => [ 'base' => NULL, 'refs' => [ 'FilterCriteria$vulnerablePackages' => 'Details on the vulnerable packages used to filter findings.
', ], ], 'PackageManager' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$packageManager' => 'The package manager of the vulnerable package.
', ], ], 'PackageName' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$name' => 'The name of the vulnerable package.
', ], ], 'PackageRelease' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$release' => 'The release of the vulnerable package.
', ], ], 'PackageSortBy' => [ 'base' => NULL, 'refs' => [ 'PackageAggregation$sortBy' => 'The value to sort results by.
', ], ], 'PackageType' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$packageType' => 'The type of deployment package. Set to Image
for container image and set Zip
for .zip file archive.
The version of the package that contains the vulnerability fix.
', 'VulnerablePackage$version' => 'The version of the vulnerable package.
', ], ], 'PackageVulnerabilityDetails' => [ 'base' => 'Information about a package vulnerability finding.
', 'refs' => [ 'Finding$packageVulnerabilityDetails' => 'An object that contains the details of a package vulnerability finding.
', ], ], 'Path' => [ 'base' => NULL, 'refs' => [ 'PathList$member' => NULL, ], ], 'PathList' => [ 'base' => NULL, 'refs' => [ 'GetEc2DeepInspectionConfigurationResponse$orgPackagePaths' => 'The Amazon Inspector deep inspection custom paths for your organization.
', 'GetEc2DeepInspectionConfigurationResponse$packagePaths' => 'The Amazon Inspector deep inspection custom paths for your account.
', 'UpdateEc2DeepInspectionConfigurationRequest$packagePaths' => 'The Amazon Inspector deep inspection custom paths you are adding for your account.
', 'UpdateEc2DeepInspectionConfigurationResponse$orgPackagePaths' => 'The current Amazon Inspector deep inspection custom paths for the organization.
', 'UpdateEc2DeepInspectionConfigurationResponse$packagePaths' => 'The current Amazon Inspector deep inspection custom paths for your account.
', 'UpdateOrgEc2DeepInspectionConfigurationRequest$orgPackagePaths' => 'The Amazon Inspector deep inspection custom paths you are adding for your organization.
', ], ], 'Permission' => [ 'base' => 'Contains information on the permissions an account has within Amazon Inspector.
', 'refs' => [ 'Permissions$member' => NULL, ], ], 'Permissions' => [ 'base' => NULL, 'refs' => [ 'ListAccountPermissionsResponse$permissions' => 'Contains details on the permissions an account has to configure Amazon Inspector.
', ], ], 'Platform' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$platform' => 'The platform of the Amazon EC2 instance.
', 'AwsEcrContainerImageDetails$platform' => 'The platform of the Amazon ECR container image.
', ], ], 'PlatformFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByChecksFilterCriteria$platformFilters' => 'The criteria\'s platform filters.
', 'CisScanResultsAggregatedByTargetResourceFilterCriteria$platformFilters' => 'The criteria\'s platform filters.
', ], ], 'PlatformVersion' => [ 'base' => NULL, 'refs' => [ 'ComputePlatform$version' => 'The compute platform version.
', ], ], 'Port' => [ 'base' => NULL, 'refs' => [ 'PortRange$begin' => 'The beginning port in a port range.
', 'PortRange$end' => 'The ending port in a port range.
', 'PortRangeFilter$beginInclusive' => 'The port number the port range begins at.
', 'PortRangeFilter$endInclusive' => 'The port number the port range ends at.
', ], ], 'PortRange' => [ 'base' => 'Details about the port range associated with a finding.
', 'refs' => [ 'NetworkReachabilityDetails$openPortRange' => 'An object that contains details about the open port range associated with a finding.
', ], ], 'PortRangeFilter' => [ 'base' => 'An object that describes the details of a port range filter.
', 'refs' => [ 'PortRangeFilterList$member' => NULL, ], ], 'PortRangeFilterList' => [ 'base' => NULL, 'refs' => [ 'FilterCriteria$portRange' => 'Details on the port ranges used to filter findings.
', ], ], 'Product' => [ 'base' => NULL, 'refs' => [ 'ComputePlatform$product' => 'The compute platform product.
', ], ], 'Reason' => [ 'base' => NULL, 'refs' => [ 'StopCisSessionMessage$reason' => 'The reason for the message.
', ], ], 'Recommendation' => [ 'base' => 'Details about the recommended course of action to remediate the finding.
', 'refs' => [ 'Remediation$recommendation' => 'An object that contains information about the recommended course of action to remediate the finding.
', ], ], 'ReferenceUrls' => [ 'base' => NULL, 'refs' => [ 'CodeVulnerabilityDetails$referenceUrls' => 'A URL containing supporting documentation about the code vulnerability detected.
', ], ], 'RelatedVulnerabilities' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$relatedVulnerabilities' => 'A list of related vulnerabilities.
', ], ], 'RelatedVulnerability' => [ 'base' => NULL, 'refs' => [ 'RelatedVulnerabilities$member' => NULL, ], ], 'RelationshipStatus' => [ 'base' => NULL, 'refs' => [ 'DelegatedAdmin$relationshipStatus' => 'The status of the Amazon Inspector delegated administrator.
', 'Member$relationshipStatus' => 'The status of the member account.
', ], ], 'Remediation' => [ 'base' => 'Information on how to remediate a finding.
', 'refs' => [ 'Finding$remediation' => 'An object that contains the details about how to remediate a finding.
', ], ], 'ReportFormat' => [ 'base' => NULL, 'refs' => [ 'CreateFindingsReportRequest$reportFormat' => 'The format to generate the report in.
', ], ], 'ReportId' => [ 'base' => NULL, 'refs' => [ 'CancelFindingsReportRequest$reportId' => 'The ID of the report to be canceled.
', 'CancelFindingsReportResponse$reportId' => 'The ID of the canceled report.
', 'CancelSbomExportRequest$reportId' => 'The report ID of the SBOM export to cancel.
', 'CancelSbomExportResponse$reportId' => 'The report ID of the canceled SBOM export.
', 'CreateFindingsReportResponse$reportId' => 'The ID of the report.
', 'CreateSbomExportResponse$reportId' => 'The report ID for the software bill of materials (SBOM) report.
', 'GetFindingsReportStatusRequest$reportId' => 'The ID of the report to retrieve the status of.
', 'GetFindingsReportStatusResponse$reportId' => 'The ID of the report.
', 'GetSbomExportRequest$reportId' => 'The report ID of the SBOM export to get details for.
', 'GetSbomExportResponse$reportId' => 'The report ID of the software bill of materials (SBOM) report.
', ], ], 'ReportTargetAccounts' => [ 'base' => NULL, 'refs' => [ 'GetCisScanReportRequest$targetAccounts' => 'The target accounts.
', ], ], 'ReportingErrorCode' => [ 'base' => NULL, 'refs' => [ 'GetFindingsReportStatusResponse$errorCode' => 'The error code of the report.
', 'GetSbomExportResponse$errorCode' => 'An error code.
', ], ], 'RepositoryAggregation' => [ 'base' => 'The details that define an aggregation based on repository.
', 'refs' => [ 'AggregationRequest$repositoryAggregation' => 'An object that contains details about an aggregation request based on Amazon ECR repositories.
', ], ], 'RepositoryAggregationResponse' => [ 'base' => 'A response that contains details on the results of a finding aggregation by repository.
', 'refs' => [ 'AggregationResponse$repositoryAggregation' => 'An object that contains details about an aggregation response based on Amazon ECR repositories.
', ], ], 'RepositorySortBy' => [ 'base' => NULL, 'refs' => [ 'RepositoryAggregation$sortBy' => 'The value to sort results by.
', ], ], 'ResetEncryptionKeyRequest' => [ 'base' => NULL, 'refs' => [], ], 'ResetEncryptionKeyResponse' => [ 'base' => NULL, 'refs' => [], ], 'Resource' => [ 'base' => 'Details about the resource involved in a finding.
', 'refs' => [ 'ResourceList$member' => NULL, ], ], 'ResourceDetails' => [ 'base' => 'Contains details about the resource involved in the finding.
', 'refs' => [ 'Resource$details' => 'An object that contains details about the resource involved in a finding.
', ], ], 'ResourceFilterCriteria' => [ 'base' => 'The resource filter criteria for a Software bill of materials (SBOM) report.
', 'refs' => [ 'CreateSbomExportRequest$resourceFilterCriteria' => 'The resource filter criteria for the software bill of materials (SBOM) report.
', 'GetSbomExportResponse$filterCriteria' => 'Contains details about the resource filter criteria used for the software bill of materials (SBOM) report.
', ], ], 'ResourceId' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetails$targetResourceId' => 'The CIS scan result details\' target resource ID.
', 'CisTargetResourceAggregation$targetResourceId' => 'The ID of the target resource.
', 'CoveredResource$resourceId' => 'The ID of the covered resource.
', 'GetCisScanResultDetailsRequest$targetResourceId' => 'The target resource ID.
', ], ], 'ResourceIdFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$targetResourceIdFilters' => 'The criteria\'s target resource ID filters.
', 'ListCisScansFilterCriteria$targetResourceIdFilters' => 'The list of target resource ID filters.
', ], ], 'ResourceList' => [ 'base' => NULL, 'refs' => [ 'Finding$resources' => 'Contains information on the resources involved in a finding. The resource
value determines the valid values for type
in your request. For more information, see Finding types in the Amazon Inspector user guide.
The filter\'s comparison.
', ], ], 'ResourceMapFilter' => [ 'base' => 'A resource map filter for a software bill of material report.
', 'refs' => [ 'ResourceMapFilterList$member' => NULL, ], ], 'ResourceMapFilterList' => [ 'base' => NULL, 'refs' => [ 'ResourceFilterCriteria$ec2InstanceTags' => 'The EC2 instance tags used as resource filter criteria.
', 'ResourceFilterCriteria$lambdaFunctionTags' => 'The AWS Lambda function tags used as resource filter criteria.
', ], ], 'ResourceNotFoundException' => [ 'base' => 'The operation tried to access an invalid resource. Make sure the resource is specified correctly.
', 'refs' => [], ], 'ResourceScanMetadata' => [ 'base' => 'An object that contains details about the metadata for an Amazon ECR resource.
', 'refs' => [ 'CoveredResource$resourceMetadata' => 'An object that contains details about the metadata.
', ], ], 'ResourceScanType' => [ 'base' => NULL, 'refs' => [ 'DisableResourceTypeList$member' => NULL, 'EnableResourceTypeList$member' => NULL, ], ], 'ResourceState' => [ 'base' => 'Details the state of Amazon Inspector for each resource type Amazon Inspector scans.
', 'refs' => [ 'AccountState$resourceState' => 'An object detailing which resources Amazon Inspector is enabled to scan for the account.
', ], ], 'ResourceStatus' => [ 'base' => 'Details the status of Amazon Inspector for each resource type Amazon Inspector scans.
', 'refs' => [ 'Account$resourceStatus' => 'Details of the status of Amazon Inspector scans by resource type.
', 'FailedAccount$resourceStatus' => 'An object detailing which resources Amazon Inspector is enabled to scan for the account.
', ], ], 'ResourceStringComparison' => [ 'base' => NULL, 'refs' => [ 'ResourceStringFilter$comparison' => 'The filter\'s comparison.
', ], ], 'ResourceStringFilter' => [ 'base' => 'A resource string filter for a software bill of materials report.
', 'refs' => [ 'ResourceStringFilterList$member' => NULL, ], ], 'ResourceStringFilterList' => [ 'base' => NULL, 'refs' => [ 'ResourceFilterCriteria$accountId' => 'The account IDs used as resource filter criteria.
', 'ResourceFilterCriteria$ecrImageTags' => 'The ECR image tags used as resource filter criteria.
', 'ResourceFilterCriteria$ecrRepositoryName' => 'The ECR repository names used as resource filter criteria.
', 'ResourceFilterCriteria$lambdaFunctionName' => 'The AWS Lambda function name used as resource filter criteria.
', 'ResourceFilterCriteria$resourceId' => 'The resource IDs used as resource filter criteria.
', 'ResourceFilterCriteria$resourceType' => 'The resource types used as resource filter criteria.
', ], ], 'ResourceStringInput' => [ 'base' => NULL, 'refs' => [ 'ResourceStringFilter$value' => 'The filter\'s value.
', ], ], 'ResourceTagFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$targetResourceTagFilters' => 'The criteria\'s target resource tag filters.
', 'ListCisScanConfigurationsFilterCriteria$targetResourceTagFilters' => 'The list of target resource tag filters.
', 'ListCisScansFilterCriteria$targetResourceTagFilters' => 'The list of target resource tag filters.
', ], ], 'ResourceType' => [ 'base' => NULL, 'refs' => [ 'GetEncryptionKeyRequest$resourceType' => 'The resource type the key encrypts.
', 'ResetEncryptionKeyRequest$resourceType' => 'The resource type the key encrypts.
', 'Resource$type' => 'The type of resource.
', 'UpdateEncryptionKeyRequest$resourceType' => 'The resource type for the encryption key.
', ], ], 'RiskScore' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$riskScore' => 'The risk score of the vulnerability.
', ], ], 'RuleId' => [ 'base' => NULL, 'refs' => [ 'CisSessionMessage$ruleId' => 'The rule ID for the CIS session message.
', ], ], 'Runtime' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$runtime' => 'The runtime environment for the AWS Lambda function.
', 'LambdaFunctionMetadata$runtime' => 'An AWS Lambda function\'s runtime.
', ], ], 'SbomReportFormat' => [ 'base' => NULL, 'refs' => [ 'CreateSbomExportRequest$reportFormat' => 'The output format for the software bill of materials (SBOM) report.
', 'GetSbomExportResponse$format' => 'The format of the software bill of materials (SBOM) report.
', ], ], 'ScanStatus' => [ 'base' => 'The status of the scan.
', 'refs' => [ 'CoveredResource$scanStatus' => 'The status of the scan covering the resource.
', ], ], 'ScanStatusCode' => [ 'base' => NULL, 'refs' => [ 'ScanStatus$statusCode' => 'The status code of the scan.
', ], ], 'ScanStatusReason' => [ 'base' => NULL, 'refs' => [ 'ScanStatus$reason' => 'The scan status. Possible return values and descriptions are:
PENDING_INITIAL_SCAN
- This resource has been identified for scanning, results will be available soon.
ACCESS_DENIED
- Resource access policy restricting Amazon Inspector access. Please update the IAM policy.
INTERNAL_ERROR
- Amazon Inspector has encountered an internal error for this resource. Amazon Inspector service will automatically resolve the issue and resume the scanning. No action required from the user.
UNMANAGED_EC2_INSTANCE
- The EC2 instance is not managed by SSM, please use the following SSM automation to remediate the issue: https://docs.aws.amazon.com/systems-manager-automation-runbooks/latest/userguide/automation-awssupport-troubleshoot-managed-instance.html. Once the instance becomes managed by SSM, Inspector will automatically begin scanning this instance.
UNSUPPORTED_OS
- Amazon Inspector does not support this OS, architecture, or image manifest type at this time. To see a complete list of supported operating systems see: https://docs.aws.amazon.com/inspector/latest/user/supported.html.
SCAN_ELIGIBILITY_EXPIRED
- The configured scan duration has lapsed for this image.
RESOURCE_TERMINATED
- This resource has been terminated. The findings and coverage associated with this resource are in the process of being cleaned up.
SUCCESSFUL
- The scan was successful.
NO_RESOURCES_FOUND
- Reserved for future use.
IMAGE_SIZE_EXCEEDED
- Reserved for future use.
SCAN_FREQUENCY_MANUAL
- This image will not be covered by Amazon Inspector due to the repository scan frequency configuration.
SCAN_FREQUENCY_SCAN_ON_PUSH
- This image will be scanned one time and will not new findings because of the scan frequency configuration.
EC2_INSTANCE_STOPPED
- This EC2 instance is in a stopped state, therefore, Amazon Inspector will pause scanning. The existing findings will continue to exist until the instance is terminated. Once the instance is re-started, Inspector will automatically start scanning the instance again. Please note that you will not be charged for this instance while it’s in a stopped state.
PENDING_DISABLE
- This resource is pending cleanup during disablement. The customer will not be billed while a resource is in the pending disable status.
NO INVENTORY
- Amazon Inspector couldn’t find software application inventory to scan for vulnerabilities. This might be caused due to required Amazon Inspector associations being deleted or failing to run on your resource. Please verify the status of InspectorInventoryCollection-do-not-delete
association in the SSM console for the resource. Additionally, you can verify the instance’s inventory in the SSM Fleet Manager console.
STALE_INVENTORY
- Amazon Inspector wasn’t able to collect an updated software application inventory in the last 7 days. Please confirm the required Amazon Inspector associations still exist and you can still see an updated inventory in the SSM console.
EXCLUDED_BY_TAG
- This resource was not scanned because it has been excluded by a tag.
UNSUPPORTED_RUNTIME
- The function was not scanned because it has an unsupported runtime. To see a complete list of supported runtimes see: https://docs.aws.amazon.com/inspector/latest/user/supported.html.
UNSUPPORTED_MEDIA_TYPE
- The ECR image has an unsupported media type.
UNSUPPORTED_CONFIG_FILE
- Reserved for future use.
DEEP_INSPECTION_PACKAGE_COLLECTION_LIMIT_EXCEEDED
- The instance has exceeded the 5000 package limit for Amazon Inspector Deep inspection. To resume Deep inspection for this instance you can try to adjust the custom paths associated with the account.
DEEP_INSPECTION_DAILY_SSM_INVENTORY_LIMIT_EXCEEDED
- The SSM agent couldn\'t send inventory to Amazon Inspector because the SSM quota for Inventory data collected per instance per day has already been reached for this instance.
DEEP_INSPECTION_COLLECTION_TIME_LIMIT_EXCEEDED
- Amazon Inspector failed to extract the package inventory because the package collection time exceeding the maximum threshold of 15 minutes.
DEEP_INSPECTION_NO_INVENTORY
The Amazon Inspector plugin hasn\'t yet been able to collect an inventory of packages for this instance. This is usually the result of a pending scan, however, if this status persists after 6 hours, use SSM to ensure that the required Amazon Inspector associations exist and are running for the instance.
The Amazon Inspector scan type covering the resource.
', 'GetEncryptionKeyRequest$scanType' => 'The scan type the key encrypts.
', 'ResetEncryptionKeyRequest$scanType' => 'The scan type the key encrypts.
', 'UpdateEncryptionKeyRequest$scanType' => 'The scan type for the encryption key.
', ], ], 'Schedule' => [ 'base' => 'A schedule.
', 'refs' => [ 'CisScanConfiguration$schedule' => 'The CIS scan configuration\'s schedule.
', 'CreateCisScanConfigurationRequest$schedule' => 'The schedule for the CIS scan configuration.
', 'UpdateCisScanConfigurationRequest$schedule' => 'The schedule for the CIS scan configuration.
', ], ], 'SearchVulnerabilitiesFilterCriteria' => [ 'base' => 'Details on the criteria used to define the filter for a vulnerability search.
', 'refs' => [ 'SearchVulnerabilitiesRequest$filterCriteria' => 'The criteria used to filter the results of a vulnerability search.
', ], ], 'SearchVulnerabilitiesRequest' => [ 'base' => NULL, 'refs' => [], ], 'SearchVulnerabilitiesResponse' => [ 'base' => NULL, 'refs' => [], ], 'SecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'SecurityGroupIdList$member' => NULL, ], ], 'SecurityGroupIdList' => [ 'base' => NULL, 'refs' => [ 'LambdaVpcConfig$securityGroupIds' => 'The VPC security groups and subnets that are attached to an AWS Lambda function. For more information, see VPC Settings.
', ], ], 'SendCisSessionHealthRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendCisSessionHealthResponse' => [ 'base' => NULL, 'refs' => [], ], 'SendCisSessionTelemetryRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendCisSessionTelemetryResponse' => [ 'base' => NULL, 'refs' => [], ], 'Service' => [ 'base' => NULL, 'refs' => [ 'ListAccountPermissionsRequest$service' => 'The service scan type to check permissions for.
', 'Permission$service' => 'The services that the permissions allow an account to perform the given operations for.
', ], ], 'ServiceQuotaExceededException' => [ 'base' => 'You have exceeded your service quota. To perform the requested action, remove some of the relevant resources, or use Service Quotas to request a service quota increase.
', 'refs' => [], ], 'Severity' => [ 'base' => NULL, 'refs' => [ 'Finding$severity' => 'The severity of the finding. UNTRIAGED
applies to PACKAGE_VULNERABILITY
type findings that the vendor has not assigned a severity yet. For more information, see Severity levels for findings in the Amazon Inspector user guide.
An object that contains the counts of aggregated finding per severity.
', 'refs' => [ 'AccountAggregationResponse$severityCounts' => 'The number of findings by severity.
', 'AmiAggregationResponse$severityCounts' => 'An object that contains the count of matched findings per severity.
', 'AwsEcrContainerAggregationResponse$severityCounts' => 'The number of finding by severity.
', 'Ec2InstanceAggregationResponse$severityCounts' => 'An object that contains the count of matched findings per severity.
', 'FindingTypeAggregationResponse$severityCounts' => 'The value to sort results by.
', 'ImageLayerAggregationResponse$severityCounts' => 'An object that represents the count of matched findings per severity.
', 'LambdaFunctionAggregationResponse$severityCounts' => NULL, 'LambdaLayerAggregationResponse$severityCounts' => NULL, 'PackageAggregationResponse$severityCounts' => 'An object that contains the count of matched findings per severity.
', 'RepositoryAggregationResponse$severityCounts' => 'An object that represent the count of matched findings per severity.
', 'TitleAggregationResponse$severityCounts' => 'An object that represent the count of matched findings per severity.
', ], ], 'SortCriteria' => [ 'base' => 'Details about the criteria used to sort finding results.
', 'refs' => [ 'ListFindingsRequest$sortCriteria' => 'Details on the sort criteria to apply to your finding results.
', ], ], 'SortField' => [ 'base' => NULL, 'refs' => [ 'SortCriteria$field' => 'The finding detail field by which results are sorted.
', ], ], 'SortOrder' => [ 'base' => NULL, 'refs' => [ 'AccountAggregation$sortOrder' => 'The sort order (ascending or descending).
', 'AmiAggregation$sortOrder' => 'The order to sort results by.
', 'AwsEcrContainerAggregation$sortOrder' => 'The sort order (ascending or descending).
', 'Ec2InstanceAggregation$sortOrder' => 'The order to sort results by.
', 'FindingTypeAggregation$sortOrder' => 'The order to sort results by.
', 'ImageLayerAggregation$sortOrder' => 'The order to sort results by.
', 'LambdaFunctionAggregation$sortOrder' => 'The order to use for sorting the results.
', 'LambdaLayerAggregation$sortOrder' => 'The order to use for sorting the results.
', 'PackageAggregation$sortOrder' => 'The order to sort results by.
', 'RepositoryAggregation$sortOrder' => 'The order to sort results by.
', 'SortCriteria$sortOrder' => 'The order by which findings are sorted.
', 'TitleAggregation$sortOrder' => 'The order to sort results by.
', ], ], 'SourceLayerHash' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$sourceLayerHash' => 'The source layer hash of the vulnerable package.
', ], ], 'StartCisSessionMessage' => [ 'base' => 'The start CIS session message.
', 'refs' => [ 'StartCisSessionRequest$message' => 'The start CIS session message.
', ], ], 'StartCisSessionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartCisSessionResponse' => [ 'base' => NULL, 'refs' => [], ], 'State' => [ 'base' => 'An object that described the state of Amazon Inspector scans for an account.
', 'refs' => [ 'AccountState$state' => 'An object detailing the status of Amazon Inspector for the account.
', 'ResourceState$ec2' => 'An object detailing the state of Amazon Inspector scanning for Amazon EC2 resources.
', 'ResourceState$ecr' => 'An object detailing the state of Amazon Inspector scanning for Amazon ECR resources.
', 'ResourceState$lambda' => NULL, 'ResourceState$lambdaCode' => NULL, ], ], 'Status' => [ 'base' => NULL, 'refs' => [ 'Account$status' => 'The status of Amazon Inspector for the account.
', 'FailedAccount$status' => 'The status of Amazon Inspector for the account.
', 'FailedMemberAccountEc2DeepInspectionStatusState$ec2ScanStatus' => 'The status of EC2 scanning in the account that failed to activate Amazon Inspector deep inspection.
', 'ResourceStatus$ec2' => 'The status of Amazon Inspector scanning for Amazon EC2 resources.
', 'ResourceStatus$ecr' => 'The status of Amazon Inspector scanning for Amazon ECR resources.
', 'ResourceStatus$lambda' => 'The status of Amazon Inspector scanning for AWS Lambda function.
', 'ResourceStatus$lambdaCode' => 'The status of Amazon Inspector scanning for custom application code for Amazon Web Services Lambda functions.
', 'State$status' => 'The status of Amazon Inspector for the account.
', ], ], 'StatusCounts' => [ 'base' => 'The status counts.
', 'refs' => [ 'CisCheckAggregation$statusCounts' => 'The CIS check status counts.
', 'CisTargetResourceAggregation$statusCounts' => 'The target resource status counts.
', ], ], 'Step' => [ 'base' => 'Details about the step associated with a finding.
', 'refs' => [ 'StepList$member' => NULL, ], ], 'StepList' => [ 'base' => NULL, 'refs' => [ 'NetworkPath$steps' => 'The details on the steps in the network path.
', ], ], 'StopCisMessageProgress' => [ 'base' => 'The stop CIS message progress.
', 'refs' => [ 'StopCisSessionMessage$progress' => 'The progress of the message.
', ], ], 'StopCisSessionMessage' => [ 'base' => 'The stop CIS session message.
', 'refs' => [ 'StopCisSessionRequest$message' => 'The stop CIS session message.
', ], ], 'StopCisSessionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopCisSessionResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopCisSessionStatus' => [ 'base' => NULL, 'refs' => [ 'StopCisSessionMessage$status' => 'The status of the message.
', ], ], 'String' => [ 'base' => NULL, 'refs' => [ 'AccessDeniedException$message' => NULL, 'AwsEcrContainerAggregationResponse$architecture' => 'The architecture of the container.
', 'AwsEcrContainerAggregationResponse$imageSha' => 'The SHA value of the container image.
', 'AwsEcrContainerAggregationResponse$repository' => 'The container repository.
', 'AwsEcrContainerImageDetails$author' => 'The image author of the Amazon ECR container image.
', 'BadRequestException$message' => NULL, 'CisCheckAggregation$checkDescription' => 'The description for the CIS check.
', 'CisCheckAggregation$checkId' => 'The check ID for the CIS check.
', 'CisCheckAggregation$platform' => 'The CIS check platform.
', 'CisCheckAggregation$title' => 'The CIS check title.
', 'CisScan$scheduledBy' => 'The account or organization that schedules the CIS scan.
', 'CisScanResultDetails$checkDescription' => 'The account ID that\'s associated with the CIS scan result details.
', 'CisScanResultDetails$checkId' => 'The CIS scan result details\' check ID.
', 'CisScanResultDetails$platform' => 'The CIS scan result details\' platform.
', 'CisScanResultDetails$remediation' => 'The CIS scan result details\' remediation.
', 'CisScanResultDetails$statusReason' => 'The CIS scan result details\' status reason.
', 'CisScanResultDetails$title' => 'The CIS scan result details\' title.
', 'CisStringFilter$value' => 'The value of the CIS string filter.
', 'CisTargetResourceAggregation$platform' => 'The platform for the CIS target resource.
', 'ConflictException$message' => NULL, 'ConflictException$resourceId' => 'The ID of the conflicting resource.
', 'ConflictException$resourceType' => 'The type of the conflicting resource.
', 'Destination$bucketName' => 'The name of the Amazon S3 bucket to export findings to.
', 'Destination$keyPrefix' => 'The prefix that the findings will be written under.
', 'Destination$kmsKeyArn' => 'The ARN of the KMS key used to encrypt data when exporting findings.
', 'Ec2InstanceAggregationResponse$accountId' => 'The Amazon Web Services account for the Amazon EC2 instance.
', 'Ec2InstanceAggregationResponse$operatingSystem' => 'The operating system of the Amazon EC2 instance.
', 'EcrRepositoryMetadata$name' => 'The name of the Amazon ECR repository.
', 'FreeTrialInfoError$message' => 'The error message returned.
', 'GetCisScanReportResponse$url' => 'The URL where the CIS scan report PDF can be downloaded.
', 'InternalServerException$message' => NULL, 'LambdaFunctionAggregationResponse$functionName' => 'The AWS Lambda function names included in the aggregation results.
', 'LambdaFunctionAggregationResponse$runtime' => 'The runtimes included in the aggregation results.
', 'LambdaFunctionMetadata$functionName' => 'The name of a function.
', 'LambdaLayerList$member' => NULL, 'ResourceNotFoundException$message' => NULL, 'ServiceQuotaExceededException$message' => NULL, 'ServiceQuotaExceededException$resourceId' => 'The ID of the resource that exceeds a service quota.
', 'TagList$member' => NULL, 'TagValueList$member' => NULL, 'ThrottlingException$message' => NULL, 'TitleAggregationResponse$vulnerabilityId' => 'The vulnerability ID of the finding.
', 'ValidationException$message' => NULL, 'ValidationExceptionField$message' => 'The validation exception message.
', 'ValidationExceptionField$name' => 'The name of the validation exception.
', ], ], 'StringComparison' => [ 'base' => NULL, 'refs' => [ 'StringFilter$comparison' => 'The operator to use when comparing values in the filter.
', ], ], 'StringFilter' => [ 'base' => 'An object that describes the details of a string filter.
', 'refs' => [ 'PackageFilter$architecture' => 'An object that contains details on the package architecture type to filter on.
', 'PackageFilter$name' => 'An object that contains details on the name of the package to filter on.
', 'PackageFilter$release' => 'An object that contains details on the package release to filter on.
', 'PackageFilter$sourceLambdaLayerArn' => NULL, 'PackageFilter$sourceLayerHash' => 'An object that contains details on the source layer hash to filter on.
', 'PackageFilter$version' => 'The package version to filter on.
', 'StringFilterList$member' => NULL, ], ], 'StringFilterList' => [ 'base' => NULL, 'refs' => [ 'AmiAggregation$amis' => 'The IDs of AMIs to aggregate findings for.
', 'AwsEcrContainerAggregation$architectures' => 'The architecture of the containers.
', 'AwsEcrContainerAggregation$imageShas' => 'The image SHA values.
', 'AwsEcrContainerAggregation$imageTags' => 'The image tags.
', 'AwsEcrContainerAggregation$repositories' => 'The container repositories.
', 'AwsEcrContainerAggregation$resourceIds' => 'The container resource IDs.
', 'Ec2InstanceAggregation$amis' => 'The AMI IDs associated with the Amazon EC2 instances to aggregate findings for.
', 'Ec2InstanceAggregation$instanceIds' => 'The Amazon EC2 instance IDs to aggregate findings for.
', 'Ec2InstanceAggregation$operatingSystems' => 'The operating system types to aggregate findings for. Valid values must be uppercase and underscore separated, examples are ORACLE_LINUX_7
and ALPINE_LINUX_3_8
.
Details of the Amazon Web Services account IDs used to filter findings.
', 'FilterCriteria$codeVulnerabilityDetectorName' => 'The name of the detector used to identify a code vulnerability in a Lambda function used to filter findings.
', 'FilterCriteria$codeVulnerabilityDetectorTags' => 'The detector type tag associated with the vulnerability used to filter findings. Detector tags group related vulnerabilities by common themes or tactics. For a list of available tags by programming language, see Java tags, or Python tags.
', 'FilterCriteria$codeVulnerabilityFilePath' => 'The file path to the file in a Lambda function that contains a code vulnerability used to filter findings.
', 'FilterCriteria$componentId' => 'Details of the component IDs used to filter findings.
', 'FilterCriteria$componentType' => 'Details of the component types used to filter findings.
', 'FilterCriteria$ec2InstanceImageId' => 'Details of the Amazon EC2 instance image IDs used to filter findings.
', 'FilterCriteria$ec2InstanceSubnetId' => 'Details of the Amazon EC2 instance subnet IDs used to filter findings.
', 'FilterCriteria$ec2InstanceVpcId' => 'Details of the Amazon EC2 instance VPC IDs used to filter findings.
', 'FilterCriteria$ecrImageArchitecture' => 'Details of the Amazon ECR image architecture types used to filter findings.
', 'FilterCriteria$ecrImageHash' => 'Details of the Amazon ECR image hashes used to filter findings.
', 'FilterCriteria$ecrImageRegistry' => 'Details on the Amazon ECR registry used to filter findings.
', 'FilterCriteria$ecrImageRepositoryName' => 'Details on the name of the Amazon ECR repository used to filter findings.
', 'FilterCriteria$ecrImageTags' => 'The tags attached to the Amazon ECR container image.
', 'FilterCriteria$exploitAvailable' => 'Filters the list of AWS Lambda findings by the availability of exploits.
', 'FilterCriteria$findingArn' => 'Details on the finding ARNs used to filter findings.
', 'FilterCriteria$findingStatus' => 'Details on the finding status types used to filter findings.
', 'FilterCriteria$findingType' => 'Details on the finding types used to filter findings.
', 'FilterCriteria$fixAvailable' => 'Details on whether a fix is available through a version update. This value can be YES
, NO
, or PARTIAL
. A PARTIAL
fix means that some, but not all, of the packages identified in the finding have fixes available through updated versions.
Filters the list of AWS Lambda functions by execution role.
', 'FilterCriteria$lambdaFunctionLayers' => 'Filters the list of AWS Lambda functions by the function\'s layers. A Lambda function can have up to five layers.
', 'FilterCriteria$lambdaFunctionName' => 'Filters the list of AWS Lambda functions by the name of the function.
', 'FilterCriteria$lambdaFunctionRuntime' => 'Filters the list of AWS Lambda functions by the runtime environment for the Lambda function.
', 'FilterCriteria$networkProtocol' => 'Details on network protocol used to filter findings.
', 'FilterCriteria$relatedVulnerabilities' => 'Details on the related vulnerabilities used to filter findings.
', 'FilterCriteria$resourceId' => 'Details on the resource IDs used to filter findings.
', 'FilterCriteria$resourceType' => 'Details on the resource types used to filter findings.
', 'FilterCriteria$severity' => 'Details on the severity used to filter findings.
', 'FilterCriteria$title' => 'Details on the finding title used to filter findings.
', 'FilterCriteria$vendorSeverity' => 'Details on the vendor severity used to filter findings.
', 'FilterCriteria$vulnerabilityId' => 'Details on the vulnerability ID used to filter findings.
', 'FilterCriteria$vulnerabilitySource' => 'Details on the vulnerability type used to filter findings.
', 'ImageLayerAggregation$layerHashes' => 'The hashes associated with the layers.
', 'ImageLayerAggregation$repositories' => 'The repository associated with the container image hosting the layers.
', 'ImageLayerAggregation$resourceIds' => 'The ID of the container image layer.
', 'LambdaFunctionAggregation$functionNames' => 'The AWS Lambda function names to include in the aggregation results.
', 'LambdaFunctionAggregation$resourceIds' => 'The resource IDs to include in the aggregation results.
', 'LambdaFunctionAggregation$runtimes' => 'Returns findings aggregated by AWS Lambda function runtime environments.
', 'LambdaLayerAggregation$functionNames' => 'The names of the AWS Lambda functions associated with the layers.
', 'LambdaLayerAggregation$layerArns' => 'The Amazon Resource Name (ARN) of the AWS Lambda function layer.
', 'LambdaLayerAggregation$resourceIds' => 'The resource IDs for the AWS Lambda function layers.
', 'ListFindingAggregationsRequest$accountIds' => 'The Amazon Web Services account IDs to retrieve finding aggregation data for.
', 'PackageAggregation$packageNames' => 'The names of packages to aggregate findings on.
', 'RepositoryAggregation$repositories' => 'The names of repositories to aggregate findings on.
', 'TitleAggregation$titles' => 'The finding titles to aggregate on.
', 'TitleAggregation$vulnerabilityIds' => 'The vulnerability IDs of the findings.
', ], ], 'StringInput' => [ 'base' => NULL, 'refs' => [ 'StringFilter$value' => 'The value to filter on.
', ], ], 'StringList' => [ 'base' => NULL, 'refs' => [ 'AwsEcrContainerAggregationResponse$imageTags' => 'The container image stags.
', ], ], 'SubnetId' => [ 'base' => NULL, 'refs' => [ 'SubnetIdList$member' => NULL, ], ], 'SubnetIdList' => [ 'base' => NULL, 'refs' => [ 'LambdaVpcConfig$subnetIds' => 'A list of VPC subnet IDs.
', ], ], 'SuggestedFix' => [ 'base' => 'A suggested fix for a vulnerability in your Lambda function code.
', 'refs' => [ 'SuggestedFixes$member' => NULL, ], ], 'SuggestedFixCodeString' => [ 'base' => NULL, 'refs' => [ 'SuggestedFix$code' => 'The fix\'s code.
', ], ], 'SuggestedFixDescriptionString' => [ 'base' => NULL, 'refs' => [ 'SuggestedFix$description' => 'The fix\'s description.
', ], ], 'SuggestedFixes' => [ 'base' => NULL, 'refs' => [ 'CodeSnippetResult$suggestedFixes' => 'Details of a suggested code fix.
', ], ], 'TagComparison' => [ 'base' => NULL, 'refs' => [ 'TagFilter$comparison' => 'The tag filter comparison value.
', ], ], 'TagFilter' => [ 'base' => 'The tag filter.
', 'refs' => [ 'ResourceTagFilterList$member' => NULL, ], ], 'TagKey' => [ 'base' => NULL, 'refs' => [ 'TagKeyList$member' => NULL, ], ], 'TagKeyList' => [ 'base' => NULL, 'refs' => [ 'UntagResourceRequest$tagKeys' => 'The tag keys to remove from the resource.
', ], ], 'TagList' => [ 'base' => NULL, 'refs' => [ 'EcrContainerImageMetadata$tags' => 'Tags associated with the Amazon ECR image metadata.
', ], ], 'TagMap' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$tags' => 'A list of tags for the filter.
', 'Ec2InstanceAggregationResponse$instanceTags' => 'The tags attached to the instance.
', 'Ec2Metadata$tags' => 'The tags attached to the instance.
', 'Filter$tags' => 'The tags attached to the filter.
', 'LambdaFunctionAggregationResponse$lambdaTags' => 'The tags included in the aggregation results.
', 'LambdaFunctionMetadata$functionTags' => 'The resource tags on an AWS Lambda function.
', 'ListTagsForResourceResponse$tags' => 'The tags associated with the resource.
', 'Resource$tags' => 'The tags attached to the resource.
', 'TagResourceRequest$tags' => 'The tags to be added to a resource.
', ], ], 'TagResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'TagResourceResponse' => [ 'base' => NULL, 'refs' => [], ], 'TagValueList' => [ 'base' => NULL, 'refs' => [ 'TargetResourceTags$value' => NULL, ], ], 'Target' => [ 'base' => NULL, 'refs' => [ 'Targets$member' => NULL, ], ], 'TargetAccount' => [ 'base' => NULL, 'refs' => [ 'TargetAccountList$member' => NULL, ], ], 'TargetAccountList' => [ 'base' => NULL, 'refs' => [ 'CreateCisTargets$accountIds' => 'The CIS target account ids.
', 'UpdateCisTargets$accountIds' => 'The target account ids.
', ], ], 'TargetResourceTags' => [ 'base' => NULL, 'refs' => [ 'CisTargetResourceAggregation$targetResourceTags' => 'The tag for the target resource.
', 'CisTargets$targetResourceTags' => 'The CIS target resource tags.
', 'CreateCisTargets$targetResourceTags' => 'The CIS target resource tags.
', 'UpdateCisTargets$targetResourceTags' => 'The target resource tags.
', ], ], 'TargetStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$targetStatusFilters' => 'The criteria\'s target status filters.
', ], ], 'TargetStatusReasonFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$targetStatusReasonFilters' => 'The criteria\'s target status reason filters.
', ], ], 'Targets' => [ 'base' => NULL, 'refs' => [ 'AtigData$targets' => 'The commercial sectors this vulnerability targets.
', ], ], 'ThrottlingException' => [ 'base' => 'The limit on the number of requests per second was exceeded.
', 'refs' => [], ], 'Time' => [ 'base' => 'The time.
', 'refs' => [ 'DailySchedule$startTime' => 'The schedule start time.
', 'MonthlySchedule$startTime' => 'The monthly schedule\'s start time.
', 'WeeklySchedule$startTime' => 'The weekly schedule\'s start time.
', ], ], 'TimeOfDay' => [ 'base' => NULL, 'refs' => [ 'Time$timeOfDay' => 'The time of day in 24-hour format (00:00).
', ], ], 'Timestamp' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$lastModifiedAt' => 'The date and time that a user last updated the configuration, in ISO 8601 format
', 'CisDateFilter$earliestScanStartTime' => 'The CIS date filter\'s earliest scan start time.
', 'CisDateFilter$latestScanStartTime' => 'The CIS date filter\'s latest scan start time.
', 'CisScan$scanDate' => 'The CIS scan\'s date.
', 'DateFilter$endInclusive' => 'A timestamp representing the end of the time period filtered on.
', 'DateFilter$startInclusive' => 'A timestamp representing the start of the time period filtered on.
', 'FreeTrialInfo$end' => 'The date and time that the Amazon Inspector free trail ends for a given account.
', 'FreeTrialInfo$start' => 'The date and time that the Amazon Inspector free trail started for a given account.
', ], ], 'Timezone' => [ 'base' => NULL, 'refs' => [ 'Time$timezone' => 'The timezone.
', ], ], 'TitleAggregation' => [ 'base' => 'The details that define an aggregation based on finding title.
', 'refs' => [ 'AggregationRequest$titleAggregation' => 'An object that contains details about an aggregation request based on finding title.
', ], ], 'TitleAggregationResponse' => [ 'base' => 'A response that contains details on the results of a finding aggregation by title.
', 'refs' => [ 'AggregationResponse$titleAggregation' => 'An object that contains details about an aggregation response based on finding title.
', ], ], 'TitleFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$titleFilters' => 'The criteria\'s title filters.
', 'CisScanResultsAggregatedByChecksFilterCriteria$titleFilters' => 'The criteria\'s title filters.
', ], ], 'TitleSortBy' => [ 'base' => NULL, 'refs' => [ 'TitleAggregation$sortBy' => 'The value to sort results by.
', ], ], 'Tool' => [ 'base' => NULL, 'refs' => [ 'Tools$member' => NULL, ], ], 'Tools' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$tools' => 'The known malware tools or kits that can exploit the vulnerability.
', ], ], 'Ttp' => [ 'base' => NULL, 'refs' => [ 'Ttps$member' => NULL, ], ], 'Ttps' => [ 'base' => NULL, 'refs' => [ 'AtigData$ttps' => 'The MITRE ATT&CK tactics, techniques, and procedures (TTPs) associated with vulnerability.
', 'FindingDetail$ttps' => 'The MITRE adversary tactics, techniques, or procedures (TTPs) associated with the vulnerability.
', ], ], 'UUID' => [ 'base' => NULL, 'refs' => [ 'SendCisSessionHealthRequest$scanJobId' => 'A unique identifier for the scan job.
', 'SendCisSessionHealthRequest$sessionToken' => 'The unique token that identifies the CIS session.
', 'SendCisSessionTelemetryRequest$scanJobId' => 'A unique identifier for the scan job.
', 'SendCisSessionTelemetryRequest$sessionToken' => 'The unique token that identifies the CIS session.
', 'StartCisSessionMessage$sessionToken' => 'The unique token that identifies the CIS session.
', 'StartCisSessionRequest$scanJobId' => 'A unique identifier for the scan job.
', 'StopCisSessionRequest$scanJobId' => 'A unique identifier for the scan job.
', 'StopCisSessionRequest$sessionToken' => 'The unique token that identifies the CIS session.
', ], ], 'UntagResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UntagResourceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCisScanConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCisScanConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCisTargets' => [ 'base' => 'Updates CIS targets.
', 'refs' => [ 'UpdateCisScanConfigurationRequest$targets' => 'The targets for the CIS scan configuration.
', ], ], 'UpdateConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEc2DeepInspectionConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEc2DeepInspectionConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEncryptionKeyRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEncryptionKeyResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFilterRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFilterResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateOrgEc2DeepInspectionConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateOrgEc2DeepInspectionConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateOrganizationConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateOrganizationConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'Usage' => [ 'base' => 'Contains usage information about the cost of Amazon Inspector operation.
', 'refs' => [ 'UsageList$member' => NULL, ], ], 'UsageAccountId' => [ 'base' => NULL, 'refs' => [ 'UsageAccountIdList$member' => NULL, ], ], 'UsageAccountIdList' => [ 'base' => NULL, 'refs' => [ 'ListUsageTotalsRequest$accountIds' => 'The Amazon Web Services account IDs to retrieve usage totals for.
', ], ], 'UsageList' => [ 'base' => NULL, 'refs' => [ 'UsageTotal$usage' => 'An object representing the total usage for an account.
', ], ], 'UsageTotal' => [ 'base' => 'The total of usage for an account ID.
', 'refs' => [ 'UsageTotalList$member' => NULL, ], ], 'UsageTotalList' => [ 'base' => NULL, 'refs' => [ 'ListUsageTotalsResponse$totals' => 'An object with details on the total usage for the requested account.
', ], ], 'UsageType' => [ 'base' => NULL, 'refs' => [ 'Usage$type' => 'The type scan.
', ], ], 'UsageValue' => [ 'base' => NULL, 'refs' => [ 'Usage$total' => 'The total of usage.
', ], ], 'ValidationException' => [ 'base' => 'The request has failed validation due to missing required fields or having invalid inputs.
', 'refs' => [], ], 'ValidationExceptionField' => [ 'base' => 'An object that describes a validation exception.
', 'refs' => [ 'ValidationExceptionFields$member' => NULL, ], ], 'ValidationExceptionFields' => [ 'base' => NULL, 'refs' => [ 'ValidationException$fields' => 'The fields that failed validation.
', ], ], 'ValidationExceptionReason' => [ 'base' => NULL, 'refs' => [ 'ValidationException$reason' => 'The reason for the validation failure.
', ], ], 'Vendor' => [ 'base' => NULL, 'refs' => [ 'ComputePlatform$vendor' => 'The compute platform vendor.
', ], ], 'VendorCreatedAt' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$vendorCreatedAt' => 'The date and time when the vendor created this vulnerability.
', ], ], 'VendorSeverity' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$vendorSeverity' => 'The severity assigned by the vendor.
', ], ], 'VendorUpdatedAt' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$vendorUpdatedAt' => 'The date and time when the vendor last updated this vulnerability.
', ], ], 'Version' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$version' => 'The version of the AWS Lambda function.
', ], ], 'VpcId' => [ 'base' => NULL, 'refs' => [ 'LambdaVpcConfig$vpcId' => 'The ID of the VPC.
', ], ], 'VulnId' => [ 'base' => NULL, 'refs' => [ 'VulnIdList$member' => NULL, ], ], 'VulnIdList' => [ 'base' => NULL, 'refs' => [ 'SearchVulnerabilitiesFilterCriteria$vulnerabilityIds' => 'The IDs for specific vulnerabilities.
', ], ], 'Vulnerabilities' => [ 'base' => NULL, 'refs' => [ 'SearchVulnerabilitiesResponse$vulnerabilities' => 'Details about the listed vulnerability.
', ], ], 'Vulnerability' => [ 'base' => 'Contains details about a specific vulnerability Amazon Inspector can detect.
', 'refs' => [ 'Vulnerabilities$member' => NULL, ], ], 'VulnerabilityDescription' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$description' => 'A description of the vulnerability.
', ], ], 'VulnerabilityId' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$vulnerabilityId' => 'The ID given to this vulnerability.
', 'VulnerabilityIdList$member' => NULL, ], ], 'VulnerabilityIdList' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$relatedVulnerabilities' => 'One or more vulnerabilities related to the one identified in this finding.
', ], ], 'VulnerabilityReferenceUrl' => [ 'base' => NULL, 'refs' => [ 'VulnerabilityReferenceUrls$member' => NULL, ], ], 'VulnerabilityReferenceUrls' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$referenceUrls' => 'The reference URLs for the vulnerability data.
', 'Vulnerability$referenceUrls' => 'Links to various resources with more information on this vulnerability.
', ], ], 'VulnerabilitySource' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$source' => 'The source of the vulnerability information. Possible results are RHEL
, AMAZON_CVE
, DEBIAN
or NVD
.
A link to the official source material for this vulnerability.
', ], ], 'VulnerablePackage' => [ 'base' => 'Information on the vulnerable package identified by a finding.
', 'refs' => [ 'VulnerablePackageList$member' => NULL, ], ], 'VulnerablePackageList' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$vulnerablePackages' => 'The packages impacted by this vulnerability.
', ], ], 'VulnerablePackageRemediation' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$remediation' => 'The code to run in your environment to update packages with a fix available.
', ], ], 'WeeklySchedule' => [ 'base' => 'A weekly schedule.
', 'refs' => [ 'Schedule$weekly' => 'The schedule\'s weekly.
', ], ], ],]; +return [ 'version' => '2.0', 'service' => 'Amazon Inspector is a vulnerability discovery service that automates continuous scanning for security vulnerabilities within your Amazon EC2, Amazon ECR, and Amazon Web Services Lambda environments.
', 'operations' => [ 'AssociateMember' => 'Associates an Amazon Web Services account with an Amazon Inspector delegated administrator. An HTTP 200 response indicates the association was successfully started, but doesn’t indicate whether it was completed. You can check if the association completed by using ListMembers for multiple accounts or GetMembers for a single account.
', 'BatchGetAccountStatus' => 'Retrieves the Amazon Inspector status of multiple Amazon Web Services accounts within your environment.
', 'BatchGetCodeSnippet' => 'Retrieves code snippets from findings that Amazon Inspector detected code vulnerabilities in.
', 'BatchGetFindingDetails' => 'Gets vulnerability details for findings.
', 'BatchGetFreeTrialInfo' => 'Gets free trial status for multiple Amazon Web Services accounts.
', 'BatchGetMemberEc2DeepInspectionStatus' => 'Retrieves Amazon Inspector deep inspection activation status of multiple member accounts within your organization. You must be the delegated administrator of an organization in Amazon Inspector to use this API.
', 'BatchUpdateMemberEc2DeepInspectionStatus' => 'Activates or deactivates Amazon Inspector deep inspection for the provided member accounts in your organization. You must be the delegated administrator of an organization in Amazon Inspector to use this API.
', 'CancelFindingsReport' => 'Cancels the given findings report.
', 'CancelSbomExport' => 'Cancels a software bill of materials (SBOM) report.
', 'CreateCisScanConfiguration' => 'Creates a CIS scan configuration.
', 'CreateFilter' => 'Creates a filter resource using specified filter criteria. When the filter action is set to SUPPRESS
this action creates a suppression rule.
Creates a finding report. By default only ACTIVE
findings are returned in the report. To see SUPRESSED
or CLOSED
findings you must specify a value for the findingStatus
filter criteria.
Creates a software bill of materials (SBOM) report.
', 'DeleteCisScanConfiguration' => 'Deletes a CIS scan configuration.
', 'DeleteFilter' => 'Deletes a filter resource.
', 'DescribeOrganizationConfiguration' => 'Describe Amazon Inspector configuration settings for an Amazon Web Services organization.
', 'Disable' => 'Disables Amazon Inspector scans for one or more Amazon Web Services accounts. Disabling all scan types in an account disables the Amazon Inspector service.
', 'DisableDelegatedAdminAccount' => 'Disables the Amazon Inspector delegated administrator for your organization.
', 'DisassociateMember' => 'Disassociates a member account from an Amazon Inspector delegated administrator.
', 'Enable' => 'Enables Amazon Inspector scans for one or more Amazon Web Services accounts.
', 'EnableDelegatedAdminAccount' => 'Enables the Amazon Inspector delegated administrator for your Organizations organization.
', 'GetCisScanReport' => 'Retrieves a CIS scan report.
', 'GetCisScanResultDetails' => 'Retrieves CIS scan result details.
', 'GetConfiguration' => 'Retrieves setting configurations for Inspector scans.
', 'GetDelegatedAdminAccount' => 'Retrieves information about the Amazon Inspector delegated administrator for your organization.
', 'GetEc2DeepInspectionConfiguration' => 'Retrieves the activation status of Amazon Inspector deep inspection and custom paths associated with your account.
', 'GetEncryptionKey' => 'Gets an encryption key.
', 'GetFindingsReportStatus' => 'Gets the status of a findings report.
', 'GetMember' => 'Gets member information for your organization.
', 'GetSbomExport' => 'Gets details of a software bill of materials (SBOM) report.
', 'ListAccountPermissions' => 'Lists the permissions an account has to configure Amazon Inspector.
', 'ListCisScanConfigurations' => 'Lists CIS scan configurations.
', 'ListCisScanResultsAggregatedByChecks' => 'Lists scan results aggregated by checks.
', 'ListCisScanResultsAggregatedByTargetResource' => 'Lists scan results aggregated by a target resource.
', 'ListCisScans' => 'Returns a CIS scan list.
', 'ListCoverage' => 'Lists coverage details for you environment.
', 'ListCoverageStatistics' => 'Lists Amazon Inspector coverage statistics for your environment.
', 'ListDelegatedAdminAccounts' => 'Lists information about the Amazon Inspector delegated administrator of your organization.
', 'ListFilters' => 'Lists the filters associated with your account.
', 'ListFindingAggregations' => 'Lists aggregated finding data for your environment based on specific criteria.
', 'ListFindings' => 'Lists findings for your environment.
', 'ListMembers' => 'List members associated with the Amazon Inspector delegated administrator for your organization.
', 'ListTagsForResource' => 'Lists all tags attached to a given resource.
', 'ListUsageTotals' => 'Lists the Amazon Inspector usage totals over the last 30 days.
', 'ResetEncryptionKey' => 'Resets an encryption key. After the key is reset your resources will be encrypted by an Amazon Web Services owned key.
', 'SearchVulnerabilities' => 'Lists Amazon Inspector coverage details for a specific vulnerability.
', 'SendCisSessionHealth' => 'Sends a CIS session health. This API is used by the Amazon Inspector SSM plugin to communicate with the Amazon Inspector service. The Amazon Inspector SSM plugin calls this API to start a CIS scan session for the scan ID supplied by the service.
', 'SendCisSessionTelemetry' => 'Sends a CIS session telemetry. This API is used by the Amazon Inspector SSM plugin to communicate with the Amazon Inspector service. The Amazon Inspector SSM plugin calls this API to start a CIS scan session for the scan ID supplied by the service.
', 'StartCisSession' => 'Starts a CIS session. This API is used by the Amazon Inspector SSM plugin to communicate with the Amazon Inspector service. The Amazon Inspector SSM plugin calls this API to start a CIS scan session for the scan ID supplied by the service.
', 'StopCisSession' => 'Stops a CIS session. This API is used by the Amazon Inspector SSM plugin to communicate with the Amazon Inspector service. The Amazon Inspector SSM plugin calls this API to start a CIS scan session for the scan ID supplied by the service.
', 'TagResource' => 'Adds tags to a resource.
', 'UntagResource' => 'Removes tags from a resource.
', 'UpdateCisScanConfiguration' => 'Updates a CIS scan configuration.
', 'UpdateConfiguration' => 'Updates setting configurations for your Amazon Inspector account. When you use this API as an Amazon Inspector delegated administrator this updates the setting for all accounts you manage. Member accounts in an organization cannot update this setting.
', 'UpdateEc2DeepInspectionConfiguration' => 'Activates, deactivates Amazon Inspector deep inspection, or updates custom paths for your account.
', 'UpdateEncryptionKey' => 'Updates an encryption key. A ResourceNotFoundException
means that an Amazon Web Services owned key is being used for encryption.
Specifies the action that is to be applied to the findings that match the filter.
', 'UpdateOrgEc2DeepInspectionConfiguration' => 'Updates the Amazon Inspector deep inspection custom paths for your organization. You must be an Amazon Inspector delegated administrator to use this API.
', 'UpdateOrganizationConfiguration' => 'Updates the configurations for your Amazon Inspector organization.
', ], 'shapes' => [ 'AccessDeniedException' => [ 'base' => 'You do not have sufficient access to perform this action.
', 'refs' => [], ], 'Account' => [ 'base' => 'An Amazon Web Services account within your environment that Amazon Inspector has been enabled for.
', 'refs' => [ 'AccountList$member' => NULL, ], ], 'AccountAggregation' => [ 'base' => 'An object that contains details about an aggregation response based on Amazon Web Services accounts.
', 'refs' => [ 'AggregationRequest$accountAggregation' => 'An object that contains details about an aggregation request based on Amazon Web Services account IDs.
', ], ], 'AccountAggregationResponse' => [ 'base' => 'An aggregation of findings by Amazon Web Services account ID.
', 'refs' => [ 'AggregationResponse$accountAggregation' => 'An object that contains details about an aggregation response based on Amazon Web Services account IDs.
', ], ], 'AccountId' => [ 'base' => NULL, 'refs' => [ 'Account$accountId' => 'The ID of the Amazon Web Services account.
', 'AccountAggregationResponse$accountId' => 'The Amazon Web Services account ID.
', 'AccountIdSet$member' => NULL, 'AccountState$accountId' => 'The Amazon Web Services account ID.
', 'AmiAggregationResponse$accountId' => 'The Amazon Web Services account ID for the AMI.
', 'AssociateMemberRequest$accountId' => 'The Amazon Web Services account ID of the member account to be associated.
', 'AssociateMemberResponse$accountId' => 'The Amazon Web Services account ID of the successfully associated member account.
', 'AwsEcrContainerAggregationResponse$accountId' => 'The Amazon Web Services account ID of the account that owns the container.
', 'CisAccountIdList$member' => NULL, 'CisCheckAggregation$accountId' => 'The account ID for the CIS check.
', 'CisScanResultDetails$accountId' => 'The CIS scan result details\' account ID.
', 'CisTargetResourceAggregation$accountId' => 'The account ID for the CIS target resource.
', 'CoveredResource$accountId' => 'The Amazon Web Services account ID of the covered resource.
', 'DelegatedAdmin$accountId' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator for your organization.
', 'DelegatedAdminAccount$accountId' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator for your organization.
', 'DisableDelegatedAdminAccountRequest$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the current Amazon Inspector delegated administrator.
', 'DisableDelegatedAdminAccountResponse$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the successfully disabled delegated administrator.
', 'DisassociateMemberRequest$accountId' => 'The Amazon Web Services account ID of the member account to disassociate.
', 'DisassociateMemberResponse$accountId' => 'The Amazon Web Services account ID of the successfully disassociated member.
', 'EnableDelegatedAdminAccountRequest$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator.
', 'EnableDelegatedAdminAccountResponse$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the successfully Amazon Inspector delegated administrator.
', 'FailedAccount$accountId' => 'The Amazon Web Services account ID.
', 'FailedMemberAccountEc2DeepInspectionStatusState$accountId' => 'The unique identifier for the Amazon Web Services account of the organization member that failed to activate Amazon Inspector deep inspection.
', 'Finding$awsAccountId' => 'The Amazon Web Services account ID associated with the finding.
', 'FindingTypeAggregationResponse$accountId' => 'The ID of the Amazon Web Services account associated with the findings.
', 'GetCisScanResultDetailsRequest$accountId' => 'The account ID.
', 'GetMemberRequest$accountId' => 'The Amazon Web Services account ID of the member account to retrieve information on.
', 'ImageLayerAggregationResponse$accountId' => 'The ID of the Amazon Web Services account that owns the container image hosting the layer image.
', 'LambdaFunctionAggregationResponse$accountId' => 'The ID of the Amazon Web Services account that owns the Amazon Web Services Lambda function.
', 'LambdaLayerAggregationResponse$accountId' => 'The account ID of the Amazon Web Services Lambda function layer.
', 'Member$accountId' => 'The Amazon Web Services account ID of the member account.
', 'Member$delegatedAdminAccountId' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator for this member account.
', 'MemberAccountEc2DeepInspectionStatus$accountId' => 'The unique identifier for the Amazon Web Services account of the organization member.
', 'MemberAccountEc2DeepInspectionStatusState$accountId' => 'The unique identifier for the Amazon Web Services account of the organization member
', 'PackageAggregationResponse$accountId' => 'The ID of the Amazon Web Services account associated with the findings.
', 'ReportTargetAccounts$member' => NULL, 'RepositoryAggregationResponse$accountId' => 'The ID of the Amazon Web Services account associated with the findings.
', 'TitleAggregationResponse$accountId' => 'The ID of the Amazon Web Services account associated with the findings.
', ], ], 'AccountIdFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$accountIdFilters' => 'The criteria\'s account ID filters.
', 'ListCisScansFilterCriteria$targetAccountIdFilters' => 'The list of target account ID filters.
', ], ], 'AccountIdSet' => [ 'base' => NULL, 'refs' => [ 'BatchGetAccountStatusRequest$accountIds' => 'The 12-digit Amazon Web Services account IDs of the accounts to retrieve Amazon Inspector status for.
', 'BatchGetMemberEc2DeepInspectionStatusRequest$accountIds' => 'The unique identifiers for the Amazon Web Services accounts to retrieve Amazon Inspector deep inspection activation status for.
</p>
', 'DisableRequest$accountIds' => 'An array of account IDs you want to disable Amazon Inspector scans for.
', 'EnableRequest$accountIds' => 'A list of account IDs you want to enable Amazon Inspector scans for.
', ], ], 'AccountList' => [ 'base' => NULL, 'refs' => [ 'DisableResponse$accounts' => 'Information on the accounts that have had Amazon Inspector scans successfully disabled. Details are provided for each account.
', 'EnableResponse$accounts' => 'Information on the accounts that have had Amazon Inspector scans successfully enabled. Details are provided for each account.
', ], ], 'AccountSortBy' => [ 'base' => NULL, 'refs' => [ 'AccountAggregation$sortBy' => 'The value to sort by.
', ], ], 'AccountState' => [ 'base' => 'An object with details the status of an Amazon Web Services account within your Amazon Inspector environment.
', 'refs' => [ 'AccountStateList$member' => NULL, ], ], 'AccountStateList' => [ 'base' => NULL, 'refs' => [ 'BatchGetAccountStatusResponse$accounts' => 'An array of objects that provide details on the status of Amazon Inspector for each of the requested accounts.
', ], ], 'AggCounts' => [ 'base' => NULL, 'refs' => [ 'Counts$count' => 'The number of resources.
', ], ], 'AggregationFindingType' => [ 'base' => NULL, 'refs' => [ 'AccountAggregation$findingType' => 'The type of finding.
', 'FindingTypeAggregation$findingType' => 'The finding type to aggregate.
', 'TitleAggregation$findingType' => 'The type of finding to aggregate on.
', ], ], 'AggregationRequest' => [ 'base' => 'Contains details about an aggregation request.
', 'refs' => [ 'ListFindingAggregationsRequest$aggregationRequest' => 'Details of the aggregation request that is used to filter your aggregation results.
', ], ], 'AggregationResourceType' => [ 'base' => NULL, 'refs' => [ 'AccountAggregation$resourceType' => 'The type of resource.
', 'FindingTypeAggregation$resourceType' => 'The resource type to aggregate.
', 'TitleAggregation$resourceType' => 'The resource type to aggregate on.
', ], ], 'AggregationResponse' => [ 'base' => 'A structure that contains details about the results of an aggregation type.
', 'refs' => [ 'AggregationResponseList$member' => NULL, ], ], 'AggregationResponseList' => [ 'base' => NULL, 'refs' => [ 'ListFindingAggregationsResponse$responses' => 'Objects that contain the results of an aggregation operation.
', ], ], 'AggregationType' => [ 'base' => NULL, 'refs' => [ 'ListFindingAggregationsRequest$aggregationType' => 'The type of the aggregation request.
', 'ListFindingAggregationsResponse$aggregationType' => 'The type of aggregation to perform.
', ], ], 'AmiAggregation' => [ 'base' => 'The details that define an aggregation based on Amazon machine images (AMIs).
', 'refs' => [ 'AggregationRequest$amiAggregation' => 'An object that contains details about an aggregation request based on Amazon Machine Images (AMIs).
', ], ], 'AmiAggregationResponse' => [ 'base' => 'A response that contains the results of a finding aggregation by AMI.
', 'refs' => [ 'AggregationResponse$amiAggregation' => 'An object that contains details about an aggregation response based on Amazon Machine Images (AMIs).
', ], ], 'AmiId' => [ 'base' => NULL, 'refs' => [ 'AmiAggregationResponse$ami' => 'The ID of the AMI that findings were aggregated for.
', 'Ec2InstanceAggregationResponse$ami' => 'The Amazon Machine Image (AMI) of the Amazon EC2 instance.
', 'Ec2Metadata$amiId' => 'The ID of the Amazon Machine Image (AMI) used to launch the instance.
', ], ], 'AmiSortBy' => [ 'base' => NULL, 'refs' => [ 'AmiAggregation$sortBy' => 'The value to sort results by.
', ], ], 'Architecture' => [ 'base' => NULL, 'refs' => [ 'ArchitectureList$member' => NULL, ], ], 'ArchitectureList' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$architectures' => 'The instruction set architecture that the Amazon Web Services Lambda function supports. Architecture is a string array with one of the valid values. The default architecture value is x86_64
.
The Amazon resource number (ARN) of the resource to list tags of.
', 'TagResourceRequest$resourceArn' => 'The Amazon Resource Name (ARN) of the resource to apply a tag to.
', 'UntagResourceRequest$resourceArn' => 'The Amazon Resource Name (ARN) for the resource to remove tags from.
', ], ], 'AssociateMemberRequest' => [ 'base' => NULL, 'refs' => [], ], 'AssociateMemberResponse' => [ 'base' => NULL, 'refs' => [], ], 'AtigData' => [ 'base' => 'The Amazon Web Services Threat Intel Group (ATIG) details for a specific vulnerability.
', 'refs' => [ 'Vulnerability$atigData' => 'An object that contains information about the Amazon Web Services Threat Intel Group (ATIG) details for the vulnerability.
', ], ], 'AutoEnable' => [ 'base' => 'Represents which scan types are automatically enabled for new members of your Amazon Inspector organization.
', 'refs' => [ 'DescribeOrganizationConfigurationResponse$autoEnable' => 'The scan types are automatically enabled for new members of your organization.
', 'UpdateOrganizationConfigurationRequest$autoEnable' => 'Defines which scan types are enabled automatically for new members of your Amazon Inspector organization.
', 'UpdateOrganizationConfigurationResponse$autoEnable' => 'The updated status of scan types automatically enabled for new members of your Amazon Inspector organization.
', ], ], 'AwsEc2InstanceDetails' => [ 'base' => 'Details of the Amazon EC2 instance involved in a finding.
', 'refs' => [ 'ResourceDetails$awsEc2Instance' => 'An object that contains details about the Amazon EC2 instance involved in the finding.
', ], ], 'AwsEcrContainerAggregation' => [ 'base' => 'An aggregation of information about Amazon ECR containers.
', 'refs' => [ 'AggregationRequest$awsEcrContainerAggregation' => 'An object that contains details about an aggregation request based on Amazon ECR container images.
', ], ], 'AwsEcrContainerAggregationResponse' => [ 'base' => 'An aggregation of information about Amazon ECR containers.
', 'refs' => [ 'AggregationResponse$awsEcrContainerAggregation' => 'An object that contains details about an aggregation response based on Amazon ECR container images.
', ], ], 'AwsEcrContainerImageDetails' => [ 'base' => 'The image details of the Amazon ECR container image.
', 'refs' => [ 'ResourceDetails$awsEcrContainerImage' => 'An object that contains details about the Amazon ECR container image involved in the finding.
', ], ], 'AwsEcrContainerSortBy' => [ 'base' => NULL, 'refs' => [ 'AwsEcrContainerAggregation$sortBy' => 'The value to sort by.
', ], ], 'AwsLambdaFunctionDetails' => [ 'base' => 'A summary of information about the Amazon Web Services Lambda function.
', 'refs' => [ 'ResourceDetails$awsLambdaFunction' => 'A summary of the information about an Amazon Web Services Lambda function affected by a finding.
', ], ], 'BadRequestException' => [ 'base' => 'One or more tags submitted as part of the request is not valid.
', 'refs' => [], ], 'BatchGetAccountStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetAccountStatusResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetCodeSnippetRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetCodeSnippetRequestFindingArnsList' => [ 'base' => NULL, 'refs' => [ 'BatchGetCodeSnippetRequest$findingArns' => 'An array of finding ARNs for the findings you want to retrieve code snippets from.
', ], ], 'BatchGetCodeSnippetResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetFindingDetailsRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetFindingDetailsResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetFreeTrialInfoRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetFreeTrialInfoRequestAccountIdsList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFreeTrialInfoRequest$accountIds' => 'The account IDs to get free trial status for.
', ], ], 'BatchGetFreeTrialInfoResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetMemberEc2DeepInspectionStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchGetMemberEc2DeepInspectionStatusResponse' => [ 'base' => NULL, 'refs' => [], ], 'BatchUpdateMemberEc2DeepInspectionStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'BatchUpdateMemberEc2DeepInspectionStatusResponse' => [ 'base' => NULL, 'refs' => [], ], 'BenchmarkProfile' => [ 'base' => NULL, 'refs' => [ 'StopCisSessionMessage$benchmarkProfile' => 'The message benchmark profile.
', ], ], 'BenchmarkVersion' => [ 'base' => NULL, 'refs' => [ 'StopCisSessionMessage$benchmarkVersion' => 'The message benchmark version.
', ], ], 'Boolean' => [ 'base' => NULL, 'refs' => [ 'AutoEnable$ec2' => 'Represents whether Amazon EC2 scans are automatically enabled for new members of your Amazon Inspector organization.
', 'AutoEnable$ecr' => 'Represents whether Amazon ECR scans are automatically enabled for new members of your Amazon Inspector organization.
', 'AutoEnable$lambda' => 'Represents whether Amazon Web Services Lambda standard scans are automatically enabled for new members of your Amazon Inspector organization.
', 'AutoEnable$lambdaCode' => 'Represents whether Lambda code scans are automatically enabled for new members of your Amazon Inspector organization.
</p>
', 'DescribeOrganizationConfigurationResponse$maxAccountLimitReached' => 'Represents whether your organization has reached the maximum Amazon Web Services account limit for Amazon Inspector.
', 'ListMembersRequest$onlyAssociated' => 'Specifies whether to list only currently associated members if True
or to list all members within the organization if False
.
Whether Amazon Inspector deep inspection is active in the account. If TRUE
Amazon Inspector deep inspection is active, if FALSE
it is not active.
Specify TRUE
to activate Amazon Inspector deep inspection in your account, or FALSE
to deactivate. Member accounts in an organization cannot deactivate deep inspection, instead the delegated administrator for the organization can deactivate a member account using BatchUpdateMemberEc2DeepInspectionStatus.
The progress\' error checks.
', 'StopCisMessageProgress$failedChecks' => 'The progress\' failed checks.
', 'StopCisMessageProgress$informationalChecks' => 'The progress\' informational checks.
', 'StopCisMessageProgress$notApplicableChecks' => 'The progress\' not applicable checks.
', 'StopCisMessageProgress$notEvaluatedChecks' => 'The progress\' not evaluated checks.
', 'StopCisMessageProgress$successfulChecks' => 'The progress\' successful checks.
', 'StopCisMessageProgress$totalChecks' => 'The progress\' total checks.
', 'StopCisMessageProgress$unknownChecks' => 'The progress\' unknown checks.
', ], ], 'CheckIdFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$checkIdFilters' => 'The criteria\'s check ID filters.
', 'CisScanResultsAggregatedByChecksFilterCriteria$checkIdFilters' => 'The criteria\'s check ID filters.
', 'CisScanResultsAggregatedByTargetResourceFilterCriteria$checkIdFilters' => 'The criteria\'s check ID filters.
', ], ], 'CisAccountIdList' => [ 'base' => NULL, 'refs' => [ 'CisTargets$accountIds' => 'The CIS target account ids.
', ], ], 'CisCheckAggregation' => [ 'base' => 'A CIS check.
', 'refs' => [ 'CisCheckAggregationList$member' => NULL, ], ], 'CisCheckAggregationList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByChecksResponse$checkAggregations' => 'The check aggregations.
', ], ], 'CisDateFilter' => [ 'base' => 'The CIS date filter.
', 'refs' => [ 'CisScanDateFilterList$member' => NULL, ], ], 'CisFindingArn' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetails$findingArn' => 'The CIS scan result details\' finding ARN.
', ], ], 'CisFindingArnFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$findingArnFilters' => 'The criteria\'s finding ARN filters.
', ], ], 'CisFindingStatus' => [ 'base' => NULL, 'refs' => [ 'CisFindingStatusFilter$value' => 'The value of the CIS finding status filter.
', 'CisScanResultDetails$status' => 'The CIS scan result details\' status.
', ], ], 'CisFindingStatusComparison' => [ 'base' => NULL, 'refs' => [ 'CisFindingStatusFilter$comparison' => 'The comparison value of the CIS finding status filter.
', ], ], 'CisFindingStatusFilter' => [ 'base' => 'The CIS finding status filter.
', 'refs' => [ 'CisFindingStatusFilterList$member' => NULL, ], ], 'CisFindingStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$findingStatusFilters' => 'The criteria\'s finding status filters.
', ], ], 'CisNumberFilter' => [ 'base' => 'The CIS number filter.
', 'refs' => [ 'CisNumberFilterList$member' => NULL, ], ], 'CisNumberFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByChecksFilterCriteria$failedResourcesFilters' => 'The criteria\'s failed resources filters.
', 'CisScanResultsAggregatedByTargetResourceFilterCriteria$failedChecksFilters' => 'The criteria\'s failed checks filters.
', 'ListCisScansFilterCriteria$failedChecksFilters' => 'The list of failed checks filters.
', ], ], 'CisOwnerId' => [ 'base' => NULL, 'refs' => [ 'CisScanConfiguration$ownerId' => 'The CIS scan configuration\'s owner ID.
', ], ], 'CisReportStatus' => [ 'base' => NULL, 'refs' => [ 'GetCisScanReportResponse$status' => 'The status.
', ], ], 'CisResultStatus' => [ 'base' => NULL, 'refs' => [ 'CisResultStatusFilter$value' => 'The value of the CIS result status filter.
', ], ], 'CisResultStatusComparison' => [ 'base' => NULL, 'refs' => [ 'CisResultStatusFilter$comparison' => 'The comparison value of the CIS result status filter.
', ], ], 'CisResultStatusFilter' => [ 'base' => 'The CIS result status filter.
', 'refs' => [ 'CisResultStatusFilterList$member' => NULL, ], ], 'CisResultStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$statusFilters' => 'The criteria\'s status filter.
', ], ], 'CisRuleDetails' => [ 'base' => NULL, 'refs' => [ 'CisSessionMessage$cisRuleDetails' => 'The CIS rule details for the CIS session message.
', ], ], 'CisRuleStatus' => [ 'base' => NULL, 'refs' => [ 'CisSessionMessage$status' => 'The status of the CIS session message.
', ], ], 'CisScan' => [ 'base' => 'The CIS scan.
', 'refs' => [ 'CisScanList$member' => NULL, ], ], 'CisScanArn' => [ 'base' => NULL, 'refs' => [ 'CisCheckAggregation$scanArn' => 'The scan ARN for the CIS check scan ARN.
', 'CisScan$scanArn' => 'The CIS scan\'s ARN.
', 'CisScanResultDetails$scanArn' => 'The CIS scan result details\' scan ARN.
', 'CisTargetResourceAggregation$scanArn' => 'The scan ARN for the CIS target resource.
', 'GetCisScanReportRequest$scanArn' => 'The scan ARN.
', 'GetCisScanResultDetailsRequest$scanArn' => 'The scan ARN.
', 'ListCisScanResultsAggregatedByChecksRequest$scanArn' => 'The scan ARN.
', 'ListCisScanResultsAggregatedByTargetResourceRequest$scanArn' => 'The scan ARN.
', ], ], 'CisScanArnFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansFilterCriteria$scanArnFilters' => 'The list of scan ARN filters.
', ], ], 'CisScanConfiguration' => [ 'base' => 'The CIS scan configuration.
', 'refs' => [ 'CisScanConfigurationList$member' => NULL, ], ], 'CisScanConfigurationArn' => [ 'base' => NULL, 'refs' => [ 'CisScan$scanConfigurationArn' => 'The CIS scan\'s configuration ARN.
', 'CisScanConfiguration$scanConfigurationArn' => 'The CIS scan configuration\'s scan configuration ARN.
', 'CreateCisScanConfigurationResponse$scanConfigurationArn' => 'The scan configuration ARN for the CIS scan configuration.
', 'DeleteCisScanConfigurationRequest$scanConfigurationArn' => 'The ARN of the CIS scan configuration.
', 'DeleteCisScanConfigurationResponse$scanConfigurationArn' => 'The ARN of the CIS scan configuration.
', 'UpdateCisScanConfigurationRequest$scanConfigurationArn' => 'The CIS scan configuration ARN.
', 'UpdateCisScanConfigurationResponse$scanConfigurationArn' => 'The CIS scan configuration ARN.
', ], ], 'CisScanConfigurationArnFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsFilterCriteria$scanConfigurationArnFilters' => 'The list of scan configuration ARN filters.
', 'ListCisScansFilterCriteria$scanConfigurationArnFilters' => 'The list of scan configuration ARN filters.
', ], ], 'CisScanConfigurationList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsResponse$scanConfigurations' => 'The CIS scan configuration scan configurations.
', ], ], 'CisScanConfigurationsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsRequest$sortBy' => 'The CIS scan configuration sort by order.
', ], ], 'CisScanDateFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansFilterCriteria$scanAtFilters' => 'The list of scan at filters.
', ], ], 'CisScanList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansResponse$scans' => 'The CIS scans.
', ], ], 'CisScanName' => [ 'base' => NULL, 'refs' => [ 'CisScan$scanName' => 'The the name of the scan configuration that\'s associated with this scan.
', 'CisScanConfiguration$scanName' => 'The name of the CIS scan configuration.
', 'CreateCisScanConfigurationRequest$scanName' => 'The scan name for the CIS scan configuration.
', 'UpdateCisScanConfigurationRequest$scanName' => 'The scan name for the CIS scan configuration.
', ], ], 'CisScanNameFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsFilterCriteria$scanNameFilters' => 'The list of scan name filters.
', 'ListCisScansFilterCriteria$scanNameFilters' => 'The list of scan name filters.
', ], ], 'CisScanResultDetails' => [ 'base' => 'The CIS scan result details.
', 'refs' => [ 'CisScanResultDetailsList$member' => NULL, ], ], 'CisScanResultDetailsFilterCriteria' => [ 'base' => 'The CIS scan result details filter criteria.
', 'refs' => [ 'GetCisScanResultDetailsRequest$filterCriteria' => 'The filter criteria.
', ], ], 'CisScanResultDetailsList' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsResponse$scanResultDetails' => 'The scan result details.
', ], ], 'CisScanResultDetailsSortBy' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsRequest$sortBy' => 'The sort by order.
', ], ], 'CisScanResultsAggregatedByChecksFilterCriteria' => [ 'base' => 'The scan results aggregated by checks filter criteria.
', 'refs' => [ 'ListCisScanResultsAggregatedByChecksRequest$filterCriteria' => 'The filter criteria.
', ], ], 'CisScanResultsAggregatedByChecksSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByChecksRequest$sortBy' => 'The sort by order.
', ], ], 'CisScanResultsAggregatedByTargetResourceFilterCriteria' => [ 'base' => 'The scan results aggregated by target resource filter criteria.
', 'refs' => [ 'ListCisScanResultsAggregatedByTargetResourceRequest$filterCriteria' => 'The filter criteria.
', ], ], 'CisScanResultsAggregatedByTargetResourceSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByTargetResourceRequest$sortBy' => 'The sort by order.
', ], ], 'CisScanResultsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByChecksRequest$maxResults' => 'The maximum number of scan results aggregated by checks to be returned in a single page of results.
', 'ListCisScanResultsAggregatedByTargetResourceRequest$maxResults' => 'The maximum number of scan results aggregated by a target resource to be returned in a single page of results.
', ], ], 'CisScanStatus' => [ 'base' => NULL, 'refs' => [ 'CisScan$status' => 'The CIS scan\'s status.
', 'CisScanStatusFilter$value' => 'The filter value.
', ], ], 'CisScanStatusComparison' => [ 'base' => NULL, 'refs' => [ 'CisScanStatusFilter$comparison' => 'The filter comparison value.
', ], ], 'CisScanStatusFilter' => [ 'base' => 'The CIS scan status filter.
', 'refs' => [ 'CisScanStatusFilterList$member' => NULL, ], ], 'CisScanStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansFilterCriteria$scanStatusFilters' => 'The list of scan status filters.
', ], ], 'CisScheduledByFilterList' => [ 'base' => NULL, 'refs' => [ 'ListCisScansFilterCriteria$scheduledByFilters' => 'The list of scheduled by filters.
', ], ], 'CisSecurityLevel' => [ 'base' => NULL, 'refs' => [ 'CisCheckAggregation$level' => 'The CIS check level.
', 'CisScan$securityLevel' => 'The security level for the CIS scan. Security level refers to the Benchmark levels that CIS assigns to a profile.
', 'CisScanConfiguration$securityLevel' => 'The CIS scan configuration\'s security level.
', 'CisScanResultDetails$level' => 'The CIS scan result details\' level.
', 'CisSecurityLevelFilter$value' => 'The CIS security filter value.
', 'CreateCisScanConfigurationRequest$securityLevel' => 'The security level for the CIS scan configuration. Security level refers to the Benchmark levels that CIS assigns to a profile.
', 'UpdateCisScanConfigurationRequest$securityLevel' => 'The security level for the CIS scan configuration. Security level refers to the Benchmark levels that CIS assigns to a profile.
', ], ], 'CisSecurityLevelComparison' => [ 'base' => NULL, 'refs' => [ 'CisSecurityLevelFilter$comparison' => 'The CIS security filter comparison value.
', ], ], 'CisSecurityLevelFilter' => [ 'base' => 'The CIS security level filter. Security level refers to the Benchmark levels that CIS assigns to a profile.
', 'refs' => [ 'CisSecurityLevelFilterList$member' => NULL, ], ], 'CisSecurityLevelFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$securityLevelFilters' => 'The criteria\'s security level filters. . Security level refers to the Benchmark levels that CIS assigns to a profile.
', 'CisScanResultsAggregatedByChecksFilterCriteria$securityLevelFilters' => 'The criteria\'s security level filters.
', ], ], 'CisSessionMessage' => [ 'base' => 'The CIS session message.
', 'refs' => [ 'CisSessionMessages$member' => NULL, ], ], 'CisSessionMessages' => [ 'base' => NULL, 'refs' => [ 'SendCisSessionTelemetryRequest$messages' => 'The CIS session telemetry messages.
', ], ], 'CisSortOrder' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsRequest$sortOrder' => 'The sort order.
', 'ListCisScanConfigurationsRequest$sortOrder' => 'The CIS scan configuration sort order order.
', 'ListCisScanResultsAggregatedByChecksRequest$sortOrder' => 'The sort order.
', 'ListCisScanResultsAggregatedByTargetResourceRequest$sortOrder' => 'The sort order.
', 'ListCisScansRequest$sortOrder' => 'The CIS scans sort order.
', ], ], 'CisStringComparison' => [ 'base' => NULL, 'refs' => [ 'CisStringFilter$comparison' => 'The comparison value of the CIS string filter.
', ], ], 'CisStringFilter' => [ 'base' => 'The CIS string filter.
', 'refs' => [ 'AccountIdFilterList$member' => NULL, 'CheckIdFilterList$member' => NULL, 'CisFindingArnFilterList$member' => NULL, 'CisScanArnFilterList$member' => NULL, 'CisScanConfigurationArnFilterList$member' => NULL, 'CisScanNameFilterList$member' => NULL, 'CisScheduledByFilterList$member' => NULL, 'OneAccountIdFilterList$member' => NULL, 'PlatformFilterList$member' => NULL, 'ResourceIdFilterList$member' => NULL, 'TitleFilterList$member' => NULL, ], ], 'CisTagMap' => [ 'base' => NULL, 'refs' => [ 'CisScanConfiguration$tags' => 'The CIS scan configuration\'s tags.
', 'CreateCisScanConfigurationRequest$tags' => 'The tags for the CIS scan configuration.
', ], ], 'CisTargetResourceAggregation' => [ 'base' => 'The CIS target resource aggregation.
', 'refs' => [ 'CisTargetResourceAggregationList$member' => NULL, ], ], 'CisTargetResourceAggregationList' => [ 'base' => NULL, 'refs' => [ 'ListCisScanResultsAggregatedByTargetResourceResponse$targetResourceAggregations' => 'The resource aggregations.
', ], ], 'CisTargetStatus' => [ 'base' => NULL, 'refs' => [ 'CisTargetResourceAggregation$targetStatus' => 'The status of the target resource.
', 'CisTargetStatusFilter$value' => 'The value of the CIS target status filter.
', ], ], 'CisTargetStatusComparison' => [ 'base' => NULL, 'refs' => [ 'CisTargetStatusFilter$comparison' => 'The comparison value of the CIS target status filter.
', 'CisTargetStatusReasonFilter$comparison' => 'The comparison value of the CIS target status reason filter.
', ], ], 'CisTargetStatusFilter' => [ 'base' => 'The CIS target status filter.
', 'refs' => [ 'TargetStatusFilterList$member' => NULL, ], ], 'CisTargetStatusReason' => [ 'base' => NULL, 'refs' => [ 'CisTargetResourceAggregation$targetStatusReason' => 'The reason for the target resource.
', 'CisTargetStatusReasonFilter$value' => 'The value of the CIS target status reason filter.
', ], ], 'CisTargetStatusReasonFilter' => [ 'base' => 'The CIS target status reason filter.
', 'refs' => [ 'TargetStatusReasonFilterList$member' => NULL, ], ], 'CisTargets' => [ 'base' => 'The CIS targets.
', 'refs' => [ 'CisScan$targets' => 'The CIS scan\'s targets.
', 'CisScanConfiguration$targets' => 'The CIS scan configuration\'s targets.
', ], ], 'CisaAction' => [ 'base' => NULL, 'refs' => [ 'CisaData$action' => 'The remediation action recommended by CISA for this vulnerability.
', ], ], 'CisaData' => [ 'base' => 'The Cybersecurity and Infrastructure Security Agency (CISA) details for a specific vulnerability.
', 'refs' => [ 'FindingDetail$cisaData' => NULL, 'Vulnerability$cisaData' => 'An object that contains the Cybersecurity and Infrastructure Security Agency (CISA) details for the vulnerability.
', ], ], 'CisaDateAdded' => [ 'base' => NULL, 'refs' => [ 'CisaData$dateAdded' => 'The date and time CISA added this vulnerability to their catalogue.
', ], ], 'CisaDateDue' => [ 'base' => NULL, 'refs' => [ 'CisaData$dateDue' => 'The date and time CISA expects a fix to have been provided vulnerability.
', ], ], 'ClientToken' => [ 'base' => NULL, 'refs' => [ 'EnableDelegatedAdminAccountRequest$clientToken' => 'The idempotency token for the request.
', 'EnableRequest$clientToken' => 'The idempotency token for the request.
', ], ], 'CodeFilePath' => [ 'base' => 'Contains information on where a code vulnerability is located in your Lambda function.
', 'refs' => [ 'CodeVulnerabilityDetails$filePath' => 'Contains information on where the code vulnerability is located in your code.
', ], ], 'CodeLine' => [ 'base' => 'Contains information on the lines of code associated with a code snippet.
', 'refs' => [ 'CodeLineList$member' => NULL, ], ], 'CodeLineContentString' => [ 'base' => NULL, 'refs' => [ 'CodeLine$content' => 'The content of a line of code
', ], ], 'CodeLineList' => [ 'base' => NULL, 'refs' => [ 'CodeSnippetResult$codeSnippet' => 'Contains information on the retrieved code snippet.
', ], ], 'CodeSnippetError' => [ 'base' => 'Contains information about any errors encountered while trying to retrieve a code snippet.
', 'refs' => [ 'CodeSnippetErrorList$member' => NULL, ], ], 'CodeSnippetErrorCode' => [ 'base' => NULL, 'refs' => [ 'CodeSnippetError$errorCode' => 'The error code for the error that prevented a code snippet from being retrieved.
', ], ], 'CodeSnippetErrorList' => [ 'base' => NULL, 'refs' => [ 'BatchGetCodeSnippetResponse$errors' => 'Any errors Amazon Inspector encountered while trying to retrieve the requested code snippets.
', ], ], 'CodeSnippetResult' => [ 'base' => 'Contains information on a code snippet retrieved by Amazon Inspector from a code vulnerability finding.
', 'refs' => [ 'CodeSnippetResultList$member' => NULL, ], ], 'CodeSnippetResultList' => [ 'base' => NULL, 'refs' => [ 'BatchGetCodeSnippetResponse$codeSnippetResults' => 'The retrieved code snippets associated with the provided finding ARNs.
', ], ], 'CodeVulnerabilityDetails' => [ 'base' => 'Contains information on the code vulnerability identified in your Lambda function.
', 'refs' => [ 'Finding$codeVulnerabilityDetails' => 'Details about the code vulnerability identified in a Lambda function used to filter findings.
', ], ], 'Component' => [ 'base' => NULL, 'refs' => [ 'Step$componentId' => 'The component ID.
', ], ], 'ComponentType' => [ 'base' => NULL, 'refs' => [ 'Step$componentType' => 'The component type.
', ], ], 'ComputePlatform' => [ 'base' => 'A compute platform.
', 'refs' => [ 'StopCisSessionMessage$computePlatform' => 'The message compute platform.
', ], ], 'ConflictException' => [ 'base' => 'A conflict occurred.
', 'refs' => [], ], 'Counts' => [ 'base' => 'a structure that contains information on the count of resources within a group.
', 'refs' => [ 'CountsList$member' => NULL, ], ], 'CountsList' => [ 'base' => NULL, 'refs' => [ 'ListCoverageStatisticsResponse$countsByGroup' => 'An array with the number for each group.
', ], ], 'CoverageDateFilter' => [ 'base' => 'Contains details of a coverage date filter.
', 'refs' => [ 'CoverageDateFilterList$member' => NULL, ], ], 'CoverageDateFilterList' => [ 'base' => NULL, 'refs' => [ 'CoverageFilterCriteria$imagePulledAt' => 'The date an image was last pulled at.
', 'CoverageFilterCriteria$lastScannedAt' => 'Filters Amazon Web Services resources based on whether Amazon Inspector has checked them for vulnerabilities within the specified time range.
', ], ], 'CoverageFilterCriteria' => [ 'base' => 'A structure that identifies filter criteria for GetCoverageStatistics
.
An object that contains details on the filters to apply to the coverage data for your environment.
', 'ListCoverageStatisticsRequest$filterCriteria' => 'An object that contains details on the filters to apply to the coverage data for your environment.
', ], ], 'CoverageMapComparison' => [ 'base' => NULL, 'refs' => [ 'CoverageMapFilter$comparison' => 'The operator to compare coverage on.
', ], ], 'CoverageMapFilter' => [ 'base' => 'Contains details of a coverage map filter.
', 'refs' => [ 'CoverageMapFilterList$member' => NULL, ], ], 'CoverageMapFilterList' => [ 'base' => NULL, 'refs' => [ 'CoverageFilterCriteria$ec2InstanceTags' => 'The Amazon EC2 instance tags to filter on.
', 'CoverageFilterCriteria$lambdaFunctionTags' => 'Returns coverage statistics for Amazon Web Services Lambda functions filtered by tag.
', ], ], 'CoverageResourceType' => [ 'base' => NULL, 'refs' => [ 'CoveredResource$resourceType' => 'The type of the covered resource.
', ], ], 'CoverageStringComparison' => [ 'base' => NULL, 'refs' => [ 'CoverageStringFilter$comparison' => 'The operator to compare strings on.
', ], ], 'CoverageStringFilter' => [ 'base' => 'Contains details of a coverage string filter.
', 'refs' => [ 'CoverageStringFilterList$member' => NULL, ], ], 'CoverageStringFilterList' => [ 'base' => NULL, 'refs' => [ 'CoverageFilterCriteria$accountId' => 'An array of Amazon Web Services account IDs to return coverage statistics for.
', 'CoverageFilterCriteria$ecrImageTags' => 'The Amazon ECR image tags to filter on.
', 'CoverageFilterCriteria$ecrRepositoryName' => 'The Amazon ECR repository name to filter on.
', 'CoverageFilterCriteria$lambdaFunctionName' => 'Returns coverage statistics for Amazon Web Services Lambda functions filtered by function names.
', 'CoverageFilterCriteria$lambdaFunctionRuntime' => 'Returns coverage statistics for Amazon Web Services Lambda functions filtered by runtime.
', 'CoverageFilterCriteria$resourceId' => 'An array of Amazon Web Services resource IDs to return coverage statistics for.
', 'CoverageFilterCriteria$resourceType' => 'An array of Amazon Web Services resource types to return coverage statistics for. The values can be AWS_EC2_INSTANCE
, AWS_LAMBDA_FUNCTION
, AWS_ECR_CONTAINER_IMAGE
, AWS_ECR_REPOSITORY
or AWS_ACCOUNT
.
The scan status code to filter on. Valid values are: ValidationException
, InternalServerException
, ResourceNotFoundException
, BadRequestException
, and ThrottlingException
.
The scan status reason to filter on.
', 'CoverageFilterCriteria$scanType' => 'An array of Amazon Inspector scan types to return coverage statistics for.
', ], ], 'CoverageStringInput' => [ 'base' => NULL, 'refs' => [ 'CoverageStringFilter$value' => 'The value to compare strings on.
', ], ], 'CoveredResource' => [ 'base' => 'An object that contains details about a resource covered by Amazon Inspector.
', 'refs' => [ 'CoveredResources$member' => NULL, ], ], 'CoveredResources' => [ 'base' => NULL, 'refs' => [ 'ListCoverageResponse$coveredResources' => 'An object that contains details on the covered resources in your environment.
', ], ], 'CreateCisScanConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateCisScanConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateCisTargets' => [ 'base' => 'Creates CIS targets.
', 'refs' => [ 'CreateCisScanConfigurationRequest$targets' => 'The targets for the CIS scan configuration.
', ], ], 'CreateFilterRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFilterResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFindingsReportRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFindingsReportResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateSbomExportRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateSbomExportResponse' => [ 'base' => NULL, 'refs' => [], ], 'Currency' => [ 'base' => NULL, 'refs' => [ 'Usage$currency' => 'The currency type used when calculating usage data.
', ], ], 'Cvss2' => [ 'base' => 'The Common Vulnerability Scoring System (CVSS) version 2 details for the vulnerability.
', 'refs' => [ 'Vulnerability$cvss2' => 'An object that contains the Common Vulnerability Scoring System (CVSS) Version 2 details for the vulnerability.
', ], ], 'Cvss2BaseScore' => [ 'base' => NULL, 'refs' => [ 'Cvss2$baseScore' => 'The CVSS v2 base score for the vulnerability.
', ], ], 'Cvss2ScoringVector' => [ 'base' => NULL, 'refs' => [ 'Cvss2$scoringVector' => 'The scoring vector associated with the CVSS v2 score.
', ], ], 'Cvss3' => [ 'base' => 'The Common Vulnerability Scoring System (CVSS) version 3 details for the vulnerability.
', 'refs' => [ 'Vulnerability$cvss3' => 'An object that contains the Common Vulnerability Scoring System (CVSS) Version 3 details for the vulnerability.
', ], ], 'Cvss3BaseScore' => [ 'base' => NULL, 'refs' => [ 'Cvss3$baseScore' => 'The CVSS v3 base score for the vulnerability.
', ], ], 'Cvss3ScoringVector' => [ 'base' => NULL, 'refs' => [ 'Cvss3$scoringVector' => 'The scoring vector associated with the CVSS v3 score.
', ], ], 'CvssScore' => [ 'base' => 'The CVSS score for a finding.
', 'refs' => [ 'CvssScoreList$member' => NULL, ], ], 'CvssScoreAdjustment' => [ 'base' => 'Details on adjustments Amazon Inspector made to the CVSS score for a finding.
', 'refs' => [ 'CvssScoreAdjustmentList$member' => NULL, ], ], 'CvssScoreAdjustmentList' => [ 'base' => NULL, 'refs' => [ 'CvssScoreDetails$adjustments' => 'An object that contains details about adjustment Amazon Inspector made to the CVSS score.
', ], ], 'CvssScoreDetails' => [ 'base' => 'Information about the CVSS score.
', 'refs' => [ 'InspectorScoreDetails$adjustedCvss' => 'An object that contains details about the CVSS score given to a finding.
', ], ], 'CvssScoreList' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$cvss' => 'An object that contains details about the CVSS score of a finding.
', ], ], 'Cwe' => [ 'base' => NULL, 'refs' => [ 'Cwes$member' => NULL, ], ], 'CweList' => [ 'base' => NULL, 'refs' => [ 'CodeVulnerabilityDetails$cwes' => 'The Common Weakness Enumeration (CWE) item associated with the detected vulnerability.
', ], ], 'Cwes' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$cwes' => 'The Common Weakness Enumerations (CWEs) associated with the vulnerability.
', 'Vulnerability$cwes' => 'The Common Weakness Enumeration (CWE) associated with the vulnerability.
', ], ], 'DailySchedule' => [ 'base' => 'A daily schedule.
', 'refs' => [ 'Schedule$daily' => 'The schedule\'s daily.
', ], ], 'DateFilter' => [ 'base' => 'Contains details on the time range used to filter findings.
', 'refs' => [ 'DateFilterList$member' => NULL, ], ], 'DateFilterList' => [ 'base' => NULL, 'refs' => [ 'FilterCriteria$ecrImagePushedAt' => 'Details on the Amazon ECR image push date and time used to filter findings.
', 'FilterCriteria$firstObservedAt' => 'Details on the date and time a finding was first seen used to filter findings.
', 'FilterCriteria$lambdaFunctionLastModifiedAt' => 'Filters the list of Amazon Web Services Lambda functions by the date and time that a user last updated the configuration, in ISO 8601 format
', 'FilterCriteria$lastObservedAt' => 'Details on the date and time a finding was last seen used to filter findings.
', 'FilterCriteria$updatedAt' => 'Details on the date and time a finding was last updated at used to filter findings.
', ], ], 'DateTimeTimestamp' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$launchedAt' => 'The date and time the Amazon EC2 instance was launched at.
', 'AwsEcrContainerImageDetails$pushedAt' => 'The date and time the Amazon ECR container image was pushed.
', 'CoverageDateFilter$endInclusive' => 'A timestamp representing the end of the time period to filter results by.
', 'CoverageDateFilter$startInclusive' => 'A timestamp representing the start of the time period to filter results by.
', 'CoveredResource$lastScannedAt' => 'The date and time the resource was last checked for vulnerabilities.
', 'EcrContainerImageMetadata$imagePulledAt' => 'The date an image was last pulled at.
', 'EcrRescanDurationState$updatedAt' => 'A timestamp representing when the last time the ECR scan duration setting was changed.
', 'ExploitabilityDetails$lastKnownExploitAt' => 'The date and time of the last exploit associated with a finding discovered in your environment.
', 'Filter$createdAt' => 'The date and time this filter was created at.
', 'Filter$updatedAt' => 'The date and time the filter was last updated at.
', 'Finding$firstObservedAt' => 'The date and time that the finding was first observed.
', 'Finding$lastObservedAt' => 'The date and time that the finding was last observed.
', 'Finding$updatedAt' => 'The date and time the finding was last updated at.
', 'LambdaFunctionAggregationResponse$lastModifiedAt' => 'The date that the Amazon Web Services Lambda function included in the aggregation results was last changed.
', 'Member$updatedAt' => 'A timestamp showing when the status of this member was last updated.
', 'PackageVulnerabilityDetails$vendorCreatedAt' => 'The date and time that this vulnerability was first added to the vendor\'s database.
', 'PackageVulnerabilityDetails$vendorUpdatedAt' => 'The date and time the vendor last updated this vulnerability in their database.
', ], ], 'Day' => [ 'base' => NULL, 'refs' => [ 'DaysList$member' => NULL, 'MonthlySchedule$day' => 'The monthly schedule\'s day.
', ], ], 'DaysList' => [ 'base' => NULL, 'refs' => [ 'WeeklySchedule$days' => 'The weekly schedule\'s days.
', ], ], 'DelegatedAdmin' => [ 'base' => 'Details of the Amazon Inspector delegated administrator for your organization.
', 'refs' => [ 'GetDelegatedAdminAccountResponse$delegatedAdmin' => 'The Amazon Web Services account ID of the Amazon Inspector delegated administrator.
', ], ], 'DelegatedAdminAccount' => [ 'base' => 'Details of the Amazon Inspector delegated administrator for your organization.
', 'refs' => [ 'DelegatedAdminAccountList$member' => NULL, ], ], 'DelegatedAdminAccountList' => [ 'base' => NULL, 'refs' => [ 'ListDelegatedAdminAccountsResponse$delegatedAdminAccounts' => 'Details of the Amazon Inspector delegated administrator of your organization.
', ], ], 'DelegatedAdminStatus' => [ 'base' => NULL, 'refs' => [ 'DelegatedAdminAccount$status' => 'The status of the Amazon Inspector delegated administrator.
', ], ], 'DeleteCisScanConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteCisScanConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'DeleteFilterRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteFilterResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeOrganizationConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeOrganizationConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'Destination' => [ 'base' => 'Contains details of the Amazon S3 bucket and KMS key used to export findings.
', 'refs' => [ 'CreateFindingsReportRequest$s3Destination' => 'The Amazon S3 export destination for the report.
', 'CreateSbomExportRequest$s3Destination' => NULL, 'GetFindingsReportStatusResponse$destination' => 'The destination of the report.
', 'GetSbomExportResponse$s3Destination' => NULL, ], ], 'DetectionPlatforms' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$detectionPlatforms' => 'Platforms that the vulnerability can be detected on.
', ], ], 'DetectorTagList' => [ 'base' => NULL, 'refs' => [ 'CodeVulnerabilityDetails$detectorTags' => 'The detector tag associated with the vulnerability. Detector tags group related vulnerabilities by common themes or tactics. For a list of available tags by programming language, see Java tags, or Python tags.
', ], ], 'DisableDelegatedAdminAccountRequest' => [ 'base' => NULL, 'refs' => [], ], 'DisableDelegatedAdminAccountResponse' => [ 'base' => NULL, 'refs' => [], ], 'DisableRequest' => [ 'base' => NULL, 'refs' => [], ], 'DisableResourceTypeList' => [ 'base' => NULL, 'refs' => [ 'DisableRequest$resourceTypes' => 'The resource scan types you want to disable.
', ], ], 'DisableResponse' => [ 'base' => NULL, 'refs' => [], ], 'DisassociateMemberRequest' => [ 'base' => NULL, 'refs' => [], ], 'DisassociateMemberResponse' => [ 'base' => NULL, 'refs' => [], ], 'Double' => [ 'base' => NULL, 'refs' => [ 'CvssScore$baseScore' => 'The base CVSS score used for the finding.
', 'CvssScoreDetails$score' => 'The CVSS score.
', 'Finding$inspectorScore' => 'The Amazon Inspector score given to the finding.
', 'FindingDetail$epssScore' => 'The Exploit Prediction Scoring System (EPSS) score of the vulnerability.
', 'NumberFilter$lowerInclusive' => 'The lowest number to be included in the filter.
', 'NumberFilter$upperInclusive' => 'The highest number to be included in the filter.
', ], ], 'Ec2DeepInspectionStatus' => [ 'base' => NULL, 'refs' => [ 'GetEc2DeepInspectionConfigurationResponse$status' => 'The activation status of Amazon Inspector deep inspection in your account.
', 'MemberAccountEc2DeepInspectionStatusState$status' => 'The state of Amazon Inspector deep inspection in the member account.
', 'UpdateEc2DeepInspectionConfigurationResponse$status' => 'The status of Amazon Inspector deep inspection in your account.
', ], ], 'Ec2InstanceAggregation' => [ 'base' => 'The details that define an aggregation based on Amazon EC2 instances.
', 'refs' => [ 'AggregationRequest$ec2InstanceAggregation' => 'An object that contains details about an aggregation request based on Amazon EC2 instances.
', ], ], 'Ec2InstanceAggregationResponse' => [ 'base' => 'A response that contains the results of a finding aggregation by Amazon EC2 instance.
', 'refs' => [ 'AggregationResponse$ec2InstanceAggregation' => 'An object that contains details about an aggregation response based on Amazon EC2 instances.
', ], ], 'Ec2InstanceSortBy' => [ 'base' => NULL, 'refs' => [ 'Ec2InstanceAggregation$sortBy' => 'The value to sort results by.
', ], ], 'Ec2Metadata' => [ 'base' => 'Meta data details of an Amazon EC2 instance.
', 'refs' => [ 'ResourceScanMetadata$ec2' => 'An object that contains metadata details for an Amazon EC2 instance.
', ], ], 'Ec2Platform' => [ 'base' => NULL, 'refs' => [ 'Ec2Metadata$platform' => 'The platform of the instance.
', ], ], 'EcrConfiguration' => [ 'base' => 'Details about the ECR automated re-scan duration setting for your environment.
', 'refs' => [ 'UpdateConfigurationRequest$ecrConfiguration' => 'Specifies how the ECR automated re-scan will be updated for your environment.
', ], ], 'EcrConfigurationState' => [ 'base' => 'Details about the state of the ECR scans for your environment.
', 'refs' => [ 'GetConfigurationResponse$ecrConfiguration' => 'Specifies how the ECR automated re-scan duration is currently configured for your environment.
', ], ], 'EcrContainerImageMetadata' => [ 'base' => 'Information on the Amazon ECR image metadata associated with a finding.
', 'refs' => [ 'ResourceScanMetadata$ecrImage' => 'An object that contains details about the container metadata for an Amazon ECR image.
', ], ], 'EcrPullDateRescanDuration' => [ 'base' => NULL, 'refs' => [ 'EcrConfiguration$pullDateRescanDuration' => 'The rescan duration configured for image pull date.
', 'EcrRescanDurationState$pullDateRescanDuration' => 'The rescan duration configured for image pull date.
', ], ], 'EcrRepositoryMetadata' => [ 'base' => 'Information on the Amazon ECR repository metadata associated with a finding.
', 'refs' => [ 'ResourceScanMetadata$ecrRepository' => 'An object that contains details about the repository an Amazon ECR image resides in.
', ], ], 'EcrRescanDuration' => [ 'base' => NULL, 'refs' => [ 'EcrConfiguration$rescanDuration' => 'The rescan duration configured for image push date.
', 'EcrRescanDurationState$rescanDuration' => 'The rescan duration configured for image push date.
</p>
', ], ], 'EcrRescanDurationState' => [ 'base' => 'Details about the state of your ECR re-scan duration settings. The ECR re-scan duration defines how long an ECR image will be actively scanned by Amazon Inspector. When the number of days since an image was last pushed exceeds the duration configured for image pull date, and the duration configured for image pull date, the monitoring state of that image becomes inactive
and all associated findings are scheduled for closure.
An object that contains details about the state of the ECR re-scan settings.
', ], ], 'EcrRescanDurationStatus' => [ 'base' => NULL, 'refs' => [ 'EcrRescanDurationState$status' => 'The status of changes to the ECR automated re-scan duration.
', ], ], 'EcrScanFrequency' => [ 'base' => NULL, 'refs' => [ 'EcrRepositoryMetadata$scanFrequency' => 'The frequency of scans.
', ], ], 'EnableDelegatedAdminAccountRequest' => [ 'base' => NULL, 'refs' => [], ], 'EnableDelegatedAdminAccountResponse' => [ 'base' => NULL, 'refs' => [], ], 'EnableRequest' => [ 'base' => NULL, 'refs' => [], ], 'EnableResourceTypeList' => [ 'base' => NULL, 'refs' => [ 'EnableRequest$resourceTypes' => 'The resource scan types you want to enable.
', ], ], 'EnableResponse' => [ 'base' => NULL, 'refs' => [], ], 'Epss' => [ 'base' => 'Details about the Exploit Prediction Scoring System (EPSS) score.
', 'refs' => [ 'Vulnerability$epss' => 'An object that contains the Exploit Prediction Scoring System (EPSS) score for a vulnerability.
', ], ], 'EpssDetails' => [ 'base' => 'Details about the Exploit Prediction Scoring System (EPSS) score for a finding.
', 'refs' => [ 'Finding$epss' => 'The finding\'s EPSS score.
', ], ], 'EpssScore' => [ 'base' => NULL, 'refs' => [ 'Epss$score' => 'The Exploit Prediction Scoring System (EPSS) score.
', ], ], 'EpssScoreValue' => [ 'base' => NULL, 'refs' => [ 'EpssDetails$score' => 'The EPSS score.
', ], ], 'ErrorCode' => [ 'base' => NULL, 'refs' => [ 'FailedAccount$errorCode' => 'The error code explaining why the account failed to enable Amazon Inspector.
', 'State$errorCode' => 'The error code explaining why the account failed to enable Amazon Inspector.
', ], ], 'ErrorMessage' => [ 'base' => NULL, 'refs' => [ 'GetFindingsReportStatusResponse$errorMessage' => 'The error message of the report.
', ], ], 'Evidence' => [ 'base' => 'Details of the evidence for a vulnerability identified in a finding.
', 'refs' => [ 'EvidenceList$member' => NULL, ], ], 'EvidenceDetail' => [ 'base' => NULL, 'refs' => [ 'Evidence$evidenceDetail' => 'The evidence details.
', ], ], 'EvidenceList' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$evidences' => 'Information on the evidence of the vulnerability.
', ], ], 'EvidenceRule' => [ 'base' => NULL, 'refs' => [ 'Evidence$evidenceRule' => 'The evidence rule.
', ], ], 'EvidenceSeverity' => [ 'base' => NULL, 'refs' => [ 'Evidence$severity' => 'The evidence severity.
', ], ], 'ExecutionRoleArn' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$executionRoleArn' => 'The Amazon Web Services Lambda function\'s execution role.
', ], ], 'ExploitAvailable' => [ 'base' => NULL, 'refs' => [ 'Finding$exploitAvailable' => 'If a finding discovered in your environment has an exploit available.
', ], ], 'ExploitObserved' => [ 'base' => 'Contains information on when this exploit was observed.
', 'refs' => [ 'FindingDetail$exploitObserved' => NULL, 'Vulnerability$exploitObserved' => 'An object that contains details on when the exploit was observed.
', ], ], 'ExploitabilityDetails' => [ 'base' => 'The details of an exploit available for a finding discovered in your environment.
', 'refs' => [ 'Finding$exploitabilityDetails' => 'The details of an exploit available for a finding discovered in your environment.
', ], ], 'ExternalReportStatus' => [ 'base' => NULL, 'refs' => [ 'GetFindingsReportStatusResponse$status' => 'The status of the report.
', 'GetSbomExportResponse$status' => 'The status of the software bill of materials (SBOM) report.
', ], ], 'FailedAccount' => [ 'base' => 'An object with details on why an account failed to enable Amazon Inspector.
', 'refs' => [ 'FailedAccountList$member' => NULL, ], ], 'FailedAccountList' => [ 'base' => NULL, 'refs' => [ 'BatchGetAccountStatusResponse$failedAccounts' => 'An array of objects detailing any accounts that failed to enable Amazon Inspector and why.
', 'DisableResponse$failedAccounts' => 'Information on any accounts for which Amazon Inspector scans could not be disabled. Details are provided for each account.
', 'EnableResponse$failedAccounts' => 'Information on any accounts for which Amazon Inspector scans could not be enabled. Details are provided for each account.
', ], ], 'FailedMemberAccountEc2DeepInspectionStatusState' => [ 'base' => 'An object that contains details about a member account in your organization that failed to activate Amazon Inspector deep inspection.
', 'refs' => [ 'FailedMemberAccountEc2DeepInspectionStatusStateList$member' => NULL, ], ], 'FailedMemberAccountEc2DeepInspectionStatusStateList' => [ 'base' => NULL, 'refs' => [ 'BatchGetMemberEc2DeepInspectionStatusResponse$failedAccountIds' => 'An array of objects that provide details on any accounts that failed to activate Amazon Inspector deep inspection and why.
</p>
', 'BatchUpdateMemberEc2DeepInspectionStatusResponse$failedAccountIds' => 'An array of objects that provide details for each of the accounts that Amazon Inspector deep inspection status could not be successfully changed for.
', ], ], 'FilePath' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$filePath' => 'The file path of the vulnerable package.
', ], ], 'Filter' => [ 'base' => 'Details about a filter.
', 'refs' => [ 'FilterList$member' => NULL, ], ], 'FilterAction' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$action' => 'Defines the action that is to be applied to the findings that match the filter.
', 'Filter$action' => 'The action that is to be applied to the findings that match the filter.
', 'ListFiltersRequest$action' => 'The action the filter applies to matched findings.
', 'UpdateFilterRequest$action' => 'Specifies the action that is to be applied to the findings that match the filter.
', ], ], 'FilterArn' => [ 'base' => NULL, 'refs' => [ 'CreateFilterResponse$arn' => 'The Amazon Resource Number (ARN) of the successfully created filter.
', 'DeleteFilterRequest$arn' => 'The Amazon Resource Number (ARN) of the filter to be deleted.
', 'DeleteFilterResponse$arn' => 'The Amazon Resource Number (ARN) of the filter that has been deleted.
', 'Filter$arn' => 'The Amazon Resource Number (ARN) associated with this filter.
', 'FilterArnList$member' => NULL, 'UpdateFilterRequest$filterArn' => 'The Amazon Resource Number (ARN) of the filter to update.
', 'UpdateFilterResponse$arn' => 'The Amazon Resource Number (ARN) of the successfully updated filter.
', ], ], 'FilterArnList' => [ 'base' => NULL, 'refs' => [ 'ListFiltersRequest$arns' => 'The Amazon resource number (ARN) of the filter.
', ], ], 'FilterCriteria' => [ 'base' => 'Details on the criteria used to define the filter.
', 'refs' => [ 'CreateFilterRequest$filterCriteria' => 'Defines the criteria to be used in the filter for querying findings.
', 'CreateFindingsReportRequest$filterCriteria' => 'The filter criteria to apply to the results of the finding report.
', 'Filter$criteria' => 'Details on the filter criteria associated with this filter.
', 'GetFindingsReportStatusResponse$filterCriteria' => 'The filter criteria associated with the report.
', 'ListFindingsRequest$filterCriteria' => 'Details on the filters to apply to your finding results.
', 'UpdateFilterRequest$filterCriteria' => 'Defines the criteria to be update in the filter.
', ], ], 'FilterDescription' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$description' => 'A description of the filter.
', 'Filter$description' => 'A description of the filter.
', 'UpdateFilterRequest$description' => 'A description of the filter.
', ], ], 'FilterList' => [ 'base' => NULL, 'refs' => [ 'ListFiltersResponse$filters' => 'Contains details on the filters associated with your account.
', ], ], 'FilterName' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$name' => 'The name of the filter. Minimum length of 3. Maximum length of 64. Valid characters include alphanumeric characters, dot (.), underscore (_), and dash (-). Spaces are not allowed.
', 'Filter$name' => 'The name of the filter.
', 'UpdateFilterRequest$name' => 'The name of the filter.
', ], ], 'FilterReason' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$reason' => 'The reason for creating the filter.
', 'Filter$reason' => 'The reason for the filter.
', 'UpdateFilterRequest$reason' => 'The reason the filter was updated.
', ], ], 'Finding' => [ 'base' => 'Details about an Amazon Inspector finding.
', 'refs' => [ 'FindingList$member' => NULL, ], ], 'FindingArn' => [ 'base' => NULL, 'refs' => [ 'BatchGetCodeSnippetRequestFindingArnsList$member' => NULL, 'CodeSnippetError$findingArn' => 'The ARN of the finding that a code snippet couldn\'t be retrieved for.
', 'CodeSnippetResult$findingArn' => 'The ARN of a finding that the code snippet is associated with.
', 'Finding$findingArn' => 'The Amazon Resource Number (ARN) of the finding.
', 'FindingArnList$member' => NULL, 'FindingDetail$findingArn' => 'The finding ARN that the vulnerability details are associated with.
', 'FindingDetailsError$findingArn' => 'The finding ARN that returned an error.
', ], ], 'FindingArnList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFindingDetailsRequest$findingArns' => 'A list of finding ARNs.
', ], ], 'FindingDescription' => [ 'base' => NULL, 'refs' => [ 'Finding$description' => 'The description of the finding.
', ], ], 'FindingDetail' => [ 'base' => 'Details of the vulnerability identified in a finding.
', 'refs' => [ 'FindingDetails$member' => NULL, ], ], 'FindingDetails' => [ 'base' => NULL, 'refs' => [ 'BatchGetFindingDetailsResponse$findingDetails' => 'A finding\'s vulnerability details.
', ], ], 'FindingDetailsError' => [ 'base' => 'Details about an error encountered when trying to return vulnerability data for a finding.
', 'refs' => [ 'FindingDetailsErrorList$member' => NULL, ], ], 'FindingDetailsErrorCode' => [ 'base' => NULL, 'refs' => [ 'FindingDetailsError$errorCode' => 'The error code.
', ], ], 'FindingDetailsErrorList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFindingDetailsResponse$errors' => 'Error information for findings that details could not be returned for.
', ], ], 'FindingList' => [ 'base' => NULL, 'refs' => [ 'ListFindingsResponse$findings' => 'Contains details on the findings in your environment.
', ], ], 'FindingStatus' => [ 'base' => NULL, 'refs' => [ 'Finding$status' => 'The status of the finding.
', ], ], 'FindingTitle' => [ 'base' => NULL, 'refs' => [ 'Finding$title' => 'The title of the finding.
', ], ], 'FindingType' => [ 'base' => NULL, 'refs' => [ 'Finding$type' => 'The type of the finding. The type
value determines the valid values for resource
in your request. For more information, see Finding types in the Amazon Inspector user guide.
The details that define an aggregation based on finding type.
', 'refs' => [ 'AggregationRequest$findingTypeAggregation' => 'An object that contains details about an aggregation request based on finding types.
', ], ], 'FindingTypeAggregationResponse' => [ 'base' => 'A response that contains the results of a finding type aggregation.
', 'refs' => [ 'AggregationResponse$findingTypeAggregation' => 'An object that contains details about an aggregation response based on finding types.
', ], ], 'FindingTypeSortBy' => [ 'base' => NULL, 'refs' => [ 'FindingTypeAggregation$sortBy' => 'The value to sort results by.
', ], ], 'FirstSeen' => [ 'base' => NULL, 'refs' => [ 'AtigData$firstSeen' => 'The date and time this vulnerability was first observed.
', 'ExploitObserved$firstSeen' => 'The date an time when the exploit was first seen.
', ], ], 'FixAvailable' => [ 'base' => NULL, 'refs' => [ 'Finding$fixAvailable' => 'Details on whether a fix is available through a version update. This value can be YES
, NO
, or PARTIAL
. A PARTIAL
fix means that some, but not all, of the packages identified in the finding have fixes available through updated versions.
Information about the Amazon Inspector free trial for an account.
', 'refs' => [ 'FreeTrialAccountInfoList$member' => NULL, ], ], 'FreeTrialAccountInfoList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFreeTrialInfoResponse$accounts' => 'An array of objects that provide Amazon Inspector free trial details for each of the requested accounts.
', ], ], 'FreeTrialInfo' => [ 'base' => 'An object that contains information about the Amazon Inspector free trial for an account.
', 'refs' => [ 'FreeTrialInfoList$member' => NULL, ], ], 'FreeTrialInfoError' => [ 'base' => 'Information about an error received while accessing free trail data for an account.
', 'refs' => [ 'FreeTrialInfoErrorList$member' => NULL, ], ], 'FreeTrialInfoErrorCode' => [ 'base' => NULL, 'refs' => [ 'FreeTrialInfoError$code' => 'The error code.
', ], ], 'FreeTrialInfoErrorList' => [ 'base' => NULL, 'refs' => [ 'BatchGetFreeTrialInfoResponse$failedAccounts' => 'An array of objects detailing any accounts that free trial data could not be returned for.
', ], ], 'FreeTrialInfoList' => [ 'base' => NULL, 'refs' => [ 'FreeTrialAccountInfo$freeTrialInfo' => 'Contains information about the Amazon Inspector free trial for an account.
', ], ], 'FreeTrialStatus' => [ 'base' => NULL, 'refs' => [ 'FreeTrialInfo$status' => 'The order to sort results by.
', ], ], 'FreeTrialType' => [ 'base' => NULL, 'refs' => [ 'FreeTrialInfo$type' => 'The type of scan covered by the Amazon Inspector free trail.
', ], ], 'FunctionName' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$functionName' => 'The name of the Amazon Web Services Lambda function.
', ], ], 'GetCisScanReportRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetCisScanReportResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetCisScanResultDetailsMaxResults' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsRequest$maxResults' => 'The maximum number of CIS scan result details to be returned in a single page of results.
', ], ], 'GetCisScanResultDetailsRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetCisScanResultDetailsResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetDelegatedAdminAccountRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetDelegatedAdminAccountResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetEc2DeepInspectionConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetEc2DeepInspectionConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetEncryptionKeyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetEncryptionKeyResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetFindingsReportStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetFindingsReportStatusResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetMemberRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMemberResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetSbomExportRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetSbomExportResponse' => [ 'base' => NULL, 'refs' => [], ], 'GroupKey' => [ 'base' => NULL, 'refs' => [ 'Counts$groupKey' => 'The key associated with this group
', 'ListCoverageStatisticsRequest$groupBy' => 'The value to group the results by.
', ], ], 'ImageHash' => [ 'base' => NULL, 'refs' => [ 'AwsEcrContainerImageDetails$imageHash' => 'The image hash of the Amazon ECR container image.
', ], ], 'ImageLayerAggregation' => [ 'base' => 'The details that define an aggregation based on container image layers.
', 'refs' => [ 'AggregationRequest$imageLayerAggregation' => 'An object that contains details about an aggregation request based on container image layers.
', ], ], 'ImageLayerAggregationResponse' => [ 'base' => 'A response that contains the results of a finding aggregation by image layer.
', 'refs' => [ 'AggregationResponse$imageLayerAggregation' => 'An object that contains details about an aggregation response based on container image layers.
', ], ], 'ImageLayerSortBy' => [ 'base' => NULL, 'refs' => [ 'ImageLayerAggregation$sortBy' => 'The value to sort results by.
', ], ], 'ImageTagList' => [ 'base' => NULL, 'refs' => [ 'AwsEcrContainerImageDetails$imageTags' => 'The image tags attached to the Amazon ECR container image.
', ], ], 'InspectorScoreDetails' => [ 'base' => 'Information about the Amazon Inspector score given to a finding.
', 'refs' => [ 'Finding$inspectorScoreDetails' => 'An object that contains details of the Amazon Inspector score.
', ], ], 'Integer' => [ 'base' => NULL, 'refs' => [ 'CisNumberFilter$lowerInclusive' => 'The CIS number filter\'s lower inclusive.
', 'CisNumberFilter$upperInclusive' => 'The CIS number filter\'s upper inclusive.
', 'CisScan$failedChecks' => 'The CIS scan\'s failed checks.
', 'CisScan$totalChecks' => 'The CIS scan\'s total checks.
', 'CodeFilePath$endLine' => 'The line number of the last line of code that a vulnerability was found in.
', 'CodeFilePath$startLine' => 'The line number of the first line of code that a vulnerability was found in.
', 'CodeLine$lineNumber' => 'The line number that a section of code is located at.
', 'CodeSnippetResult$endLine' => 'The line number of the last line of a code snippet.
', 'CodeSnippetResult$startLine' => 'The line number of the first line of a code snippet.
', 'InternalServerException$retryAfterSeconds' => 'The number of seconds to wait before retrying the request.
', 'StatusCounts$failed' => 'The number of checks that failed.
', 'StatusCounts$passed' => 'The number of checks that passed.
', 'StatusCounts$skipped' => 'The number of checks that were skipped.
', 'ThrottlingException$retryAfterSeconds' => 'The number of seconds to wait before retrying the request.
', ], ], 'InternalServerException' => [ 'base' => 'The request has failed due to an internal failure of the Amazon Inspector service.
', 'refs' => [], ], 'IpV4Address' => [ 'base' => NULL, 'refs' => [ 'IpV4AddressList$member' => NULL, ], ], 'IpV4AddressList' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$ipV4Addresses' => 'The IPv4 addresses of the Amazon EC2 instance.
', ], ], 'IpV6Address' => [ 'base' => NULL, 'refs' => [ 'IpV6AddressList$member' => NULL, ], ], 'IpV6AddressList' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$ipV6Addresses' => 'The IPv6 addresses of the Amazon EC2 instance.
', ], ], 'KmsKeyArn' => [ 'base' => NULL, 'refs' => [ 'GetEncryptionKeyResponse$kmsKeyId' => 'A kms key ID.
', 'UpdateEncryptionKeyRequest$kmsKeyId' => 'A KMS key ID for the encryption key.
', ], ], 'LambdaFunctionAggregation' => [ 'base' => 'The details that define a findings aggregation based on Amazon Web Services Lambda functions.
', 'refs' => [ 'AggregationRequest$lambdaFunctionAggregation' => 'Returns an object with findings aggregated by Amazon Web Services Lambda function.
', ], ], 'LambdaFunctionAggregationResponse' => [ 'base' => 'A response that contains the results of an Amazon Web Services Lambda function finding aggregation.
', 'refs' => [ 'AggregationResponse$lambdaFunctionAggregation' => 'An aggregation of findings by Amazon Web Services Lambda function.
', ], ], 'LambdaFunctionMetadata' => [ 'base' => 'The Amazon Web Services Lambda function metadata.
', 'refs' => [ 'ResourceScanMetadata$lambdaFunction' => 'An object that contains metadata details for an Amazon Web Services Lambda function.
', ], ], 'LambdaFunctionSortBy' => [ 'base' => NULL, 'refs' => [ 'LambdaFunctionAggregation$sortBy' => 'The finding severity to use for sorting the results.
', ], ], 'LambdaLayerAggregation' => [ 'base' => 'The details that define a findings aggregation based on an Amazon Web Services Lambda function\'s layers.
', 'refs' => [ 'AggregationRequest$lambdaLayerAggregation' => 'Returns an object with findings aggregated by Amazon Web Services Lambda layer.
', ], ], 'LambdaLayerAggregationResponse' => [ 'base' => 'A response that contains the results of an Amazon Web Services Lambda function layer finding aggregation.
', 'refs' => [ 'AggregationResponse$lambdaLayerAggregation' => 'An aggregation of findings by Amazon Web Services Lambda layer.
', ], ], 'LambdaLayerArn' => [ 'base' => NULL, 'refs' => [ 'CodeVulnerabilityDetails$sourceLambdaLayerArn' => 'The Amazon Resource Name (ARN) of the Lambda layer that the code vulnerability was detected in.
', 'LayerList$member' => NULL, 'VulnerablePackage$sourceLambdaLayerArn' => 'The Amazon Resource Number (ARN) of the Amazon Web Services Lambda function affected by a finding.
', ], ], 'LambdaLayerList' => [ 'base' => NULL, 'refs' => [ 'LambdaFunctionMetadata$layers' => 'The layers for an Amazon Web Services Lambda function. A Lambda function can have up to five layers.
', ], ], 'LambdaLayerSortBy' => [ 'base' => NULL, 'refs' => [ 'LambdaLayerAggregation$sortBy' => 'The finding severity to use for sorting the results.
', ], ], 'LambdaVpcConfig' => [ 'base' => 'The VPC security groups and subnets that are attached to an Amazon Web Services Lambda function. For more information, see VPC Settings.
', 'refs' => [ 'AwsLambdaFunctionDetails$vpcConfig' => 'The Amazon Web Services Lambda function\'s networking configuration.
', ], ], 'LastSeen' => [ 'base' => NULL, 'refs' => [ 'AtigData$lastSeen' => 'The date and time this vulnerability was last observed.
', 'ExploitObserved$lastSeen' => 'The date an time when the exploit was last seen.
', ], ], 'LayerList' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$layers' => 'The Amazon Web Services Lambda function\'s layers. A Lambda function can have up to five layers.
', ], ], 'ListAccountPermissionsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListAccountPermissionsRequest$maxResults' => 'The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
A list of CIS scan configurations filter criteria.
', 'refs' => [ 'ListCisScanConfigurationsRequest$filterCriteria' => 'The CIS scan configuration filter criteria.
', ], ], 'ListCisScanConfigurationsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListCisScanConfigurationsRequest$maxResults' => 'The maximum number of CIS scan configurations to be returned in a single page of results.
', ], ], 'ListCisScanConfigurationsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanConfigurationsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanResultsAggregatedByChecksRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanResultsAggregatedByChecksResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanResultsAggregatedByTargetResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScanResultsAggregatedByTargetResourceResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScansDetailLevel' => [ 'base' => NULL, 'refs' => [ 'ListCisScansRequest$detailLevel' => 'The detail applied to the CIS scan.
', ], ], 'ListCisScansFilterCriteria' => [ 'base' => 'A list of CIS scans filter criteria.
', 'refs' => [ 'ListCisScansRequest$filterCriteria' => 'The CIS scan filter criteria.
', ], ], 'ListCisScansMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListCisScansRequest$maxResults' => 'The maximum number of results to be returned.
', ], ], 'ListCisScansRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScansResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCisScansSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCisScansRequest$sortBy' => 'The CIS scans sort by order.
', ], ], 'ListCoverageMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListCoverageRequest$maxResults' => 'The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
The maximum number of results the response can return. If your request would return more than the maximum the response will return a nextToken
value, use this value when you call the action again to get the remaining results.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
The pagination parameter to be used on the next list operation to retrieve more items.
', ], ], 'ListUsageTotalsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListUsageTotalsResponse' => [ 'base' => NULL, 'refs' => [], ], 'Long' => [ 'base' => NULL, 'refs' => [ 'AmiAggregationResponse$affectedInstances' => 'The IDs of Amazon EC2 instances using this AMI.
', 'Ec2InstanceAggregationResponse$networkFindings' => 'The number of network findings for the Amazon EC2 instance.
', 'ListCoverageStatisticsResponse$totalCounts' => 'The total number for all groups.
', 'RepositoryAggregationResponse$affectedImages' => 'The number of container images impacted by the findings.
', 'SeverityCounts$all' => 'The total count of findings from all severities.
', 'SeverityCounts$critical' => 'The total count of critical severity findings.
', 'SeverityCounts$high' => 'The total count of high severity findings.
', 'SeverityCounts$medium' => 'The total count of medium severity findings.
', ], ], 'MapComparison' => [ 'base' => NULL, 'refs' => [ 'MapFilter$comparison' => 'The operator to use when comparing values in the filter.
', ], ], 'MapFilter' => [ 'base' => 'An object that describes details of a map filter.
', 'refs' => [ 'MapFilterList$member' => NULL, ], ], 'MapFilterList' => [ 'base' => NULL, 'refs' => [ 'Ec2InstanceAggregation$instanceTags' => 'The Amazon EC2 instance tags to aggregate findings for.
', 'FilterCriteria$resourceTags' => 'Details on the resource tags used to filter findings.
', 'LambdaFunctionAggregation$functionTags' => 'The tags to include in the aggregation results.
', ], ], 'MapKey' => [ 'base' => NULL, 'refs' => [ 'CisTagMap$key' => NULL, 'MapFilter$key' => 'The tag key used in the filter.
', 'TagMap$key' => NULL, ], ], 'MapValue' => [ 'base' => NULL, 'refs' => [ 'CisTagMap$value' => NULL, 'MapFilter$value' => 'The tag value used in the filter.
', 'TagMap$value' => NULL, ], ], 'Member' => [ 'base' => 'Details on a member account in your organization.
', 'refs' => [ 'GetMemberResponse$member' => 'Details of the retrieved member account.
', 'MemberList$member' => NULL, ], ], 'MemberAccountEc2DeepInspectionStatus' => [ 'base' => 'An object that contains details about the status of Amazon Inspector deep inspection for a member account in your organization.
', 'refs' => [ 'MemberAccountEc2DeepInspectionStatusList$member' => NULL, ], ], 'MemberAccountEc2DeepInspectionStatusList' => [ 'base' => NULL, 'refs' => [ 'BatchUpdateMemberEc2DeepInspectionStatusRequest$accountIds' => 'The unique identifiers for the Amazon Web Services accounts to change Amazon Inspector deep inspection status for.
', ], ], 'MemberAccountEc2DeepInspectionStatusState' => [ 'base' => 'An object that contains details about the state of Amazon Inspector deep inspection for a member account.
', 'refs' => [ 'MemberAccountEc2DeepInspectionStatusStateList$member' => NULL, ], ], 'MemberAccountEc2DeepInspectionStatusStateList' => [ 'base' => NULL, 'refs' => [ 'BatchGetMemberEc2DeepInspectionStatusResponse$accountIds' => 'An array of objects that provide details on the activation status of Amazon Inspector deep inspection for each of the requested accounts.
</p>
', 'BatchUpdateMemberEc2DeepInspectionStatusResponse$accountIds' => 'An array of objects that provide details for each of the accounts that Amazon Inspector deep inspection status was successfully changed for.
', ], ], 'MemberList' => [ 'base' => NULL, 'refs' => [ 'ListMembersResponse$members' => 'An object that contains details for each member account.
', ], ], 'MeteringAccountId' => [ 'base' => NULL, 'refs' => [ 'BatchGetFreeTrialInfoRequestAccountIdsList$member' => NULL, 'FreeTrialAccountInfo$accountId' => 'The account associated with the Amazon Inspector free trial information.
', 'FreeTrialInfoError$accountId' => 'The account associated with the Amazon Inspector free trial information.
', 'UsageTotal$accountId' => 'The account ID of the account that usage data was retrieved for.
', ], ], 'MonthlyCostEstimate' => [ 'base' => NULL, 'refs' => [ 'Usage$estimatedMonthlyCost' => 'The estimated monthly cost of Amazon Inspector.
', ], ], 'MonthlySchedule' => [ 'base' => 'A monthly schedule.
', 'refs' => [ 'Schedule$monthly' => 'The schedule\'s monthly.
', ], ], 'NetworkPath' => [ 'base' => 'Information on the network path associated with a finding.
', 'refs' => [ 'NetworkReachabilityDetails$networkPath' => 'An object that contains details about a network path associated with a finding.
', ], ], 'NetworkProtocol' => [ 'base' => NULL, 'refs' => [ 'NetworkReachabilityDetails$protocol' => 'The protocol associated with a finding.
', ], ], 'NetworkReachabilityDetails' => [ 'base' => 'Contains the details of a network reachability finding.
', 'refs' => [ 'Finding$networkReachabilityDetails' => 'An object that contains the details of a network reachability finding.
', ], ], 'NextToken' => [ 'base' => NULL, 'refs' => [ 'GetCisScanResultDetailsRequest$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'GetCisScanResultDetailsResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListAccountPermissionsRequest$nextToken' => 'A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the NextToken value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanConfigurationsResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanResultsAggregatedByChecksRequest$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanResultsAggregatedByChecksResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanResultsAggregatedByTargetResourceRequest$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScanResultsAggregatedByTargetResourceResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScansRequest$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCisScansResponse$nextToken' => 'The pagination token from a previous request that\'s used to retrieve the next page of results.
', 'ListCoverageRequest$nextToken' => 'A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. If your response returns more than the maxResults
maximum value it will also return a nextToken
value. For subsequent calls, use the nextToken
value returned from the previous request to continue listing results after the first page.
The pagination parameter to be used on the next list operation to retrieve more items.
', 'SearchVulnerabilitiesRequest$nextToken' => 'A token to use for paginating results that are returned in the response. Set the value of this parameter to null for the first request to a list action. For subsequent calls, use the NextToken
value returned from the previous request to continue listing results after the first page.
The pagination parameter to be used on the next list operation to retrieve more items.
', ], ], 'NonEmptyString' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$iamInstanceProfileArn' => 'The IAM instance profile ARN of the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$imageId' => 'The image ID of the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$keyName' => 'The name of the key pair used to launch the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$subnetId' => 'The subnet ID of the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$type' => 'The type of the Amazon EC2 instance.
', 'AwsEc2InstanceDetails$vpcId' => 'The VPC ID of the Amazon EC2 instance.
', 'AwsEcrContainerAggregationResponse$resourceId' => 'The resource ID of the container.
', 'AwsEcrContainerImageDetails$architecture' => 'The architecture of the Amazon ECR container image.
', 'AwsEcrContainerImageDetails$registry' => 'The registry for the Amazon ECR container image.
', 'AwsEcrContainerImageDetails$repositoryName' => 'The name of the repository the Amazon ECR container image resides in.
', 'AwsLambdaFunctionDetails$codeSha256' => 'The SHA256 hash of the Amazon Web Services Lambda function\'s deployment package.
', 'CodeFilePath$fileName' => 'The name of the file the code vulnerability was found in.
', 'CodeFilePath$filePath' => 'The file path to the code that a vulnerability was found in.
', 'CodeSnippetError$errorMessage' => 'The error message received when Amazon Inspector failed to retrieve a code snippet.
', 'CodeVulnerabilityDetails$detectorId' => 'The ID for the Amazon CodeGuru detector associated with the finding. For more information on detectors see Amazon CodeGuru Detector Library.
', 'CodeVulnerabilityDetails$detectorName' => 'The name of the detector used to identify the code vulnerability. For more information on detectors see CodeGuru Detector Library.
', 'CodeVulnerabilityDetails$ruleId' => 'The identifier for a rule that was used to detect the code vulnerability.
', 'CoverageMapFilter$key' => 'The tag key associated with the coverage map filter.
', 'CoverageMapFilter$value' => 'The tag value associated with the coverage map filter.
', 'CvssScore$scoringVector' => 'The vector string of the CVSS score.
', 'CvssScore$source' => 'The source of the CVSS score.
', 'CvssScore$version' => 'The version of CVSS used for the score.
', 'CvssScoreAdjustment$metric' => 'The metric used to adjust the CVSS score.
', 'CvssScoreAdjustment$reason' => 'The reason the CVSS score has been adjustment.
', 'CvssScoreDetails$cvssSource' => 'The source of the CVSS data.
', 'CvssScoreDetails$scoreSource' => 'The source for the CVSS score.
', 'CvssScoreDetails$scoringVector' => 'The vector for the CVSS score.
', 'CvssScoreDetails$version' => 'The CVSS version used in scoring.
', 'CweList$member' => NULL, 'DetectionPlatforms$member' => NULL, 'DetectorTagList$member' => NULL, 'Ec2InstanceAggregationResponse$instanceId' => 'The Amazon EC2 instance ID.
', 'FailedAccount$errorMessage' => 'The error message received when the account failed to enable Amazon Inspector.
', 'FailedMemberAccountEc2DeepInspectionStatusState$errorMessage' => 'The error message explaining why the account failed to activate Amazon Inspector deep inspection.
', 'FindingDetailsError$errorMessage' => 'The error message.
', 'GetEc2DeepInspectionConfigurationResponse$errorMessage' => 'An error message explaining why Amazon Inspector deep inspection configurations could not be retrieved for your account.
', 'GetSbomExportResponse$errorMessage' => 'An error message.
', 'ImageLayerAggregationResponse$layerHash' => 'The layer hash.
', 'ImageLayerAggregationResponse$repository' => 'The repository the layer resides in.
', 'ImageLayerAggregationResponse$resourceId' => 'The resource ID of the container image layer.
', 'ImageTagList$member' => NULL, 'LambdaFunctionAggregationResponse$resourceId' => 'The resource IDs included in the aggregation results.
', 'LambdaLayerAggregationResponse$functionName' => 'The names of the Amazon Web Services Lambda functions associated with the layers.
', 'LambdaLayerAggregationResponse$layerArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Lambda function layer.
', 'LambdaLayerAggregationResponse$resourceId' => 'The Resource ID of the Amazon Web Services Lambda function layer.
', 'MemberAccountEc2DeepInspectionStatusState$errorMessage' => 'The error message explaining why the account failed to activate Amazon Inspector deep inspection.
', 'NonEmptyStringList$member' => NULL, 'PackageAggregationResponse$packageName' => 'The name of the operating system package.
', 'PackageVulnerabilityDetails$source' => 'The source of the vulnerability information.
', 'PackageVulnerabilityDetails$sourceUrl' => 'A URL to the source of the vulnerability information.
', 'PackageVulnerabilityDetails$vendorSeverity' => 'The severity the vendor has given to this vulnerability type.
', 'Recommendation$Url' => 'The URL address to the CVE remediation recommendations.
', 'Recommendation$text' => 'The recommended course of action to remediate the finding.
', 'ReferenceUrls$member' => NULL, 'RepositoryAggregationResponse$repository' => 'The name of the repository associated with the findings.
', 'Resource$id' => 'The ID of the resource.
', 'Resource$partition' => 'The partition of the resource.
', 'Resource$region' => 'The Amazon Web Services Region the impacted resource is located in.
', 'ResourceMapFilter$key' => 'The filter\'s key.
', 'ResourceMapFilter$value' => 'The filter\'s value.
', 'State$errorMessage' => 'The error message received when the account failed to enable Amazon Inspector.
', 'StringList$member' => NULL, 'TagFilter$key' => 'The tag filter key.
', 'TagFilter$value' => 'The tag filter value.
', 'TargetResourceTags$key' => NULL, 'TitleAggregationResponse$title' => 'The title that the findings were aggregated on.
', 'UpdateEc2DeepInspectionConfigurationResponse$errorMessage' => 'An error message explaining why new Amazon Inspector deep inspection custom paths could not be added.
', 'Vulnerability$id' => 'The ID for the specific vulnerability.
', ], ], 'NonEmptyStringList' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$referenceUrls' => 'One or more URLs that contain details about this vulnerability type.
', ], ], 'NumberFilter' => [ 'base' => 'An object that describes the details of a number filter.
', 'refs' => [ 'NumberFilterList$member' => NULL, 'PackageFilter$epoch' => 'An object that contains details on the package epoch to filter on.
', ], ], 'NumberFilterList' => [ 'base' => NULL, 'refs' => [ 'FilterCriteria$epssScore' => 'The EPSS score used to filter findings.
', 'FilterCriteria$inspectorScore' => 'The Amazon Inspector score to filter on.
', ], ], 'OneAccountIdFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByChecksFilterCriteria$accountIdFilters' => 'The criteria\'s account ID filters.
', ], ], 'OneTimeSchedule' => [ 'base' => 'A one time schedule.
', 'refs' => [ 'Schedule$oneTime' => 'The schedule\'s one time.
', ], ], 'Operation' => [ 'base' => NULL, 'refs' => [ 'Permission$operation' => 'The operations that can be performed with the given permissions.
', ], ], 'OwnerId' => [ 'base' => NULL, 'refs' => [ 'Filter$ownerId' => 'The Amazon Web Services account ID of the account that created the filter.
', ], ], 'PackageAggregation' => [ 'base' => 'The details that define an aggregation based on operating system package type.
', 'refs' => [ 'AggregationRequest$packageAggregation' => 'An object that contains details about an aggregation request based on operating system package type.
', ], ], 'PackageAggregationResponse' => [ 'base' => 'A response that contains the results of a finding aggregation by image layer.
', 'refs' => [ 'AggregationResponse$packageAggregation' => 'An object that contains details about an aggregation response based on operating system package type.
', ], ], 'PackageArchitecture' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$arch' => 'The architecture of the vulnerable package.
', ], ], 'PackageEpoch' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$epoch' => 'The epoch of the vulnerable package.
', ], ], 'PackageFilter' => [ 'base' => 'Contains information on the details of a package filter.
', 'refs' => [ 'PackageFilterList$member' => NULL, ], ], 'PackageFilterList' => [ 'base' => NULL, 'refs' => [ 'FilterCriteria$vulnerablePackages' => 'Details on the vulnerable packages used to filter findings.
', ], ], 'PackageManager' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$packageManager' => 'The package manager of the vulnerable package.
', ], ], 'PackageName' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$name' => 'The name of the vulnerable package.
', ], ], 'PackageRelease' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$release' => 'The release of the vulnerable package.
', ], ], 'PackageSortBy' => [ 'base' => NULL, 'refs' => [ 'PackageAggregation$sortBy' => 'The value to sort results by.
', ], ], 'PackageType' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$packageType' => 'The type of deployment package. Set to Image
for container image and set Zip
for .zip file archive.
The version of the package that contains the vulnerability fix.
', 'VulnerablePackage$version' => 'The version of the vulnerable package.
', ], ], 'PackageVulnerabilityDetails' => [ 'base' => 'Information about a package vulnerability finding.
', 'refs' => [ 'Finding$packageVulnerabilityDetails' => 'An object that contains the details of a package vulnerability finding.
', ], ], 'Path' => [ 'base' => NULL, 'refs' => [ 'PathList$member' => NULL, ], ], 'PathList' => [ 'base' => NULL, 'refs' => [ 'GetEc2DeepInspectionConfigurationResponse$orgPackagePaths' => 'The Amazon Inspector deep inspection custom paths for your organization.
', 'GetEc2DeepInspectionConfigurationResponse$packagePaths' => 'The Amazon Inspector deep inspection custom paths for your account.
', 'UpdateEc2DeepInspectionConfigurationRequest$packagePaths' => 'The Amazon Inspector deep inspection custom paths you are adding for your account.
', 'UpdateEc2DeepInspectionConfigurationResponse$orgPackagePaths' => 'The current Amazon Inspector deep inspection custom paths for the organization.
', 'UpdateEc2DeepInspectionConfigurationResponse$packagePaths' => 'The current Amazon Inspector deep inspection custom paths for your account.
', 'UpdateOrgEc2DeepInspectionConfigurationRequest$orgPackagePaths' => 'The Amazon Inspector deep inspection custom paths you are adding for your organization.
', ], ], 'Permission' => [ 'base' => 'Contains information on the permissions an account has within Amazon Inspector.
', 'refs' => [ 'Permissions$member' => NULL, ], ], 'Permissions' => [ 'base' => NULL, 'refs' => [ 'ListAccountPermissionsResponse$permissions' => 'Contains details on the permissions an account has to configure Amazon Inspector.
', ], ], 'Platform' => [ 'base' => NULL, 'refs' => [ 'AwsEc2InstanceDetails$platform' => 'The platform of the Amazon EC2 instance.
', 'AwsEcrContainerImageDetails$platform' => 'The platform of the Amazon ECR container image.
', ], ], 'PlatformFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByChecksFilterCriteria$platformFilters' => 'The criteria\'s platform filters.
', 'CisScanResultsAggregatedByTargetResourceFilterCriteria$platformFilters' => 'The criteria\'s platform filters.
', ], ], 'PlatformVersion' => [ 'base' => NULL, 'refs' => [ 'ComputePlatform$version' => 'The compute platform version.
', ], ], 'Port' => [ 'base' => NULL, 'refs' => [ 'PortRange$begin' => 'The beginning port in a port range.
', 'PortRange$end' => 'The ending port in a port range.
', 'PortRangeFilter$beginInclusive' => 'The port number the port range begins at.
', 'PortRangeFilter$endInclusive' => 'The port number the port range ends at.
', ], ], 'PortRange' => [ 'base' => 'Details about the port range associated with a finding.
', 'refs' => [ 'NetworkReachabilityDetails$openPortRange' => 'An object that contains details about the open port range associated with a finding.
', ], ], 'PortRangeFilter' => [ 'base' => 'An object that describes the details of a port range filter.
', 'refs' => [ 'PortRangeFilterList$member' => NULL, ], ], 'PortRangeFilterList' => [ 'base' => NULL, 'refs' => [ 'FilterCriteria$portRange' => 'Details on the port ranges used to filter findings.
', ], ], 'Product' => [ 'base' => NULL, 'refs' => [ 'ComputePlatform$product' => 'The compute platform product.
', ], ], 'Reason' => [ 'base' => NULL, 'refs' => [ 'StopCisSessionMessage$reason' => 'The reason for the message.
', ], ], 'Recommendation' => [ 'base' => 'Details about the recommended course of action to remediate the finding.
', 'refs' => [ 'Remediation$recommendation' => 'An object that contains information about the recommended course of action to remediate the finding.
', ], ], 'ReferenceUrls' => [ 'base' => NULL, 'refs' => [ 'CodeVulnerabilityDetails$referenceUrls' => 'A URL containing supporting documentation about the code vulnerability detected.
', ], ], 'RelatedVulnerabilities' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$relatedVulnerabilities' => 'A list of related vulnerabilities.
', ], ], 'RelatedVulnerability' => [ 'base' => NULL, 'refs' => [ 'RelatedVulnerabilities$member' => NULL, ], ], 'RelationshipStatus' => [ 'base' => NULL, 'refs' => [ 'DelegatedAdmin$relationshipStatus' => 'The status of the Amazon Inspector delegated administrator.
', 'Member$relationshipStatus' => 'The status of the member account.
', ], ], 'Remediation' => [ 'base' => 'Information on how to remediate a finding.
', 'refs' => [ 'Finding$remediation' => 'An object that contains the details about how to remediate a finding.
', ], ], 'ReportFormat' => [ 'base' => NULL, 'refs' => [ 'CreateFindingsReportRequest$reportFormat' => 'The format to generate the report in.
', ], ], 'ReportId' => [ 'base' => NULL, 'refs' => [ 'CancelFindingsReportRequest$reportId' => 'The ID of the report to be canceled.
', 'CancelFindingsReportResponse$reportId' => 'The ID of the canceled report.
', 'CancelSbomExportRequest$reportId' => 'The report ID of the SBOM export to cancel.
', 'CancelSbomExportResponse$reportId' => 'The report ID of the canceled SBOM export.
', 'CreateFindingsReportResponse$reportId' => 'The ID of the report.
', 'CreateSbomExportResponse$reportId' => 'The report ID for the software bill of materials (SBOM) report.
', 'GetFindingsReportStatusRequest$reportId' => 'The ID of the report to retrieve the status of.
', 'GetFindingsReportStatusResponse$reportId' => 'The ID of the report.
', 'GetSbomExportRequest$reportId' => 'The report ID of the SBOM export to get details for.
', 'GetSbomExportResponse$reportId' => 'The report ID of the software bill of materials (SBOM) report.
', ], ], 'ReportTargetAccounts' => [ 'base' => NULL, 'refs' => [ 'GetCisScanReportRequest$targetAccounts' => 'The target accounts.
', ], ], 'ReportingErrorCode' => [ 'base' => NULL, 'refs' => [ 'GetFindingsReportStatusResponse$errorCode' => 'The error code of the report.
', 'GetSbomExportResponse$errorCode' => 'An error code.
', ], ], 'RepositoryAggregation' => [ 'base' => 'The details that define an aggregation based on repository.
', 'refs' => [ 'AggregationRequest$repositoryAggregation' => 'An object that contains details about an aggregation request based on Amazon ECR repositories.
', ], ], 'RepositoryAggregationResponse' => [ 'base' => 'A response that contains details on the results of a finding aggregation by repository.
', 'refs' => [ 'AggregationResponse$repositoryAggregation' => 'An object that contains details about an aggregation response based on Amazon ECR repositories.
', ], ], 'RepositorySortBy' => [ 'base' => NULL, 'refs' => [ 'RepositoryAggregation$sortBy' => 'The value to sort results by.
', ], ], 'ResetEncryptionKeyRequest' => [ 'base' => NULL, 'refs' => [], ], 'ResetEncryptionKeyResponse' => [ 'base' => NULL, 'refs' => [], ], 'Resource' => [ 'base' => 'Details about the resource involved in a finding.
', 'refs' => [ 'ResourceList$member' => NULL, ], ], 'ResourceDetails' => [ 'base' => 'Contains details about the resource involved in the finding.
', 'refs' => [ 'Resource$details' => 'An object that contains details about the resource involved in a finding.
', ], ], 'ResourceFilterCriteria' => [ 'base' => 'The resource filter criteria for a Software bill of materials (SBOM) report.
', 'refs' => [ 'CreateSbomExportRequest$resourceFilterCriteria' => 'The resource filter criteria for the software bill of materials (SBOM) report.
', 'GetSbomExportResponse$filterCriteria' => 'Contains details about the resource filter criteria used for the software bill of materials (SBOM) report.
', ], ], 'ResourceId' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetails$targetResourceId' => 'The CIS scan result details\' target resource ID.
', 'CisTargetResourceAggregation$targetResourceId' => 'The ID of the target resource.
', 'CoveredResource$resourceId' => 'The ID of the covered resource.
', 'GetCisScanResultDetailsRequest$targetResourceId' => 'The target resource ID.
', ], ], 'ResourceIdFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$targetResourceIdFilters' => 'The criteria\'s target resource ID filters.
', 'ListCisScansFilterCriteria$targetResourceIdFilters' => 'The list of target resource ID filters.
', ], ], 'ResourceList' => [ 'base' => NULL, 'refs' => [ 'Finding$resources' => 'Contains information on the resources involved in a finding. The resource
value determines the valid values for type
in your request. For more information, see Finding types in the Amazon Inspector user guide.
The filter\'s comparison.
', ], ], 'ResourceMapFilter' => [ 'base' => 'A resource map filter for a software bill of material report.
', 'refs' => [ 'ResourceMapFilterList$member' => NULL, ], ], 'ResourceMapFilterList' => [ 'base' => NULL, 'refs' => [ 'ResourceFilterCriteria$ec2InstanceTags' => 'The EC2 instance tags used as resource filter criteria.
', 'ResourceFilterCriteria$lambdaFunctionTags' => 'The Amazon Web Services Lambda function tags used as resource filter criteria.
', ], ], 'ResourceNotFoundException' => [ 'base' => 'The operation tried to access an invalid resource. Make sure the resource is specified correctly.
', 'refs' => [], ], 'ResourceScanMetadata' => [ 'base' => 'An object that contains details about the metadata for an Amazon ECR resource.
', 'refs' => [ 'CoveredResource$resourceMetadata' => 'An object that contains details about the metadata.
', ], ], 'ResourceScanType' => [ 'base' => NULL, 'refs' => [ 'DisableResourceTypeList$member' => NULL, 'EnableResourceTypeList$member' => NULL, ], ], 'ResourceState' => [ 'base' => 'Details the state of Amazon Inspector for each resource type Amazon Inspector scans.
', 'refs' => [ 'AccountState$resourceState' => 'An object detailing which resources Amazon Inspector is enabled to scan for the account.
', ], ], 'ResourceStatus' => [ 'base' => 'Details the status of Amazon Inspector for each resource type Amazon Inspector scans.
', 'refs' => [ 'Account$resourceStatus' => 'Details of the status of Amazon Inspector scans by resource type.
', 'FailedAccount$resourceStatus' => 'An object detailing which resources Amazon Inspector is enabled to scan for the account.
', ], ], 'ResourceStringComparison' => [ 'base' => NULL, 'refs' => [ 'ResourceStringFilter$comparison' => 'The filter\'s comparison.
', ], ], 'ResourceStringFilter' => [ 'base' => 'A resource string filter for a software bill of materials report.
', 'refs' => [ 'ResourceStringFilterList$member' => NULL, ], ], 'ResourceStringFilterList' => [ 'base' => NULL, 'refs' => [ 'ResourceFilterCriteria$accountId' => 'The account IDs used as resource filter criteria.
', 'ResourceFilterCriteria$ecrImageTags' => 'The ECR image tags used as resource filter criteria.
', 'ResourceFilterCriteria$ecrRepositoryName' => 'The ECR repository names used as resource filter criteria.
', 'ResourceFilterCriteria$lambdaFunctionName' => 'The Amazon Web Services Lambda function name used as resource filter criteria.
', 'ResourceFilterCriteria$resourceId' => 'The resource IDs used as resource filter criteria.
', 'ResourceFilterCriteria$resourceType' => 'The resource types used as resource filter criteria.
', ], ], 'ResourceStringInput' => [ 'base' => NULL, 'refs' => [ 'ResourceStringFilter$value' => 'The filter\'s value.
', ], ], 'ResourceTagFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$targetResourceTagFilters' => 'The criteria\'s target resource tag filters.
', 'ListCisScanConfigurationsFilterCriteria$targetResourceTagFilters' => 'The list of target resource tag filters.
', 'ListCisScansFilterCriteria$targetResourceTagFilters' => 'The list of target resource tag filters.
', ], ], 'ResourceType' => [ 'base' => NULL, 'refs' => [ 'GetEncryptionKeyRequest$resourceType' => 'The resource type the key encrypts.
', 'ResetEncryptionKeyRequest$resourceType' => 'The resource type the key encrypts.
', 'Resource$type' => 'The type of resource.
', 'UpdateEncryptionKeyRequest$resourceType' => 'The resource type for the encryption key.
', ], ], 'RiskScore' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$riskScore' => 'The risk score of the vulnerability.
', ], ], 'RuleId' => [ 'base' => NULL, 'refs' => [ 'CisSessionMessage$ruleId' => 'The rule ID for the CIS session message.
', ], ], 'Runtime' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$runtime' => 'The runtime environment for the Amazon Web Services Lambda function.
', 'LambdaFunctionMetadata$runtime' => 'An Amazon Web Services Lambda function\'s runtime.
', ], ], 'SbomReportFormat' => [ 'base' => NULL, 'refs' => [ 'CreateSbomExportRequest$reportFormat' => 'The output format for the software bill of materials (SBOM) report.
', 'GetSbomExportResponse$format' => 'The format of the software bill of materials (SBOM) report.
', ], ], 'ScanStatus' => [ 'base' => 'The status of the scan.
', 'refs' => [ 'CoveredResource$scanStatus' => 'The status of the scan covering the resource.
', ], ], 'ScanStatusCode' => [ 'base' => NULL, 'refs' => [ 'ScanStatus$statusCode' => 'The status code of the scan.
', ], ], 'ScanStatusReason' => [ 'base' => NULL, 'refs' => [ 'ScanStatus$reason' => 'The scan status. Possible return values and descriptions are:
PENDING_INITIAL_SCAN
- This resource has been identified for scanning, results will be available soon.
ACCESS_DENIED
- Resource access policy restricting Amazon Inspector access. Please update the IAM policy.
INTERNAL_ERROR
- Amazon Inspector has encountered an internal error for this resource. Amazon Inspector service will automatically resolve the issue and resume the scanning. No action required from the user.
UNMANAGED_EC2_INSTANCE
- The EC2 instance is not managed by SSM, please use the following SSM automation to remediate the issue: https://docs.aws.amazon.com/systems-manager-automation-runbooks/latest/userguide/automation-awssupport-troubleshoot-managed-instance.html. Once the instance becomes managed by SSM, Inspector will automatically begin scanning this instance.
UNSUPPORTED_OS
- Amazon Inspector does not support this OS, architecture, or image manifest type at this time. To see a complete list of supported operating systems see: https://docs.aws.amazon.com/inspector/latest/user/supported.html.
SCAN_ELIGIBILITY_EXPIRED
- The configured scan duration has lapsed for this image.
RESOURCE_TERMINATED
- This resource has been terminated. The findings and coverage associated with this resource are in the process of being cleaned up.
SUCCESSFUL
- The scan was successful.
NO_RESOURCES_FOUND
- Reserved for future use.
IMAGE_SIZE_EXCEEDED
- Reserved for future use.
SCAN_FREQUENCY_MANUAL
- This image will not be covered by Amazon Inspector due to the repository scan frequency configuration.
SCAN_FREQUENCY_SCAN_ON_PUSH
- This image will be scanned one time and will not new findings because of the scan frequency configuration.
EC2_INSTANCE_STOPPED
- This EC2 instance is in a stopped state, therefore, Amazon Inspector will pause scanning. The existing findings will continue to exist until the instance is terminated. Once the instance is re-started, Inspector will automatically start scanning the instance again. Please note that you will not be charged for this instance while it’s in a stopped state.
PENDING_DISABLE
- This resource is pending cleanup during disablement. The customer will not be billed while a resource is in the pending disable status.
NO INVENTORY
- Amazon Inspector couldn’t find software application inventory to scan for vulnerabilities. This might be caused due to required Amazon Inspector associations being deleted or failing to run on your resource. Please verify the status of InspectorInventoryCollection-do-not-delete
association in the SSM console for the resource. Additionally, you can verify the instance’s inventory in the SSM Fleet Manager console.
STALE_INVENTORY
- Amazon Inspector wasn’t able to collect an updated software application inventory in the last 7 days. Please confirm the required Amazon Inspector associations still exist and you can still see an updated inventory in the SSM console.
EXCLUDED_BY_TAG
- This resource was not scanned because it has been excluded by a tag.
UNSUPPORTED_RUNTIME
- The function was not scanned because it has an unsupported runtime. To see a complete list of supported runtimes see: https://docs.aws.amazon.com/inspector/latest/user/supported.html.
UNSUPPORTED_MEDIA_TYPE
- The ECR image has an unsupported media type.
UNSUPPORTED_CONFIG_FILE
- Reserved for future use.
DEEP_INSPECTION_PACKAGE_COLLECTION_LIMIT_EXCEEDED
- The instance has exceeded the 5000 package limit for Amazon Inspector Deep inspection. To resume Deep inspection for this instance you can try to adjust the custom paths associated with the account.
DEEP_INSPECTION_DAILY_SSM_INVENTORY_LIMIT_EXCEEDED
- The SSM agent couldn\'t send inventory to Amazon Inspector because the SSM quota for Inventory data collected per instance per day has already been reached for this instance.
DEEP_INSPECTION_COLLECTION_TIME_LIMIT_EXCEEDED
- Amazon Inspector failed to extract the package inventory because the package collection time exceeding the maximum threshold of 15 minutes.
DEEP_INSPECTION_NO_INVENTORY
The Amazon Inspector plugin hasn\'t yet been able to collect an inventory of packages for this instance. This is usually the result of a pending scan, however, if this status persists after 6 hours, use SSM to ensure that the required Amazon Inspector associations exist and are running for the instance.
The Amazon Inspector scan type covering the resource.
', 'GetEncryptionKeyRequest$scanType' => 'The scan type the key encrypts.
', 'ResetEncryptionKeyRequest$scanType' => 'The scan type the key encrypts.
', 'UpdateEncryptionKeyRequest$scanType' => 'The scan type for the encryption key.
', ], ], 'Schedule' => [ 'base' => 'A schedule.
', 'refs' => [ 'CisScanConfiguration$schedule' => 'The CIS scan configuration\'s schedule.
', 'CreateCisScanConfigurationRequest$schedule' => 'The schedule for the CIS scan configuration.
', 'UpdateCisScanConfigurationRequest$schedule' => 'The schedule for the CIS scan configuration.
', ], ], 'SearchVulnerabilitiesFilterCriteria' => [ 'base' => 'Details on the criteria used to define the filter for a vulnerability search.
', 'refs' => [ 'SearchVulnerabilitiesRequest$filterCriteria' => 'The criteria used to filter the results of a vulnerability search.
', ], ], 'SearchVulnerabilitiesRequest' => [ 'base' => NULL, 'refs' => [], ], 'SearchVulnerabilitiesResponse' => [ 'base' => NULL, 'refs' => [], ], 'SecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'SecurityGroupIdList$member' => NULL, ], ], 'SecurityGroupIdList' => [ 'base' => NULL, 'refs' => [ 'LambdaVpcConfig$securityGroupIds' => 'The VPC security groups and subnets that are attached to an Amazon Web Services Lambda function. For more information, see VPC Settings.
', ], ], 'SendCisSessionHealthRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendCisSessionHealthResponse' => [ 'base' => NULL, 'refs' => [], ], 'SendCisSessionTelemetryRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendCisSessionTelemetryResponse' => [ 'base' => NULL, 'refs' => [], ], 'Service' => [ 'base' => NULL, 'refs' => [ 'ListAccountPermissionsRequest$service' => 'The service scan type to check permissions for.
', 'Permission$service' => 'The services that the permissions allow an account to perform the given operations for.
', ], ], 'ServiceQuotaExceededException' => [ 'base' => 'You have exceeded your service quota. To perform the requested action, remove some of the relevant resources, or use Service Quotas to request a service quota increase.
', 'refs' => [], ], 'Severity' => [ 'base' => NULL, 'refs' => [ 'Finding$severity' => 'The severity of the finding. UNTRIAGED
applies to PACKAGE_VULNERABILITY
type findings that the vendor has not assigned a severity yet. For more information, see Severity levels for findings in the Amazon Inspector user guide.
An object that contains the counts of aggregated finding per severity.
', 'refs' => [ 'AccountAggregationResponse$severityCounts' => 'The number of findings by severity.
', 'AmiAggregationResponse$severityCounts' => 'An object that contains the count of matched findings per severity.
', 'AwsEcrContainerAggregationResponse$severityCounts' => 'The number of finding by severity.
', 'Ec2InstanceAggregationResponse$severityCounts' => 'An object that contains the count of matched findings per severity.
', 'FindingTypeAggregationResponse$severityCounts' => 'The value to sort results by.
', 'ImageLayerAggregationResponse$severityCounts' => 'An object that represents the count of matched findings per severity.
', 'LambdaFunctionAggregationResponse$severityCounts' => NULL, 'LambdaLayerAggregationResponse$severityCounts' => NULL, 'PackageAggregationResponse$severityCounts' => 'An object that contains the count of matched findings per severity.
', 'RepositoryAggregationResponse$severityCounts' => 'An object that represent the count of matched findings per severity.
', 'TitleAggregationResponse$severityCounts' => 'An object that represent the count of matched findings per severity.
', ], ], 'SortCriteria' => [ 'base' => 'Details about the criteria used to sort finding results.
', 'refs' => [ 'ListFindingsRequest$sortCriteria' => 'Details on the sort criteria to apply to your finding results.
', ], ], 'SortField' => [ 'base' => NULL, 'refs' => [ 'SortCriteria$field' => 'The finding detail field by which results are sorted.
', ], ], 'SortOrder' => [ 'base' => NULL, 'refs' => [ 'AccountAggregation$sortOrder' => 'The sort order (ascending or descending).
', 'AmiAggregation$sortOrder' => 'The order to sort results by.
', 'AwsEcrContainerAggregation$sortOrder' => 'The sort order (ascending or descending).
', 'Ec2InstanceAggregation$sortOrder' => 'The order to sort results by.
', 'FindingTypeAggregation$sortOrder' => 'The order to sort results by.
', 'ImageLayerAggregation$sortOrder' => 'The order to sort results by.
', 'LambdaFunctionAggregation$sortOrder' => 'The order to use for sorting the results.
', 'LambdaLayerAggregation$sortOrder' => 'The order to use for sorting the results.
', 'PackageAggregation$sortOrder' => 'The order to sort results by.
', 'RepositoryAggregation$sortOrder' => 'The order to sort results by.
', 'SortCriteria$sortOrder' => 'The order by which findings are sorted.
', 'TitleAggregation$sortOrder' => 'The order to sort results by.
', ], ], 'SourceLayerHash' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$sourceLayerHash' => 'The source layer hash of the vulnerable package.
', ], ], 'StartCisSessionMessage' => [ 'base' => 'The start CIS session message.
', 'refs' => [ 'StartCisSessionRequest$message' => 'The start CIS session message.
', ], ], 'StartCisSessionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartCisSessionResponse' => [ 'base' => NULL, 'refs' => [], ], 'State' => [ 'base' => 'An object that described the state of Amazon Inspector scans for an account.
', 'refs' => [ 'AccountState$state' => 'An object detailing the status of Amazon Inspector for the account.
', 'ResourceState$ec2' => 'An object detailing the state of Amazon Inspector scanning for Amazon EC2 resources.
', 'ResourceState$ecr' => 'An object detailing the state of Amazon Inspector scanning for Amazon ECR resources.
', 'ResourceState$lambda' => NULL, 'ResourceState$lambdaCode' => NULL, ], ], 'Status' => [ 'base' => NULL, 'refs' => [ 'Account$status' => 'The status of Amazon Inspector for the account.
', 'FailedAccount$status' => 'The status of Amazon Inspector for the account.
', 'FailedMemberAccountEc2DeepInspectionStatusState$ec2ScanStatus' => 'The status of EC2 scanning in the account that failed to activate Amazon Inspector deep inspection.
', 'ResourceStatus$ec2' => 'The status of Amazon Inspector scanning for Amazon EC2 resources.
', 'ResourceStatus$ecr' => 'The status of Amazon Inspector scanning for Amazon ECR resources.
', 'ResourceStatus$lambda' => 'The status of Amazon Inspector scanning for Amazon Web Services Lambda function.
', 'ResourceStatus$lambdaCode' => 'The status of Amazon Inspector scanning for custom application code for Amazon Web Services Lambda functions.
', 'State$status' => 'The status of Amazon Inspector for the account.
', ], ], 'StatusCounts' => [ 'base' => 'The status counts.
', 'refs' => [ 'CisCheckAggregation$statusCounts' => 'The CIS check status counts.
', 'CisTargetResourceAggregation$statusCounts' => 'The target resource status counts.
', ], ], 'Step' => [ 'base' => 'Details about the step associated with a finding.
', 'refs' => [ 'StepList$member' => NULL, ], ], 'StepList' => [ 'base' => NULL, 'refs' => [ 'NetworkPath$steps' => 'The details on the steps in the network path.
', ], ], 'StopCisMessageProgress' => [ 'base' => 'The stop CIS message progress.
', 'refs' => [ 'StopCisSessionMessage$progress' => 'The progress of the message.
', ], ], 'StopCisSessionMessage' => [ 'base' => 'The stop CIS session message.
', 'refs' => [ 'StopCisSessionRequest$message' => 'The stop CIS session message.
', ], ], 'StopCisSessionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopCisSessionResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopCisSessionStatus' => [ 'base' => NULL, 'refs' => [ 'StopCisSessionMessage$status' => 'The status of the message.
', ], ], 'String' => [ 'base' => NULL, 'refs' => [ 'AccessDeniedException$message' => NULL, 'AwsEcrContainerAggregationResponse$architecture' => 'The architecture of the container.
', 'AwsEcrContainerAggregationResponse$imageSha' => 'The SHA value of the container image.
', 'AwsEcrContainerAggregationResponse$repository' => 'The container repository.
', 'AwsEcrContainerImageDetails$author' => 'The image author of the Amazon ECR container image.
', 'BadRequestException$message' => NULL, 'CisCheckAggregation$checkDescription' => 'The description for the CIS check.
', 'CisCheckAggregation$checkId' => 'The check ID for the CIS check.
', 'CisCheckAggregation$platform' => 'The CIS check platform.
', 'CisCheckAggregation$title' => 'The CIS check title.
', 'CisScan$scheduledBy' => 'The account or organization that schedules the CIS scan.
', 'CisScanResultDetails$checkDescription' => 'The account ID that\'s associated with the CIS scan result details.
', 'CisScanResultDetails$checkId' => 'The CIS scan result details\' check ID.
', 'CisScanResultDetails$platform' => 'The CIS scan result details\' platform.
', 'CisScanResultDetails$remediation' => 'The CIS scan result details\' remediation.
', 'CisScanResultDetails$statusReason' => 'The CIS scan result details\' status reason.
', 'CisScanResultDetails$title' => 'The CIS scan result details\' title.
', 'CisStringFilter$value' => 'The value of the CIS string filter.
', 'CisTargetResourceAggregation$platform' => 'The platform for the CIS target resource.
', 'ConflictException$message' => NULL, 'ConflictException$resourceId' => 'The ID of the conflicting resource.
', 'ConflictException$resourceType' => 'The type of the conflicting resource.
', 'Destination$bucketName' => 'The name of the Amazon S3 bucket to export findings to.
', 'Destination$keyPrefix' => 'The prefix that the findings will be written under.
', 'Destination$kmsKeyArn' => 'The ARN of the KMS key used to encrypt data when exporting findings.
', 'Ec2InstanceAggregationResponse$accountId' => 'The Amazon Web Services account for the Amazon EC2 instance.
', 'Ec2InstanceAggregationResponse$operatingSystem' => 'The operating system of the Amazon EC2 instance.
', 'EcrRepositoryMetadata$name' => 'The name of the Amazon ECR repository.
', 'FreeTrialInfoError$message' => 'The error message returned.
', 'GetCisScanReportResponse$url' => 'The URL where the CIS scan report PDF can be downloaded.
', 'InternalServerException$message' => NULL, 'LambdaFunctionAggregationResponse$functionName' => 'The Amazon Web Services Lambda function names included in the aggregation results.
', 'LambdaFunctionAggregationResponse$runtime' => 'The runtimes included in the aggregation results.
', 'LambdaFunctionMetadata$functionName' => 'The name of a function.
', 'LambdaLayerList$member' => NULL, 'ResourceNotFoundException$message' => NULL, 'ServiceQuotaExceededException$message' => NULL, 'ServiceQuotaExceededException$resourceId' => 'The ID of the resource that exceeds a service quota.
', 'TagList$member' => NULL, 'TagValueList$member' => NULL, 'ThrottlingException$message' => NULL, 'TitleAggregationResponse$vulnerabilityId' => 'The vulnerability ID of the finding.
', 'ValidationException$message' => NULL, 'ValidationExceptionField$message' => 'The validation exception message.
', 'ValidationExceptionField$name' => 'The name of the validation exception.
', ], ], 'StringComparison' => [ 'base' => NULL, 'refs' => [ 'StringFilter$comparison' => 'The operator to use when comparing values in the filter.
', ], ], 'StringFilter' => [ 'base' => 'An object that describes the details of a string filter.
', 'refs' => [ 'PackageFilter$architecture' => 'An object that contains details on the package architecture type to filter on.
', 'PackageFilter$name' => 'An object that contains details on the name of the package to filter on.
', 'PackageFilter$release' => 'An object that contains details on the package release to filter on.
', 'PackageFilter$sourceLambdaLayerArn' => NULL, 'PackageFilter$sourceLayerHash' => 'An object that contains details on the source layer hash to filter on.
', 'PackageFilter$version' => 'The package version to filter on.
', 'StringFilterList$member' => NULL, ], ], 'StringFilterList' => [ 'base' => NULL, 'refs' => [ 'AmiAggregation$amis' => 'The IDs of AMIs to aggregate findings for.
', 'AwsEcrContainerAggregation$architectures' => 'The architecture of the containers.
', 'AwsEcrContainerAggregation$imageShas' => 'The image SHA values.
', 'AwsEcrContainerAggregation$imageTags' => 'The image tags.
', 'AwsEcrContainerAggregation$repositories' => 'The container repositories.
', 'AwsEcrContainerAggregation$resourceIds' => 'The container resource IDs.
', 'Ec2InstanceAggregation$amis' => 'The AMI IDs associated with the Amazon EC2 instances to aggregate findings for.
', 'Ec2InstanceAggregation$instanceIds' => 'The Amazon EC2 instance IDs to aggregate findings for.
', 'Ec2InstanceAggregation$operatingSystems' => 'The operating system types to aggregate findings for. Valid values must be uppercase and underscore separated, examples are ORACLE_LINUX_7
and ALPINE_LINUX_3_8
.
Details of the Amazon Web Services account IDs used to filter findings.
', 'FilterCriteria$codeVulnerabilityDetectorName' => 'The name of the detector used to identify a code vulnerability in a Lambda function used to filter findings.
', 'FilterCriteria$codeVulnerabilityDetectorTags' => 'The detector type tag associated with the vulnerability used to filter findings. Detector tags group related vulnerabilities by common themes or tactics. For a list of available tags by programming language, see Java tags, or Python tags.
', 'FilterCriteria$codeVulnerabilityFilePath' => 'The file path to the file in a Lambda function that contains a code vulnerability used to filter findings.
', 'FilterCriteria$componentId' => 'Details of the component IDs used to filter findings.
', 'FilterCriteria$componentType' => 'Details of the component types used to filter findings.
', 'FilterCriteria$ec2InstanceImageId' => 'Details of the Amazon EC2 instance image IDs used to filter findings.
', 'FilterCriteria$ec2InstanceSubnetId' => 'Details of the Amazon EC2 instance subnet IDs used to filter findings.
', 'FilterCriteria$ec2InstanceVpcId' => 'Details of the Amazon EC2 instance VPC IDs used to filter findings.
', 'FilterCriteria$ecrImageArchitecture' => 'Details of the Amazon ECR image architecture types used to filter findings.
', 'FilterCriteria$ecrImageHash' => 'Details of the Amazon ECR image hashes used to filter findings.
', 'FilterCriteria$ecrImageRegistry' => 'Details on the Amazon ECR registry used to filter findings.
', 'FilterCriteria$ecrImageRepositoryName' => 'Details on the name of the Amazon ECR repository used to filter findings.
', 'FilterCriteria$ecrImageTags' => 'The tags attached to the Amazon ECR container image.
', 'FilterCriteria$exploitAvailable' => 'Filters the list of Amazon Web Services Lambda findings by the availability of exploits.
', 'FilterCriteria$findingArn' => 'Details on the finding ARNs used to filter findings.
', 'FilterCriteria$findingStatus' => 'Details on the finding status types used to filter findings.
', 'FilterCriteria$findingType' => 'Details on the finding types used to filter findings.
', 'FilterCriteria$fixAvailable' => 'Details on whether a fix is available through a version update. This value can be YES
, NO
, or PARTIAL
. A PARTIAL
fix means that some, but not all, of the packages identified in the finding have fixes available through updated versions.
Filters the list of Amazon Web Services Lambda functions by execution role.
', 'FilterCriteria$lambdaFunctionLayers' => 'Filters the list of Amazon Web Services Lambda functions by the function\'s layers. A Lambda function can have up to five layers.
', 'FilterCriteria$lambdaFunctionName' => 'Filters the list of Amazon Web Services Lambda functions by the name of the function.
', 'FilterCriteria$lambdaFunctionRuntime' => 'Filters the list of Amazon Web Services Lambda functions by the runtime environment for the Lambda function.
', 'FilterCriteria$networkProtocol' => 'Details on network protocol used to filter findings.
', 'FilterCriteria$relatedVulnerabilities' => 'Details on the related vulnerabilities used to filter findings.
', 'FilterCriteria$resourceId' => 'Details on the resource IDs used to filter findings.
', 'FilterCriteria$resourceType' => 'Details on the resource types used to filter findings.
', 'FilterCriteria$severity' => 'Details on the severity used to filter findings.
', 'FilterCriteria$title' => 'Details on the finding title used to filter findings.
', 'FilterCriteria$vendorSeverity' => 'Details on the vendor severity used to filter findings.
', 'FilterCriteria$vulnerabilityId' => 'Details on the vulnerability ID used to filter findings.
', 'FilterCriteria$vulnerabilitySource' => 'Details on the vulnerability type used to filter findings.
', 'ImageLayerAggregation$layerHashes' => 'The hashes associated with the layers.
', 'ImageLayerAggregation$repositories' => 'The repository associated with the container image hosting the layers.
', 'ImageLayerAggregation$resourceIds' => 'The ID of the container image layer.
', 'LambdaFunctionAggregation$functionNames' => 'The Amazon Web Services Lambda function names to include in the aggregation results.
', 'LambdaFunctionAggregation$resourceIds' => 'The resource IDs to include in the aggregation results.
', 'LambdaFunctionAggregation$runtimes' => 'Returns findings aggregated by Amazon Web Services Lambda function runtime environments.
', 'LambdaLayerAggregation$functionNames' => 'The names of the Amazon Web Services Lambda functions associated with the layers.
', 'LambdaLayerAggregation$layerArns' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Lambda function layer.
', 'LambdaLayerAggregation$resourceIds' => 'The resource IDs for the Amazon Web Services Lambda function layers.
', 'ListFindingAggregationsRequest$accountIds' => 'The Amazon Web Services account IDs to retrieve finding aggregation data for.
', 'PackageAggregation$packageNames' => 'The names of packages to aggregate findings on.
', 'RepositoryAggregation$repositories' => 'The names of repositories to aggregate findings on.
', 'TitleAggregation$titles' => 'The finding titles to aggregate on.
', 'TitleAggregation$vulnerabilityIds' => 'The vulnerability IDs of the findings.
', ], ], 'StringInput' => [ 'base' => NULL, 'refs' => [ 'StringFilter$value' => 'The value to filter on.
', ], ], 'StringList' => [ 'base' => NULL, 'refs' => [ 'AwsEcrContainerAggregationResponse$imageTags' => 'The container image stags.
', ], ], 'SubnetId' => [ 'base' => NULL, 'refs' => [ 'SubnetIdList$member' => NULL, ], ], 'SubnetIdList' => [ 'base' => NULL, 'refs' => [ 'LambdaVpcConfig$subnetIds' => 'A list of VPC subnet IDs.
', ], ], 'SuggestedFix' => [ 'base' => 'A suggested fix for a vulnerability in your Lambda function code.
', 'refs' => [ 'SuggestedFixes$member' => NULL, ], ], 'SuggestedFixCodeString' => [ 'base' => NULL, 'refs' => [ 'SuggestedFix$code' => 'The fix\'s code.
', ], ], 'SuggestedFixDescriptionString' => [ 'base' => NULL, 'refs' => [ 'SuggestedFix$description' => 'The fix\'s description.
', ], ], 'SuggestedFixes' => [ 'base' => NULL, 'refs' => [ 'CodeSnippetResult$suggestedFixes' => 'Details of a suggested code fix.
', ], ], 'TagComparison' => [ 'base' => NULL, 'refs' => [ 'TagFilter$comparison' => 'The tag filter comparison value.
', ], ], 'TagFilter' => [ 'base' => 'The tag filter.
', 'refs' => [ 'ResourceTagFilterList$member' => NULL, ], ], 'TagKey' => [ 'base' => NULL, 'refs' => [ 'TagKeyList$member' => NULL, ], ], 'TagKeyList' => [ 'base' => NULL, 'refs' => [ 'UntagResourceRequest$tagKeys' => 'The tag keys to remove from the resource.
', ], ], 'TagList' => [ 'base' => NULL, 'refs' => [ 'EcrContainerImageMetadata$tags' => 'Tags associated with the Amazon ECR image metadata.
', ], ], 'TagMap' => [ 'base' => NULL, 'refs' => [ 'CreateFilterRequest$tags' => 'A list of tags for the filter.
', 'Ec2InstanceAggregationResponse$instanceTags' => 'The tags attached to the instance.
', 'Ec2Metadata$tags' => 'The tags attached to the instance.
', 'Filter$tags' => 'The tags attached to the filter.
', 'LambdaFunctionAggregationResponse$lambdaTags' => 'The tags included in the aggregation results.
', 'LambdaFunctionMetadata$functionTags' => 'The resource tags on an Amazon Web Services Lambda function.
', 'ListTagsForResourceResponse$tags' => 'The tags associated with the resource.
', 'Resource$tags' => 'The tags attached to the resource.
', 'TagResourceRequest$tags' => 'The tags to be added to a resource.
', ], ], 'TagResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'TagResourceResponse' => [ 'base' => NULL, 'refs' => [], ], 'TagValueList' => [ 'base' => NULL, 'refs' => [ 'TargetResourceTags$value' => NULL, ], ], 'Target' => [ 'base' => NULL, 'refs' => [ 'Targets$member' => NULL, ], ], 'TargetAccount' => [ 'base' => NULL, 'refs' => [ 'TargetAccountList$member' => NULL, ], ], 'TargetAccountList' => [ 'base' => NULL, 'refs' => [ 'CreateCisTargets$accountIds' => 'The CIS target account ids.
', 'UpdateCisTargets$accountIds' => 'The target account ids.
', ], ], 'TargetResourceTags' => [ 'base' => NULL, 'refs' => [ 'CisTargetResourceAggregation$targetResourceTags' => 'The tag for the target resource.
', 'CisTargets$targetResourceTags' => 'The CIS target resource tags.
', 'CreateCisTargets$targetResourceTags' => 'The CIS target resource tags.
', 'UpdateCisTargets$targetResourceTags' => 'The target resource tags.
', ], ], 'TargetStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$targetStatusFilters' => 'The criteria\'s target status filters.
', ], ], 'TargetStatusReasonFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultsAggregatedByTargetResourceFilterCriteria$targetStatusReasonFilters' => 'The criteria\'s target status reason filters.
', ], ], 'Targets' => [ 'base' => NULL, 'refs' => [ 'AtigData$targets' => 'The commercial sectors this vulnerability targets.
', ], ], 'ThrottlingException' => [ 'base' => 'The limit on the number of requests per second was exceeded.
', 'refs' => [], ], 'Time' => [ 'base' => 'The time.
', 'refs' => [ 'DailySchedule$startTime' => 'The schedule start time.
', 'MonthlySchedule$startTime' => 'The monthly schedule\'s start time.
', 'WeeklySchedule$startTime' => 'The weekly schedule\'s start time.
', ], ], 'TimeOfDay' => [ 'base' => NULL, 'refs' => [ 'Time$timeOfDay' => 'The time of day in 24-hour format (00:00).
', ], ], 'Timestamp' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$lastModifiedAt' => 'The date and time that a user last updated the configuration, in ISO 8601 format
', 'CisDateFilter$earliestScanStartTime' => 'The CIS date filter\'s earliest scan start time.
', 'CisDateFilter$latestScanStartTime' => 'The CIS date filter\'s latest scan start time.
', 'CisScan$scanDate' => 'The CIS scan\'s date.
', 'DateFilter$endInclusive' => 'A timestamp representing the end of the time period filtered on.
', 'DateFilter$startInclusive' => 'A timestamp representing the start of the time period filtered on.
', 'FreeTrialInfo$end' => 'The date and time that the Amazon Inspector free trail ends for a given account.
', 'FreeTrialInfo$start' => 'The date and time that the Amazon Inspector free trail started for a given account.
', ], ], 'Timezone' => [ 'base' => NULL, 'refs' => [ 'Time$timezone' => 'The timezone.
', ], ], 'TitleAggregation' => [ 'base' => 'The details that define an aggregation based on finding title.
', 'refs' => [ 'AggregationRequest$titleAggregation' => 'An object that contains details about an aggregation request based on finding title.
', ], ], 'TitleAggregationResponse' => [ 'base' => 'A response that contains details on the results of a finding aggregation by title.
', 'refs' => [ 'AggregationResponse$titleAggregation' => 'An object that contains details about an aggregation response based on finding title.
', ], ], 'TitleFilterList' => [ 'base' => NULL, 'refs' => [ 'CisScanResultDetailsFilterCriteria$titleFilters' => 'The criteria\'s title filters.
', 'CisScanResultsAggregatedByChecksFilterCriteria$titleFilters' => 'The criteria\'s title filters.
', ], ], 'TitleSortBy' => [ 'base' => NULL, 'refs' => [ 'TitleAggregation$sortBy' => 'The value to sort results by.
', ], ], 'Tool' => [ 'base' => NULL, 'refs' => [ 'Tools$member' => NULL, ], ], 'Tools' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$tools' => 'The known malware tools or kits that can exploit the vulnerability.
', ], ], 'Ttp' => [ 'base' => NULL, 'refs' => [ 'Ttps$member' => NULL, ], ], 'Ttps' => [ 'base' => NULL, 'refs' => [ 'AtigData$ttps' => 'The MITRE ATT&CK tactics, techniques, and procedures (TTPs) associated with vulnerability.
', 'FindingDetail$ttps' => 'The MITRE adversary tactics, techniques, or procedures (TTPs) associated with the vulnerability.
', ], ], 'UUID' => [ 'base' => NULL, 'refs' => [ 'SendCisSessionHealthRequest$scanJobId' => 'A unique identifier for the scan job.
', 'SendCisSessionHealthRequest$sessionToken' => 'The unique token that identifies the CIS session.
', 'SendCisSessionTelemetryRequest$scanJobId' => 'A unique identifier for the scan job.
', 'SendCisSessionTelemetryRequest$sessionToken' => 'The unique token that identifies the CIS session.
', 'StartCisSessionMessage$sessionToken' => 'The unique token that identifies the CIS session.
', 'StartCisSessionRequest$scanJobId' => 'A unique identifier for the scan job.
', 'StopCisSessionRequest$scanJobId' => 'A unique identifier for the scan job.
', 'StopCisSessionRequest$sessionToken' => 'The unique token that identifies the CIS session.
', ], ], 'UntagResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UntagResourceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCisScanConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCisScanConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCisTargets' => [ 'base' => 'Updates CIS targets.
', 'refs' => [ 'UpdateCisScanConfigurationRequest$targets' => 'The targets for the CIS scan configuration.
', ], ], 'UpdateConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEc2DeepInspectionConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEc2DeepInspectionConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEncryptionKeyRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEncryptionKeyResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFilterRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFilterResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateOrgEc2DeepInspectionConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateOrgEc2DeepInspectionConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateOrganizationConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateOrganizationConfigurationResponse' => [ 'base' => NULL, 'refs' => [], ], 'Usage' => [ 'base' => 'Contains usage information about the cost of Amazon Inspector operation.
', 'refs' => [ 'UsageList$member' => NULL, ], ], 'UsageAccountId' => [ 'base' => NULL, 'refs' => [ 'UsageAccountIdList$member' => NULL, ], ], 'UsageAccountIdList' => [ 'base' => NULL, 'refs' => [ 'ListUsageTotalsRequest$accountIds' => 'The Amazon Web Services account IDs to retrieve usage totals for.
', ], ], 'UsageList' => [ 'base' => NULL, 'refs' => [ 'UsageTotal$usage' => 'An object representing the total usage for an account.
', ], ], 'UsageTotal' => [ 'base' => 'The total of usage for an account ID.
', 'refs' => [ 'UsageTotalList$member' => NULL, ], ], 'UsageTotalList' => [ 'base' => NULL, 'refs' => [ 'ListUsageTotalsResponse$totals' => 'An object with details on the total usage for the requested account.
', ], ], 'UsageType' => [ 'base' => NULL, 'refs' => [ 'Usage$type' => 'The type scan.
', ], ], 'UsageValue' => [ 'base' => NULL, 'refs' => [ 'Usage$total' => 'The total of usage.
', ], ], 'ValidationException' => [ 'base' => 'The request has failed validation due to missing required fields or having invalid inputs.
', 'refs' => [], ], 'ValidationExceptionField' => [ 'base' => 'An object that describes a validation exception.
', 'refs' => [ 'ValidationExceptionFields$member' => NULL, ], ], 'ValidationExceptionFields' => [ 'base' => NULL, 'refs' => [ 'ValidationException$fields' => 'The fields that failed validation.
', ], ], 'ValidationExceptionReason' => [ 'base' => NULL, 'refs' => [ 'ValidationException$reason' => 'The reason for the validation failure.
', ], ], 'Vendor' => [ 'base' => NULL, 'refs' => [ 'ComputePlatform$vendor' => 'The compute platform vendor.
', ], ], 'VendorCreatedAt' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$vendorCreatedAt' => 'The date and time when the vendor created this vulnerability.
', ], ], 'VendorSeverity' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$vendorSeverity' => 'The severity assigned by the vendor.
', ], ], 'VendorUpdatedAt' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$vendorUpdatedAt' => 'The date and time when the vendor last updated this vulnerability.
', ], ], 'Version' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaFunctionDetails$version' => 'The version of the Amazon Web Services Lambda function.
', ], ], 'VpcId' => [ 'base' => NULL, 'refs' => [ 'LambdaVpcConfig$vpcId' => 'The ID of the VPC.
', ], ], 'VulnId' => [ 'base' => NULL, 'refs' => [ 'VulnIdList$member' => NULL, ], ], 'VulnIdList' => [ 'base' => NULL, 'refs' => [ 'SearchVulnerabilitiesFilterCriteria$vulnerabilityIds' => 'The IDs for specific vulnerabilities.
', ], ], 'Vulnerabilities' => [ 'base' => NULL, 'refs' => [ 'SearchVulnerabilitiesResponse$vulnerabilities' => 'Details about the listed vulnerability.
', ], ], 'Vulnerability' => [ 'base' => 'Contains details about a specific vulnerability Amazon Inspector can detect.
', 'refs' => [ 'Vulnerabilities$member' => NULL, ], ], 'VulnerabilityDescription' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$description' => 'A description of the vulnerability.
', ], ], 'VulnerabilityId' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$vulnerabilityId' => 'The ID given to this vulnerability.
', 'VulnerabilityIdList$member' => NULL, ], ], 'VulnerabilityIdList' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$relatedVulnerabilities' => 'One or more vulnerabilities related to the one identified in this finding.
', ], ], 'VulnerabilityReferenceUrl' => [ 'base' => NULL, 'refs' => [ 'VulnerabilityReferenceUrls$member' => NULL, ], ], 'VulnerabilityReferenceUrls' => [ 'base' => NULL, 'refs' => [ 'FindingDetail$referenceUrls' => 'The reference URLs for the vulnerability data.
', 'Vulnerability$referenceUrls' => 'Links to various resources with more information on this vulnerability.
', ], ], 'VulnerabilitySource' => [ 'base' => NULL, 'refs' => [ 'Vulnerability$source' => 'The source of the vulnerability information. Possible results are RHEL
, AMAZON_CVE
, DEBIAN
or NVD
.
A link to the official source material for this vulnerability.
', ], ], 'VulnerablePackage' => [ 'base' => 'Information on the vulnerable package identified by a finding.
', 'refs' => [ 'VulnerablePackageList$member' => NULL, ], ], 'VulnerablePackageList' => [ 'base' => NULL, 'refs' => [ 'PackageVulnerabilityDetails$vulnerablePackages' => 'The packages impacted by this vulnerability.
', ], ], 'VulnerablePackageRemediation' => [ 'base' => NULL, 'refs' => [ 'VulnerablePackage$remediation' => 'The code to run in your environment to update packages with a fix available.
', ], ], 'WeeklySchedule' => [ 'base' => 'A weekly schedule.
', 'refs' => [ 'Schedule$weekly' => 'The schedule\'s weekly.
', ], ], ],]; diff --git a/src/data/sagemaker/2017-07-24/api-2.json b/src/data/sagemaker/2017-07-24/api-2.json index e46c7ea090..69df0671ba 100644 --- a/src/data/sagemaker/2017-07-24/api-2.json +++ b/src/data/sagemaker/2017-07-24/api-2.json @@ -1012,6 +1012,14 @@ {"shape":"ResourceNotFound"} ] }, + "DeleteHyperParameterTuningJob":{ + "name":"DeleteHyperParameterTuningJob", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"DeleteHyperParameterTuningJobRequest"} + }, "DeleteImage":{ "name":"DeleteImage", "http":{ @@ -8090,6 +8098,13 @@ "members":{ } }, + "DeleteHyperParameterTuningJobRequest":{ + "type":"structure", + "required":["HyperParameterTuningJobName"], + "members":{ + "HyperParameterTuningJobName":{"shape":"HyperParameterTuningJobName"} + } + }, "DeleteImageRequest":{ "type":"structure", "required":["ImageName"], diff --git a/src/data/sagemaker/2017-07-24/api-2.json.php b/src/data/sagemaker/2017-07-24/api-2.json.php index 268b850cd5..bd81a72a12 100644 --- a/src/data/sagemaker/2017-07-24/api-2.json.php +++ b/src/data/sagemaker/2017-07-24/api-2.json.php @@ -1,3 +1,3 @@ '2.0', 'metadata' => [ 'apiVersion' => '2017-07-24', 'endpointPrefix' => 'api.sagemaker', 'jsonVersion' => '1.1', 'protocol' => 'json', 'serviceAbbreviation' => 'SageMaker', 'serviceFullName' => 'Amazon SageMaker Service', 'serviceId' => 'SageMaker', 'signatureVersion' => 'v4', 'signingName' => 'sagemaker', 'targetPrefix' => 'SageMaker', 'uid' => 'sagemaker-2017-07-24', ], 'operations' => [ 'AddAssociation' => [ 'name' => 'AddAssociation', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AddAssociationRequest', ], 'output' => [ 'shape' => 'AddAssociationResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'AddTags' => [ 'name' => 'AddTags', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AddTagsInput', ], 'output' => [ 'shape' => 'AddTagsOutput', ], ], 'AssociateTrialComponent' => [ 'name' => 'AssociateTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AssociateTrialComponentRequest', ], 'output' => [ 'shape' => 'AssociateTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'BatchDescribeModelPackage' => [ 'name' => 'BatchDescribeModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'BatchDescribeModelPackageInput', ], 'output' => [ 'shape' => 'BatchDescribeModelPackageOutput', ], ], 'CreateAction' => [ 'name' => 'CreateAction', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateActionRequest', ], 'output' => [ 'shape' => 'CreateActionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAlgorithm' => [ 'name' => 'CreateAlgorithm', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAlgorithmInput', ], 'output' => [ 'shape' => 'CreateAlgorithmOutput', ], ], 'CreateApp' => [ 'name' => 'CreateApp', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAppRequest', ], 'output' => [ 'shape' => 'CreateAppResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateAppImageConfig' => [ 'name' => 'CreateAppImageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAppImageConfigRequest', ], 'output' => [ 'shape' => 'CreateAppImageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'CreateArtifact' => [ 'name' => 'CreateArtifact', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateArtifactRequest', ], 'output' => [ 'shape' => 'CreateArtifactResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAutoMLJob' => [ 'name' => 'CreateAutoMLJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAutoMLJobRequest', ], 'output' => [ 'shape' => 'CreateAutoMLJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAutoMLJobV2' => [ 'name' => 'CreateAutoMLJobV2', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAutoMLJobV2Request', ], 'output' => [ 'shape' => 'CreateAutoMLJobV2Response', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateCluster' => [ 'name' => 'CreateCluster', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateClusterRequest', ], 'output' => [ 'shape' => 'CreateClusterResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateCodeRepository' => [ 'name' => 'CreateCodeRepository', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateCodeRepositoryInput', ], 'output' => [ 'shape' => 'CreateCodeRepositoryOutput', ], ], 'CreateCompilationJob' => [ 'name' => 'CreateCompilationJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateCompilationJobRequest', ], 'output' => [ 'shape' => 'CreateCompilationJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateContext' => [ 'name' => 'CreateContext', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateContextRequest', ], 'output' => [ 'shape' => 'CreateContextResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateDataQualityJobDefinition' => [ 'name' => 'CreateDataQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDataQualityJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateDataQualityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateDeviceFleet' => [ 'name' => 'CreateDeviceFleet', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDeviceFleetRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateDomain' => [ 'name' => 'CreateDomain', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDomainRequest', ], 'output' => [ 'shape' => 'CreateDomainResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateEdgeDeploymentPlan' => [ 'name' => 'CreateEdgeDeploymentPlan', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgeDeploymentPlanRequest', ], 'output' => [ 'shape' => 'CreateEdgeDeploymentPlanResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEdgeDeploymentStage' => [ 'name' => 'CreateEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgeDeploymentStageRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEdgePackagingJob' => [ 'name' => 'CreateEdgePackagingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgePackagingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEndpoint' => [ 'name' => 'CreateEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEndpointInput', ], 'output' => [ 'shape' => 'CreateEndpointOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEndpointConfig' => [ 'name' => 'CreateEndpointConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEndpointConfigInput', ], 'output' => [ 'shape' => 'CreateEndpointConfigOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateExperiment' => [ 'name' => 'CreateExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateExperimentRequest', ], 'output' => [ 'shape' => 'CreateExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateFeatureGroup' => [ 'name' => 'CreateFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateFeatureGroupRequest', ], 'output' => [ 'shape' => 'CreateFeatureGroupResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateFlowDefinition' => [ 'name' => 'CreateFlowDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateFlowDefinitionRequest', ], 'output' => [ 'shape' => 'CreateFlowDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateHub' => [ 'name' => 'CreateHub', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHubRequest', ], 'output' => [ 'shape' => 'CreateHubResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateHumanTaskUi' => [ 'name' => 'CreateHumanTaskUi', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHumanTaskUiRequest', ], 'output' => [ 'shape' => 'CreateHumanTaskUiResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateHyperParameterTuningJob' => [ 'name' => 'CreateHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHyperParameterTuningJobRequest', ], 'output' => [ 'shape' => 'CreateHyperParameterTuningJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateImage' => [ 'name' => 'CreateImage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateImageRequest', ], 'output' => [ 'shape' => 'CreateImageResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateImageVersion' => [ 'name' => 'CreateImageVersion', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateImageVersionRequest', ], 'output' => [ 'shape' => 'CreateImageVersionResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'CreateInferenceComponent' => [ 'name' => 'CreateInferenceComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateInferenceComponentInput', ], 'output' => [ 'shape' => 'CreateInferenceComponentOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateInferenceExperiment' => [ 'name' => 'CreateInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateInferenceExperimentRequest', ], 'output' => [ 'shape' => 'CreateInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateInferenceRecommendationsJob' => [ 'name' => 'CreateInferenceRecommendationsJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateInferenceRecommendationsJobRequest', ], 'output' => [ 'shape' => 'CreateInferenceRecommendationsJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateLabelingJob' => [ 'name' => 'CreateLabelingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateLabelingJobRequest', ], 'output' => [ 'shape' => 'CreateLabelingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateModel' => [ 'name' => 'CreateModel', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelInput', ], 'output' => [ 'shape' => 'CreateModelOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateModelBiasJobDefinition' => [ 'name' => 'CreateModelBiasJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelBiasJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateModelBiasJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateModelCard' => [ 'name' => 'CreateModelCard', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelCardRequest', ], 'output' => [ 'shape' => 'CreateModelCardResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'CreateModelCardExportJob' => [ 'name' => 'CreateModelCardExportJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelCardExportJobRequest', ], 'output' => [ 'shape' => 'CreateModelCardExportJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'CreateModelExplainabilityJobDefinition' => [ 'name' => 'CreateModelExplainabilityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelExplainabilityJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateModelExplainabilityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateModelPackage' => [ 'name' => 'CreateModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelPackageInput', ], 'output' => [ 'shape' => 'CreateModelPackageOutput', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateModelPackageGroup' => [ 'name' => 'CreateModelPackageGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelPackageGroupInput', ], 'output' => [ 'shape' => 'CreateModelPackageGroupOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateModelQualityJobDefinition' => [ 'name' => 'CreateModelQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelQualityJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateModelQualityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateMonitoringSchedule' => [ 'name' => 'CreateMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateMonitoringScheduleRequest', ], 'output' => [ 'shape' => 'CreateMonitoringScheduleResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateNotebookInstance' => [ 'name' => 'CreateNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateNotebookInstanceInput', ], 'output' => [ 'shape' => 'CreateNotebookInstanceOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateNotebookInstanceLifecycleConfig' => [ 'name' => 'CreateNotebookInstanceLifecycleConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateNotebookInstanceLifecycleConfigInput', ], 'output' => [ 'shape' => 'CreateNotebookInstanceLifecycleConfigOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreatePipeline' => [ 'name' => 'CreatePipeline', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreatePipelineRequest', ], 'output' => [ 'shape' => 'CreatePipelineResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'CreatePresignedDomainUrl' => [ 'name' => 'CreatePresignedDomainUrl', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreatePresignedDomainUrlRequest', ], 'output' => [ 'shape' => 'CreatePresignedDomainUrlResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'CreatePresignedNotebookInstanceUrl' => [ 'name' => 'CreatePresignedNotebookInstanceUrl', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreatePresignedNotebookInstanceUrlInput', ], 'output' => [ 'shape' => 'CreatePresignedNotebookInstanceUrlOutput', ], ], 'CreateProcessingJob' => [ 'name' => 'CreateProcessingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateProcessingJobRequest', ], 'output' => [ 'shape' => 'CreateProcessingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'CreateProject' => [ 'name' => 'CreateProject', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateProjectInput', ], 'output' => [ 'shape' => 'CreateProjectOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateSpace' => [ 'name' => 'CreateSpace', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateSpaceRequest', ], 'output' => [ 'shape' => 'CreateSpaceResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateStudioLifecycleConfig' => [ 'name' => 'CreateStudioLifecycleConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateStudioLifecycleConfigRequest', ], 'output' => [ 'shape' => 'CreateStudioLifecycleConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'CreateTrainingJob' => [ 'name' => 'CreateTrainingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 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'ListNotebookInstanceLifecycleConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListNotebookInstanceLifecycleConfigsInput', ], 'output' => [ 'shape' => 'ListNotebookInstanceLifecycleConfigsOutput', ], ], 'ListNotebookInstances' => [ 'name' => 'ListNotebookInstances', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListNotebookInstancesInput', ], 'output' => [ 'shape' => 'ListNotebookInstancesOutput', ], ], 'ListPipelineExecutionSteps' => [ 'name' => 'ListPipelineExecutionSteps', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineExecutionStepsRequest', ], 'output' => [ 'shape' => 'ListPipelineExecutionStepsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelineExecutions' => [ 'name' => 'ListPipelineExecutions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineExecutionsRequest', ], 'output' => [ 'shape' => 'ListPipelineExecutionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelineParametersForExecution' => [ 'name' => 'ListPipelineParametersForExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineParametersForExecutionRequest', ], 'output' => [ 'shape' => 'ListPipelineParametersForExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelines' => [ 'name' => 'ListPipelines', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelinesRequest', ], 'output' => [ 'shape' => 'ListPipelinesResponse', ], ], 'ListProcessingJobs' => [ 'name' => 'ListProcessingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListProcessingJobsRequest', ], 'output' => [ 'shape' => 'ListProcessingJobsResponse', ], ], 'ListProjects' => [ 'name' => 'ListProjects', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListProjectsInput', ], 'output' => [ 'shape' => 'ListProjectsOutput', ], ], 'ListResourceCatalogs' => [ 'name' => 'ListResourceCatalogs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListResourceCatalogsRequest', ], 'output' => [ 'shape' => 'ListResourceCatalogsResponse', ], ], 'ListSpaces' => [ 'name' => 'ListSpaces', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListSpacesRequest', ], 'output' => [ 'shape' => 'ListSpacesResponse', ], ], 'ListStageDevices' => [ 'name' => 'ListStageDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListStageDevicesRequest', ], 'output' => [ 'shape' => 'ListStageDevicesResponse', ], ], 'ListStudioLifecycleConfigs' => [ 'name' => 'ListStudioLifecycleConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListStudioLifecycleConfigsRequest', ], 'output' => [ 'shape' => 'ListStudioLifecycleConfigsResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'ListSubscribedWorkteams' => [ 'name' => 'ListSubscribedWorkteams', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListSubscribedWorkteamsRequest', ], 'output' => [ 'shape' => 'ListSubscribedWorkteamsResponse', ], ], 'ListTags' => [ 'name' => 'ListTags', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTagsInput', ], 'output' => [ 'shape' => 'ListTagsOutput', ], ], 'ListTrainingJobs' => [ 'name' => 'ListTrainingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrainingJobsRequest', ], 'output' => [ 'shape' => 'ListTrainingJobsResponse', ], ], 'ListTrainingJobsForHyperParameterTuningJob' => [ 'name' => 'ListTrainingJobsForHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrainingJobsForHyperParameterTuningJobRequest', ], 'output' => [ 'shape' => 'ListTrainingJobsForHyperParameterTuningJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListTransformJobs' => [ 'name' => 'ListTransformJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTransformJobsRequest', ], 'output' => [ 'shape' => 'ListTransformJobsResponse', ], ], 'ListTrialComponents' => [ 'name' => 'ListTrialComponents', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrialComponentsRequest', ], 'output' => [ 'shape' => 'ListTrialComponentsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListTrials' => [ 'name' => 'ListTrials', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrialsRequest', ], 'output' => [ 'shape' => 'ListTrialsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListUserProfiles' => [ 'name' => 'ListUserProfiles', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListUserProfilesRequest', ], 'output' => [ 'shape' => 'ListUserProfilesResponse', ], ], 'ListWorkforces' => [ 'name' => 'ListWorkforces', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListWorkforcesRequest', ], 'output' => [ 'shape' => 'ListWorkforcesResponse', ], ], 'ListWorkteams' => [ 'name' => 'ListWorkteams', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListWorkteamsRequest', ], 'output' => [ 'shape' => 'ListWorkteamsResponse', ], ], 'PutModelPackageGroupPolicy' => [ 'name' => 'PutModelPackageGroupPolicy', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'PutModelPackageGroupPolicyInput', ], 'output' => [ 'shape' => 'PutModelPackageGroupPolicyOutput', ], 'errors' => [ [ 'shape' => 'ConflictException', ], ], ], 'QueryLineage' => [ 'name' => 'QueryLineage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'QueryLineageRequest', ], 'output' => [ 'shape' => 'QueryLineageResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'RegisterDevices' => [ 'name' => 'RegisterDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RegisterDevicesRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'RenderUiTemplate' => [ 'name' => 'RenderUiTemplate', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RenderUiTemplateRequest', ], 'output' => [ 'shape' => 'RenderUiTemplateResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'RetryPipelineExecution' => [ 'name' => 'RetryPipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RetryPipelineExecutionRequest', ], 'output' => [ 'shape' => 'RetryPipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'Search' => [ 'name' => 'Search', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SearchRequest', ], 'output' => [ 'shape' => 'SearchResponse', ], ], 'SendPipelineExecutionStepFailure' => [ 'name' => 'SendPipelineExecutionStepFailure', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SendPipelineExecutionStepFailureRequest', ], 'output' => [ 'shape' => 'SendPipelineExecutionStepFailureResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'SendPipelineExecutionStepSuccess' => [ 'name' => 'SendPipelineExecutionStepSuccess', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SendPipelineExecutionStepSuccessRequest', ], 'output' => [ 'shape' => 'SendPipelineExecutionStepSuccessResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'StartEdgeDeploymentStage' => [ 'name' => 'StartEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartEdgeDeploymentStageRequest', ], ], 'StartInferenceExperiment' => [ 'name' => 'StartInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartInferenceExperimentRequest', ], 'output' => [ 'shape' => 'StartInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'StartMonitoringSchedule' => [ 'name' => 'StartMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartMonitoringScheduleRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StartNotebookInstance' => [ 'name' => 'StartNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartNotebookInstanceInput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'StartPipelineExecution' => [ 'name' => 'StartPipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartPipelineExecutionRequest', ], 'output' => [ 'shape' => 'StartPipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'StopAutoMLJob' => [ 'name' => 'StopAutoMLJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopAutoMLJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopCompilationJob' => [ 'name' => 'StopCompilationJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopCompilationJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopEdgeDeploymentStage' => [ 'name' => 'StopEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopEdgeDeploymentStageRequest', ], ], 'StopEdgePackagingJob' => [ 'name' => 'StopEdgePackagingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopEdgePackagingJobRequest', ], ], 'StopHyperParameterTuningJob' => [ 'name' => 'StopHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopHyperParameterTuningJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopInferenceExperiment' => [ 'name' => 'StopInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopInferenceExperimentRequest', ], 'output' => [ 'shape' => 'StopInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'StopInferenceRecommendationsJob' => [ 'name' => 'StopInferenceRecommendationsJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopInferenceRecommendationsJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopLabelingJob' => [ 'name' => 'StopLabelingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopLabelingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopMonitoringSchedule' => [ 'name' => 'StopMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopMonitoringScheduleRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopNotebookInstance' => [ 'name' => 'StopNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopNotebookInstanceInput', ], ], 'StopPipelineExecution' => [ 'name' => 'StopPipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopPipelineExecutionRequest', ], 'output' => [ 'shape' => 'StopPipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ConflictException', ], ], ], 'StopProcessingJob' => [ 'name' => 'StopProcessingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopProcessingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopTrainingJob' => [ 'name' => 'StopTrainingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopTrainingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopTransformJob' => [ 'name' => 'StopTransformJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopTransformJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateAction' => [ 'name' => 'UpdateAction', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateActionRequest', ], 'output' => [ 'shape' => 'UpdateActionResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateAppImageConfig' => [ 'name' => 'UpdateAppImageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateAppImageConfigRequest', ], 'output' => [ 'shape' => 'UpdateAppImageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateArtifact' => [ 'name' => 'UpdateArtifact', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateArtifactRequest', ], 'output' => [ 'shape' => 'UpdateArtifactResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateCluster' => [ 'name' => 'UpdateCluster', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateClusterRequest', ], 'output' => [ 'shape' => 'UpdateClusterResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ConflictException', ], ], ], 'UpdateCodeRepository' => [ 'name' => 'UpdateCodeRepository', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateCodeRepositoryInput', ], 'output' => [ 'shape' => 'UpdateCodeRepositoryOutput', ], 'errors' => [ [ 'shape' => 'ConflictException', ], ], ], 'UpdateContext' => [ 'name' => 'UpdateContext', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateContextRequest', ], 'output' => [ 'shape' => 'UpdateContextResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateDeviceFleet' => [ 'name' => 'UpdateDeviceFleet', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateDeviceFleetRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'UpdateDevices' => [ 'name' => 'UpdateDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateDevicesRequest', ], ], 'UpdateDomain' => [ 'name' => 'UpdateDomain', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateDomainRequest', ], 'output' => [ 'shape' => 'UpdateDomainResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateEndpoint' => [ 'name' => 'UpdateEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateEndpointInput', ], 'output' => [ 'shape' => 'UpdateEndpointOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateEndpointWeightsAndCapacities' => [ 'name' => 'UpdateEndpointWeightsAndCapacities', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateEndpointWeightsAndCapacitiesInput', ], 'output' => [ 'shape' => 'UpdateEndpointWeightsAndCapacitiesOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateExperiment' => [ 'name' => 'UpdateExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateExperimentRequest', ], 'output' => [ 'shape' => 'UpdateExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateFeatureGroup' => [ 'name' => 'UpdateFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateFeatureGroupRequest', ], 'output' => [ 'shape' => 'UpdateFeatureGroupResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateFeatureMetadata' => [ 'name' => 'UpdateFeatureMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateFeatureMetadataRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateHub' => [ 'name' => 'UpdateHub', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateHubRequest', ], 'output' => [ 'shape' => 'UpdateHubResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateImage' => [ 'name' => 'UpdateImage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateImageRequest', ], 'output' => [ 'shape' => 'UpdateImageResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateImageVersion' => [ 'name' => 'UpdateImageVersion', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateImageVersionRequest', ], 'output' => [ 'shape' => 'UpdateImageVersionResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateInferenceComponent' => [ 'name' => 'UpdateInferenceComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateInferenceComponentInput', ], 'output' => [ 'shape' => 'UpdateInferenceComponentOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateInferenceComponentRuntimeConfig' => [ 'name' => 'UpdateInferenceComponentRuntimeConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateInferenceComponentRuntimeConfigInput', ], 'output' => [ 'shape' => 'UpdateInferenceComponentRuntimeConfigOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateInferenceExperiment' => [ 'name' => 'UpdateInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateInferenceExperimentRequest', ], 'output' => [ 'shape' => 'UpdateInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateModelCard' => [ 'name' => 'UpdateModelCard', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateModelCardRequest', ], 'output' => [ 'shape' => 'UpdateModelCardResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'UpdateModelPackage' => [ 'name' => 'UpdateModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateModelPackageInput', ], 'output' => [ 'shape' => 'UpdateModelPackageOutput', ], 'errors' => [ [ 'shape' => 'ConflictException', ], ], ], 'UpdateMonitoringAlert' => [ 'name' => 'UpdateMonitoringAlert', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateMonitoringAlertRequest', ], 'output' => [ 'shape' => 'UpdateMonitoringAlertResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateMonitoringSchedule' => [ 'name' => 'UpdateMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateMonitoringScheduleRequest', ], 'output' => [ 'shape' => 'UpdateMonitoringScheduleResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateNotebookInstance' => [ 'name' => 'UpdateNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateNotebookInstanceInput', ], 'output' => [ 'shape' => 'UpdateNotebookInstanceOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateNotebookInstanceLifecycleConfig' => [ 'name' => 'UpdateNotebookInstanceLifecycleConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateNotebookInstanceLifecycleConfigInput', ], 'output' => [ 'shape' => 'UpdateNotebookInstanceLifecycleConfigOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdatePipeline' => [ 'name' => 'UpdatePipeline', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdatePipelineRequest', ], 'output' => [ 'shape' => 'UpdatePipelineResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ConflictException', ], ], ], 'UpdatePipelineExecution' => [ 'name' => 'UpdatePipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdatePipelineExecutionRequest', ], 'output' => [ 'shape' => 'UpdatePipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ConflictException', ], ], ], 'UpdateProject' => [ 'name' => 'UpdateProject', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateProjectInput', ], 'output' => [ 'shape' => 'UpdateProjectOutput', ], 'errors' => [ [ 'shape' => 'ConflictException', ], ], ], 'UpdateSpace' => [ 'name' => 'UpdateSpace', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateSpaceRequest', ], 'output' => [ 'shape' => 'UpdateSpaceResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateTrainingJob' => [ 'name' => 'UpdateTrainingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateTrainingJobRequest', ], 'output' => [ 'shape' => 'UpdateTrainingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateTrial' => [ 'name' => 'UpdateTrial', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateTrialRequest', ], 'output' => [ 'shape' => 'UpdateTrialResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateTrialComponent' => [ 'name' => 'UpdateTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateTrialComponentRequest', ], 'output' => [ 'shape' => 'UpdateTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateUserProfile' => [ 'name' => 'UpdateUserProfile', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateUserProfileRequest', ], 'output' => [ 'shape' => 'UpdateUserProfileResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateWorkforce' => [ 'name' => 'UpdateWorkforce', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateWorkforceRequest', ], 'output' => [ 'shape' => 'UpdateWorkforceResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], ], ], 'UpdateWorkteam' => [ 'name' => 'UpdateWorkteam', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateWorkteamRequest', ], 'output' => [ 'shape' => 'UpdateWorkteamResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], ], 'shapes' => [ 'Accept' => [ 'type' => 'string', 'max' => 256, 'pattern' => '.*', ], 'AcceptEula' => [ 'type' => 'boolean', ], 'AccountId' => [ 'type' => 'string', 'max' => 12, 'min' => 12, 'pattern' => '^\\d+$', ], 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'CompilationJobName', 'RoleArn', 'OutputConfig', 'StoppingCondition', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'ModelPackageVersionArn' => [ 'shape' => 'ModelPackageArn', ], 'InputConfig' => [ 'shape' => 'InputConfig', ], 'OutputConfig' => [ 'shape' => 'OutputConfig', ], 'VpcConfig' => [ 'shape' => 'NeoVpcConfig', ], 'StoppingCondition' => [ 'shape' => 'StoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateCompilationJobResponse' => [ 'type' => 'structure', 'required' => [ 'CompilationJobArn', ], 'members' => [ 'CompilationJobArn' => [ 'shape' => 'CompilationJobArn', ], ], ], 'CreateContextRequest' => [ 'type' => 'structure', 'required' => [ 'ContextName', 'Source', 'ContextType', ], 'members' => [ 'ContextName' => [ 'shape' => 'ContextName', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateContextResponse' => [ 'type' => 'structure', 'members' => [ 'ContextArn' => [ 'shape' => 'ContextArn', ], ], ], 'CreateDataQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'DataQualityAppSpecification', 'DataQualityJobInput', 'DataQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'DataQualityBaselineConfig' => [ 'shape' => 'DataQualityBaselineConfig', ], 'DataQualityAppSpecification' => [ 'shape' => 'DataQualityAppSpecification', ], 'DataQualityJobInput' => [ 'shape' => 'DataQualityJobInput', ], 'DataQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateDataQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateDeviceFleetRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'OutputConfig', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Description' => [ 'shape' => 'DeviceFleetDescription', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'EnableIotRoleAlias' => [ 'shape' => 'EnableIotRoleAlias', ], ], ], 'CreateDomainRequest' => [ 'type' => 'structure', 'required' => [ 'DomainName', 'AuthMode', 'DefaultUserSettings', 'SubnetIds', 'VpcId', ], 'members' => [ 'DomainName' => [ 'shape' => 'DomainName', ], 'AuthMode' => [ 'shape' => 'AuthMode', ], 'DefaultUserSettings' => [ 'shape' => 'UserSettings', ], 'DomainSettings' => [ 'shape' => 'DomainSettings', ], 'SubnetIds' => [ 'shape' => 'Subnets', ], 'VpcId' => [ 'shape' => 'VpcId', ], 'Tags' => [ 'shape' => 'TagList', ], 'AppNetworkAccessType' => [ 'shape' => 'AppNetworkAccessType', ], 'HomeEfsFileSystemKmsKeyId' => [ 'shape' => 'KmsKeyId', 'deprecated' => true, 'deprecatedMessage' => 'This property is deprecated, use KmsKeyId instead.', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AppSecurityGroupManagement' => [ 'shape' => 'AppSecurityGroupManagement', ], 'DefaultSpaceSettings' => [ 'shape' => 'DefaultSpaceSettings', ], ], ], 'CreateDomainResponse' => [ 'type' => 'structure', 'members' => [ 'DomainArn' => [ 'shape' => 'DomainArn', ], 'Url' => [ 'shape' => 'String1024', ], ], ], 'CreateEdgeDeploymentPlanRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', 'ModelConfigs', 'DeviceFleetName', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'ModelConfigs' => [ 'shape' => 'EdgeDeploymentModelConfigs', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'Stages' => [ 'shape' => 'DeploymentStages', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEdgeDeploymentPlanResponse' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanArn', ], 'members' => [ 'EdgeDeploymentPlanArn' => [ 'shape' => 'EdgeDeploymentPlanArn', ], ], ], 'CreateEdgeDeploymentStageRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', 'Stages', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'Stages' => [ 'shape' => 'DeploymentStages', ], ], ], 'CreateEdgePackagingJobRequest' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobName', 'CompilationJobName', 'ModelName', 'ModelVersion', 'RoleArn', 'OutputConfig', ], 'members' => [ 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'ModelName' => [ 'shape' => 'EntityName', ], 'ModelVersion' => [ 'shape' => 'EdgeVersion', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'ResourceKey' => [ 'shape' => 'KmsKeyId', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEndpointConfigInput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', 'ProductionVariants', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'ExecutionRoleArn' => [ 'shape' => 'RoleArn', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'EnableNetworkIsolation' => [ 'shape' => 'Boolean', ], ], ], 'CreateEndpointConfigOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigArn', ], 'members' => [ 'EndpointConfigArn' => [ 'shape' => 'EndpointConfigArn', ], ], ], 'CreateEndpointInput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', 'EndpointConfigName', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'DeploymentConfig' => [ 'shape' => 'DeploymentConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEndpointOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointArn', ], 'members' => [ 'EndpointArn' => [ 'shape' => 'EndpointArn', ], ], ], 'CreateExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'ExperimentName', ], 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateExperimentResponse' => [ 'type' => 'structure', 'members' => [ 'ExperimentArn' => [ 'shape' => 'ExperimentArn', ], ], ], 'CreateFeatureGroupRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', 'RecordIdentifierFeatureName', 'EventTimeFeatureName', 'FeatureDefinitions', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'RecordIdentifierFeatureName' => [ 'shape' => 'FeatureName', ], 'EventTimeFeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureDefinitions' => [ 'shape' => 'FeatureDefinitions', ], 'OnlineStoreConfig' => [ 'shape' => 'OnlineStoreConfig', ], 'OfflineStoreConfig' => [ 'shape' => 'OfflineStoreConfig', ], 'ThroughputConfig' => [ 'shape' => 'ThroughputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Description' => [ 'shape' => 'Description', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateFeatureGroupResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], ], ], 'CreateFlowDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionName', 'OutputConfig', 'RoleArn', ], 'members' => [ 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], 'HumanLoopRequestSource' => [ 'shape' => 'HumanLoopRequestSource', ], 'HumanLoopActivationConfig' => [ 'shape' => 'HumanLoopActivationConfig', ], 'HumanLoopConfig' => [ 'shape' => 'HumanLoopConfig', ], 'OutputConfig' => [ 'shape' => 'FlowDefinitionOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateFlowDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionArn', ], 'members' => [ 'FlowDefinitionArn' => [ 'shape' => 'FlowDefinitionArn', ], ], ], 'CreateHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubDescription', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubDescription' => [ 'shape' => 'HubDescription', ], 'HubDisplayName' => [ 'shape' => 'HubDisplayName', ], 'HubSearchKeywords' => [ 'shape' => 'HubSearchKeywordList', ], 'S3StorageConfig' => [ 'shape' => 'HubS3StorageConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateHubResponse' => [ 'type' => 'structure', 'required' => [ 'HubArn', ], 'members' => [ 'HubArn' => [ 'shape' => 'HubArn', ], ], ], 'CreateHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', 'UiTemplate', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], 'UiTemplate' => [ 'shape' => 'UiTemplate', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateHumanTaskUiResponse' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiArn', ], 'members' => [ 'HumanTaskUiArn' => [ 'shape' => 'HumanTaskUiArn', ], ], ], 'CreateHyperParameterTuningJobRequest' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', 'HyperParameterTuningJobConfig', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], 'HyperParameterTuningJobConfig' => [ 'shape' => 'HyperParameterTuningJobConfig', ], 'TrainingJobDefinition' => [ 'shape' => 'HyperParameterTrainingJobDefinition', ], 'TrainingJobDefinitions' => [ 'shape' => 'HyperParameterTrainingJobDefinitions', ], 'WarmStartConfig' => [ 'shape' => 'HyperParameterTuningJobWarmStartConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'Autotune' => [ 'shape' => 'Autotune', ], ], ], 'CreateHyperParameterTuningJobResponse' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobArn', ], 'members' => [ 'HyperParameterTuningJobArn' => [ 'shape' => 'HyperParameterTuningJobArn', ], ], ], 'CreateImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', 'RoleArn', ], 'members' => [ 'Description' => [ 'shape' => 'ImageDescription', ], 'DisplayName' => [ 'shape' => 'ImageDisplayName', ], 'ImageName' => [ 'shape' => 'ImageName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateImageResponse' => [ 'type' => 'structure', 'members' => [ 'ImageArn' => [ 'shape' => 'ImageArn', ], ], ], 'CreateImageVersionRequest' => [ 'type' => 'structure', 'required' => [ 'BaseImage', 'ClientToken', 'ImageName', ], 'members' => [ 'BaseImage' => [ 'shape' => 'ImageBaseImage', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'ImageName' => [ 'shape' => 'ImageName', ], 'Aliases' => [ 'shape' => 'SageMakerImageVersionAliases', ], 'VendorGuidance' => [ 'shape' => 'VendorGuidance', ], 'JobType' => [ 'shape' => 'JobType', ], 'MLFramework' => [ 'shape' => 'MLFramework', ], 'ProgrammingLang' => [ 'shape' => 'ProgrammingLang', ], 'Processor' => [ 'shape' => 'Processor', ], 'Horovod' => [ 'shape' => 'Horovod', ], 'ReleaseNotes' => [ 'shape' => 'ReleaseNotes', ], ], ], 'CreateImageVersionResponse' => [ 'type' => 'structure', 'members' => [ 'ImageVersionArn' => [ 'shape' => 'ImageVersionArn', ], ], ], 'CreateInferenceComponentInput' => [ 'type' => 'structure', 'required' => [ 'InferenceComponentName', 'EndpointName', 'VariantName', 'Specification', 'RuntimeConfig', ], 'members' => [ 'InferenceComponentName' => [ 'shape' => 'InferenceComponentName', ], 'EndpointName' => [ 'shape' => 'EndpointName', ], 'VariantName' => [ 'shape' => 'VariantName', ], 'Specification' => [ 'shape' => 'InferenceComponentSpecification', ], 'RuntimeConfig' => [ 'shape' => 'InferenceComponentRuntimeConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateInferenceComponentOutput' => [ 'type' => 'structure', 'required' => [ 'InferenceComponentArn', ], 'members' => [ 'InferenceComponentArn' => [ 'shape' => 'InferenceComponentArn', ], ], ], 'CreateInferenceExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'Type', 'RoleArn', 'EndpointName', 'ModelVariants', 'ShadowModeConfig', ], 'members' => [ 'Name' => [ 'shape' => 'InferenceExperimentName', ], 'Type' => [ 'shape' => 'InferenceExperimentType', ], 'Schedule' => [ 'shape' => 'InferenceExperimentSchedule', ], 'Description' => [ 'shape' => 'InferenceExperimentDescription', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'EndpointName' => [ 'shape' => 'EndpointName', ], 'ModelVariants' => [ 'shape' => 'ModelVariantConfigList', ], 'DataStorageConfig' => [ 'shape' => 'InferenceExperimentDataStorageConfig', ], 'ShadowModeConfig' => [ 'shape' => 'ShadowModeConfig', ], 'KmsKey' => [ 'shape' => 'KmsKeyId', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateInferenceExperimentResponse' => [ 'type' => 'structure', 'required' => [ 'InferenceExperimentArn', ], 'members' => [ 'InferenceExperimentArn' => [ 'shape' => 'InferenceExperimentArn', ], ], ], 'CreateInferenceRecommendationsJobRequest' => [ 'type' => 'structure', 'required' => [ 'JobName', 'JobType', 'RoleArn', 'InputConfig', ], 'members' => [ 'JobName' => [ 'shape' => 'RecommendationJobName', ], 'JobType' => [ 'shape' => 'RecommendationJobType', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'InputConfig' => [ 'shape' => 'RecommendationJobInputConfig', ], 'JobDescription' => [ 'shape' => 'RecommendationJobDescription', ], 'StoppingConditions' => [ 'shape' => 'RecommendationJobStoppingConditions', ], 'OutputConfig' => [ 'shape' => 'RecommendationJobOutputConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateInferenceRecommendationsJobResponse' => [ 'type' => 'structure', 'required' => [ 'JobArn', ], 'members' => [ 'JobArn' => [ 'shape' => 'RecommendationJobArn', ], ], ], 'CreateLabelingJobRequest' => [ 'type' => 'structure', 'required' => [ 'LabelingJobName', 'LabelAttributeName', 'InputConfig', 'OutputConfig', 'RoleArn', 'HumanTaskConfig', ], 'members' => [ 'LabelingJobName' => [ 'shape' => 'LabelingJobName', ], 'LabelAttributeName' => [ 'shape' => 'LabelAttributeName', ], 'InputConfig' => [ 'shape' => 'LabelingJobInputConfig', ], 'OutputConfig' => [ 'shape' => 'LabelingJobOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'LabelCategoryConfigS3Uri' => [ 'shape' => 'S3Uri', ], 'StoppingConditions' => [ 'shape' => 'LabelingJobStoppingConditions', ], 'LabelingJobAlgorithmsConfig' => [ 'shape' => 'LabelingJobAlgorithmsConfig', ], 'HumanTaskConfig' => [ 'shape' => 'HumanTaskConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateLabelingJobResponse' => [ 'type' => 'structure', 'required' => [ 'LabelingJobArn', ], 'members' => [ 'LabelingJobArn' => [ 'shape' => 'LabelingJobArn', ], ], ], 'CreateModelBiasJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'ModelBiasAppSpecification', 'ModelBiasJobInput', 'ModelBiasJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'ModelBiasBaselineConfig' => [ 'shape' => 'ModelBiasBaselineConfig', ], 'ModelBiasAppSpecification' => [ 'shape' => 'ModelBiasAppSpecification', ], 'ModelBiasJobInput' => [ 'shape' => 'ModelBiasJobInput', ], 'ModelBiasJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelBiasJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateModelCardExportJobRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', 'ModelCardExportJobName', 'OutputConfig', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'ModelCardNameOrArn', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'ModelCardExportJobName' => [ 'shape' => 'EntityName', ], 'OutputConfig' => [ 'shape' => 'ModelCardExportOutputConfig', ], ], ], 'CreateModelCardExportJobResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardExportJobArn', ], 'members' => [ 'ModelCardExportJobArn' => [ 'shape' => 'ModelCardExportJobArn', ], ], ], 'CreateModelCardRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', 'Content', 'ModelCardStatus', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'EntityName', ], 'SecurityConfig' => [ 'shape' => 'ModelCardSecurityConfig', ], 'Content' => [ 'shape' => 'ModelCardContent', ], 'ModelCardStatus' => [ 'shape' => 'ModelCardStatus', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelCardResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardArn', ], 'members' => [ 'ModelCardArn' => [ 'shape' => 'ModelCardArn', ], ], ], 'CreateModelExplainabilityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'ModelExplainabilityAppSpecification', 'ModelExplainabilityJobInput', 'ModelExplainabilityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'ModelExplainabilityBaselineConfig' => [ 'shape' => 'ModelExplainabilityBaselineConfig', ], 'ModelExplainabilityAppSpecification' => [ 'shape' => 'ModelExplainabilityAppSpecification', ], 'ModelExplainabilityJobInput' => [ 'shape' => 'ModelExplainabilityJobInput', ], 'ModelExplainabilityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelExplainabilityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateModelInput' => [ 'type' => 'structure', 'required' => [ 'ModelName', ], 'members' => [ 'ModelName' => [ 'shape' => 'ModelName', ], 'PrimaryContainer' => [ 'shape' => 'ContainerDefinition', ], 'Containers' => [ 'shape' => 'ContainerDefinitionList', ], 'InferenceExecutionConfig' => [ 'shape' => 'InferenceExecutionConfig', ], 'ExecutionRoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'EnableNetworkIsolation' => [ 'shape' => 'Boolean', ], ], ], 'CreateModelOutput' => [ 'type' => 'structure', 'required' => [ 'ModelArn', ], 'members' => [ 'ModelArn' => [ 'shape' => 'ModelArn', ], ], ], 'CreateModelPackageGroupInput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupName', ], 'members' => [ 'ModelPackageGroupName' => [ 'shape' => 'EntityName', ], 'ModelPackageGroupDescription' => [ 'shape' => 'EntityDescription', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelPackageGroupOutput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupArn', ], 'members' => [ 'ModelPackageGroupArn' => [ 'shape' => 'ModelPackageGroupArn', ], ], ], 'CreateModelPackageInput' => [ 'type' => 'structure', 'members' => [ 'ModelPackageName' => [ 'shape' => 'EntityName', ], 'ModelPackageGroupName' => [ 'shape' => 'ArnOrName', ], 'ModelPackageDescription' => [ 'shape' => 'EntityDescription', ], 'InferenceSpecification' => [ 'shape' => 'InferenceSpecification', ], 'ValidationSpecification' => [ 'shape' => 'ModelPackageValidationSpecification', ], 'SourceAlgorithmSpecification' => [ 'shape' => 'SourceAlgorithmSpecification', ], 'CertifyForMarketplace' => [ 'shape' => 'CertifyForMarketplace', ], 'Tags' => [ 'shape' => 'TagList', ], 'ModelApprovalStatus' => [ 'shape' => 'ModelApprovalStatus', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'ModelMetrics' => [ 'shape' => 'ModelMetrics', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'Domain' => [ 'shape' => 'String', ], 'Task' => [ 'shape' => 'String', ], 'SamplePayloadUrl' => [ 'shape' => 'S3Uri', ], 'CustomerMetadataProperties' => [ 'shape' => 'CustomerMetadataMap', ], 'DriftCheckBaselines' => [ 'shape' => 'DriftCheckBaselines', ], 'AdditionalInferenceSpecifications' => [ 'shape' => 'AdditionalInferenceSpecifications', ], 'SkipModelValidation' => [ 'shape' => 'SkipModelValidation', ], ], ], 'CreateModelPackageOutput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageArn', ], 'members' => [ 'ModelPackageArn' => [ 'shape' => 'ModelPackageArn', ], ], ], 'CreateModelQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'ModelQualityAppSpecification', 'ModelQualityJobInput', 'ModelQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'ModelQualityBaselineConfig' => [ 'shape' => 'ModelQualityBaselineConfig', ], 'ModelQualityAppSpecification' => [ 'shape' => 'ModelQualityAppSpecification', ], 'ModelQualityJobInput' => [ 'shape' => 'ModelQualityJobInput', ], 'ModelQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateMonitoringScheduleRequest' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleName', 'MonitoringScheduleConfig', ], 'members' => [ 'MonitoringScheduleName' => [ 'shape' => 'MonitoringScheduleName', ], 'MonitoringScheduleConfig' => [ 'shape' => 'MonitoringScheduleConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateMonitoringScheduleResponse' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleArn', ], 'members' => [ 'MonitoringScheduleArn' => [ 'shape' => 'MonitoringScheduleArn', ], ], ], 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'HubName' => [ 'shape' => 'HubName', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], ], ], 'DeleteHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], ], ], 'DeleteHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], ], ], 'DeleteHumanTaskUiResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], ], ], 'DeleteImageResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteImageVersionRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], 'Version' => [ 'shape' => 'ImageVersionNumber', ], 'Alias' => [ 'shape' => 'SageMakerImageVersionAlias', ], ], ], 'DeleteImageVersionResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteInferenceComponentInput' => [ 'type' => 'structure', 'required' => [ 'InferenceComponentName', ], 'members' => [ 'InferenceComponentName' => [ 'shape' => 'InferenceComponentName', ], ], ], 'DeleteInferenceExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'Name', ], 'members' => [ 'Name' => [ 'shape' => 'InferenceExperimentName', ], ], ], 'DeleteInferenceExperimentResponse' => [ 'type' => 'structure', 'required' => [ 'InferenceExperimentArn', ], 'members' => [ 'InferenceExperimentArn' => [ 'shape' => 'InferenceExperimentArn', ], ], ], 'DeleteModelBiasJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DeleteModelCardRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'EntityName', ], ], ], 'DeleteModelExplainabilityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DeleteModelInput' => [ 'type' => 'structure', 'required' => [ 'ModelName', ], 'members' => [ 'ModelName' => [ 'shape' => 'ModelName', ], ], ], 'DeleteModelPackageGroupInput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupName', ], 'members' => [ 'ModelPackageGroupName' => [ 'shape' => 'ArnOrName', ], ], ], 'DeleteModelPackageGroupPolicyInput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupName', ], 'members' => [ 'ModelPackageGroupName' => [ 'shape' => 'EntityName', ], ], ], 'DeleteModelPackageInput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageName', ], 'members' => [ 'ModelPackageName' => [ 'shape' => 'VersionedArnOrName', ], ], ], 'DeleteModelQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DeleteMonitoringScheduleRequest' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleName', ], 'members' => [ 'MonitoringScheduleName' => [ 'shape' => 'MonitoringScheduleName', ], ], ], 'DeleteNotebookInstanceInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceName', ], 'members' => [ 'NotebookInstanceName' => [ 'shape' => 'NotebookInstanceName', ], ], ], 'DeleteNotebookInstanceLifecycleConfigInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceLifecycleConfigName', ], 'members' => [ 'NotebookInstanceLifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], ], ], 'DeletePipelineRequest' => [ 'type' => 'structure', 'required' => [ 'PipelineName', 'ClientRequestToken', ], 'members' => [ 'PipelineName' => [ 'shape' => 'PipelineName', ], 'ClientRequestToken' => [ 'shape' => 'IdempotencyToken', 'idempotencyToken' => true, ], ], ], 'DeletePipelineResponse' => [ 'type' => 'structure', 'members' => [ 'PipelineArn' => [ 'shape' => 'PipelineArn', ], ], ], 'DeleteProjectInput' => [ 'type' => 'structure', 'required' => [ 'ProjectName', ], 'members' => [ 'ProjectName' => [ 'shape' => 'ProjectEntityName', ], ], ], 'DeleteSpaceRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'SpaceName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], ], ], 'DeleteStudioLifecycleConfigRequest' => [ 'type' => 'structure', 'required' => [ 'StudioLifecycleConfigName', ], 'members' => [ 'StudioLifecycleConfigName' => [ 'shape' => 'StudioLifecycleConfigName', ], ], ], 'DeleteTagsInput' => [ 'type' => 'structure', 'required' => [ 'ResourceArn', 'TagKeys', ], 'members' => [ 'ResourceArn' => [ 'shape' => 'ResourceArn', ], 'TagKeys' => [ 'shape' => 'TagKeyList', ], ], ], 'DeleteTagsOutput' => [ 'type' => 'structure', 'members' => [], ], 'DeleteTrialComponentRequest' => [ 'type' => 'structure', 'required' => [ 'TrialComponentName', ], 'members' => [ 'TrialComponentName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DeleteTrialComponentResponse' => [ 'type' => 'structure', 'members' => [ 'TrialComponentArn' => [ 'shape' => 'TrialComponentArn', ], ], ], 'DeleteTrialRequest' => [ 'type' => 'structure', 'required' => [ 'TrialName', ], 'members' => [ 'TrialName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DeleteTrialResponse' => [ 'type' => 'structure', 'members' => [ 'TrialArn' => [ 'shape' => 'TrialArn', ], ], ], 'DeleteUserProfileRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'UserProfileName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], ], ], 'DeleteWorkforceRequest' => [ 'type' => 'structure', 'required' => [ 'WorkforceName', ], 'members' => [ 'WorkforceName' => [ 'shape' => 'WorkforceName', ], ], ], 'DeleteWorkforceResponse' => [ 'type' => 'structure', 'members' => [], ], 'DeleteWorkteamRequest' => [ 'type' => 'structure', 'required' => [ 'WorkteamName', ], 'members' => [ 'WorkteamName' => [ 'shape' => 'WorkteamName', ], ], ], 'DeleteWorkteamResponse' => [ 'type' => 'structure', 'required' => [ 'Success', ], 'members' => [ 'Success' => [ 'shape' => 'Success', ], ], ], 'DependencyCopyPath' => [ 'type' => 'string', 'max' => 1023, 'pattern' => '.*', ], 'DependencyOriginPath' => [ 'type' => 'string', 'max' => 1023, 'pattern' => '.*', ], 'DeployedImage' => [ 'type' => 'structure', 'members' => [ 'SpecifiedImage' => [ 'shape' => 'ContainerImage', ], 'ResolvedImage' => [ 'shape' => 'ContainerImage', ], 'ResolutionTime' => [ 'shape' => 'Timestamp', ], ], ], 'DeployedImages' => [ 'type' => 'list', 'member' => [ 'shape' => 'DeployedImage', ], ], 'DeploymentConfig' => [ 'type' => 'structure', 'members' => [ 'BlueGreenUpdatePolicy' => [ 'shape' => 'BlueGreenUpdatePolicy', ], 'RollingUpdatePolicy' => [ 'shape' => 'RollingUpdatePolicy', ], 'AutoRollbackConfiguration' => [ 'shape' => 'AutoRollbackConfig', ], ], ], 'DeploymentRecommendation' => [ 'type' => 'structure', 'required' => [ 'RecommendationStatus', ], 'members' => [ 'RecommendationStatus' => [ 'shape' => 'RecommendationStatus', ], 'RealTimeInferenceRecommendations' => [ 'shape' => 'RealTimeInferenceRecommendations', ], ], ], 'DeploymentStage' => [ 'type' => 'structure', 'required' => [ 'StageName', 'DeviceSelectionConfig', ], 'members' => [ 'StageName' => [ 'shape' => 'EntityName', ], 'DeviceSelectionConfig' => [ 'shape' => 'DeviceSelectionConfig', ], 'DeploymentConfig' => [ 'shape' => 'EdgeDeploymentConfig', ], ], ], 'DeploymentStageMaxResults' => [ 'type' => 'integer', 'max' => 10, ], 'DeploymentStageStatusSummaries' => [ 'type' => 'list', 'member' => [ 'shape' => 'DeploymentStageStatusSummary', ], ], 'DeploymentStageStatusSummary' => [ 'type' => 'structure', 'required' => [ 'StageName', 'DeviceSelectionConfig', 'DeploymentConfig', 'DeploymentStatus', ], 'members' => [ 'StageName' => [ 'shape' => 'EntityName', ], 'DeviceSelectionConfig' => [ 'shape' => 'DeviceSelectionConfig', ], 'DeploymentConfig' => [ 'shape' => 'EdgeDeploymentConfig', ], 'DeploymentStatus' => [ 'shape' => 'EdgeDeploymentStatus', ], ], ], 'DeploymentStages' => [ 'type' => 'list', 'member' => [ 'shape' => 'DeploymentStage', ], ], 'DeregisterDevicesRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'DeviceNames', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'DeviceNames' => [ 'shape' => 'DeviceNames', ], ], ], 'DerivedInformation' => [ 'type' => 'structure', 'members' => [ 'DerivedDataInputConfig' => [ 'shape' => 'DataInputConfig', ], ], ], 'DescribeActionRequest' => [ 'type' => 'structure', 'required' => [ 'ActionName', ], 'members' => [ 'ActionName' => [ 'shape' => 'ExperimentEntityNameOrArn', ], ], ], 'DescribeActionResponse' => [ 'type' => 'structure', 'members' => [ 'ActionName' => [ 'shape' => 'ExperimentEntityNameOrArn', ], 'ActionArn' => [ 'shape' => 'ActionArn', ], 'Source' => [ 'shape' => 'ActionSource', ], 'ActionType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Status' => [ 'shape' => 'ActionStatus', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeAlgorithmInput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmName', ], 'members' => [ 'AlgorithmName' => [ 'shape' => 'ArnOrName', ], ], ], 'DescribeAlgorithmOutput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmName', 'AlgorithmArn', 'CreationTime', 'TrainingSpecification', 'AlgorithmStatus', 'AlgorithmStatusDetails', ], 'members' => [ 'AlgorithmName' => [ 'shape' => 'EntityName', ], 'AlgorithmArn' => [ 'shape' => 'AlgorithmArn', ], 'AlgorithmDescription' => [ 'shape' => 'EntityDescription', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'TrainingSpecification' => [ 'shape' => 'TrainingSpecification', ], 'InferenceSpecification' => [ 'shape' => 'InferenceSpecification', ], 'ValidationSpecification' => [ 'shape' => 'AlgorithmValidationSpecification', ], 'AlgorithmStatus' => [ 'shape' => 'AlgorithmStatus', ], 'AlgorithmStatusDetails' => [ 'shape' => 'AlgorithmStatusDetails', ], 'ProductId' => [ 'shape' => 'ProductId', ], 'CertifyForMarketplace' => [ 'shape' => 'CertifyForMarketplace', ], ], ], 'DescribeAppImageConfigRequest' => [ 'type' => 'structure', 'required' => [ 'AppImageConfigName', ], 'members' => [ 'AppImageConfigName' => [ 'shape' => 'AppImageConfigName', ], ], ], 'DescribeAppImageConfigResponse' => [ 'type' => 'structure', 'members' => [ 'AppImageConfigArn' => [ 'shape' => 'AppImageConfigArn', ], 'AppImageConfigName' => [ 'shape' => 'AppImageConfigName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'KernelGatewayImageConfig' => [ 'shape' => 'KernelGatewayImageConfig', ], 'JupyterLabAppImageConfig' => [ 'shape' => 'JupyterLabAppImageConfig', ], ], ], 'DescribeAppRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'AppType', 'AppName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], 'AppType' => [ 'shape' => 'AppType', ], 'AppName' => [ 'shape' => 'AppName', ], ], ], 'DescribeAppResponse' => [ 'type' => 'structure', 'members' => [ 'AppArn' => [ 'shape' => 'AppArn', ], 'AppType' => [ 'shape' => 'AppType', ], 'AppName' => [ 'shape' => 'AppName', ], 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], 'Status' => [ 'shape' => 'AppStatus', ], 'LastHealthCheckTimestamp' => [ 'shape' => 'Timestamp', ], 'LastUserActivityTimestamp' => [ 'shape' => 'Timestamp', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ResourceSpec' => [ 'shape' => 'ResourceSpec', ], ], ], 'DescribeArtifactRequest' => [ 'type' => 'structure', 'required' => [ 'ArtifactArn', ], 'members' => [ 'ArtifactArn' => [ 'shape' => 'ArtifactArn', ], ], ], 'DescribeArtifactResponse' => [ 'type' => 'structure', 'members' => [ 'ArtifactName' => [ 'shape' => 'ExperimentEntityNameOrArn', ], 'ArtifactArn' => [ 'shape' => 'ArtifactArn', ], 'Source' => [ 'shape' => 'ArtifactSource', ], 'ArtifactType' => [ 'shape' => 'String256', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeAutoMLJobRequest' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], ], ], 'DescribeAutoMLJobResponse' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobArn', 'InputDataConfig', 'OutputDataConfig', 'RoleArn', 'CreationTime', 'LastModifiedTime', 'AutoMLJobStatus', 'AutoMLJobSecondaryStatus', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], 'InputDataConfig' => [ 'shape' => 'AutoMLInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'ProblemType' => [ 'shape' => 'ProblemType', ], 'AutoMLJobConfig' => [ 'shape' => 'AutoMLJobConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'AutoMLFailureReason', ], 'PartialFailureReasons' => [ 'shape' => 'AutoMLPartialFailureReasons', ], 'BestCandidate' => [ 'shape' => 'AutoMLCandidate', ], 'AutoMLJobStatus' => [ 'shape' => 'AutoMLJobStatus', ], 'AutoMLJobSecondaryStatus' => [ 'shape' => 'AutoMLJobSecondaryStatus', ], 'GenerateCandidateDefinitionsOnly' => [ 'shape' => 'GenerateCandidateDefinitionsOnly', ], 'AutoMLJobArtifacts' => [ 'shape' => 'AutoMLJobArtifacts', ], 'ResolvedAttributes' => [ 'shape' => 'ResolvedAttributes', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'ModelDeployResult' => [ 'shape' => 'ModelDeployResult', ], ], ], 'DescribeAutoMLJobV2Request' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], ], ], 'DescribeAutoMLJobV2Response' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobArn', 'AutoMLJobInputDataConfig', 'OutputDataConfig', 'RoleArn', 'CreationTime', 'LastModifiedTime', 'AutoMLJobStatus', 'AutoMLJobSecondaryStatus', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], 'AutoMLJobInputDataConfig' => [ 'shape' => 'AutoMLJobInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'AutoMLProblemTypeConfig' => [ 'shape' => 'AutoMLProblemTypeConfig', ], 'AutoMLProblemTypeConfigName' => [ 'shape' => 'AutoMLProblemTypeConfigName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'AutoMLFailureReason', ], 'PartialFailureReasons' => [ 'shape' => 'AutoMLPartialFailureReasons', ], 'BestCandidate' => [ 'shape' => 'AutoMLCandidate', ], 'AutoMLJobStatus' => [ 'shape' => 'AutoMLJobStatus', ], 'AutoMLJobSecondaryStatus' => [ 'shape' => 'AutoMLJobSecondaryStatus', ], 'AutoMLJobArtifacts' => [ 'shape' => 'AutoMLJobArtifacts', ], 'ResolvedAttributes' => [ 'shape' => 'AutoMLResolvedAttributes', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'ModelDeployResult' => [ 'shape' => 'ModelDeployResult', ], 'DataSplitConfig' => [ 'shape' => 'AutoMLDataSplitConfig', ], 'SecurityConfig' => [ 'shape' => 'AutoMLSecurityConfig', ], ], ], 'DescribeClusterNodeRequest' => [ 'type' => 'structure', 'required' => [ 'ClusterName', 'NodeId', ], 'members' => [ 'ClusterName' => [ 'shape' => 'ClusterNameOrArn', ], 'NodeId' => [ 'shape' => 'ClusterNodeId', ], ], ], 'DescribeClusterNodeResponse' => [ 'type' => 'structure', 'required' => [ 'NodeDetails', ], 'members' => [ 'NodeDetails' => [ 'shape' => 'ClusterNodeDetails', ], ], ], 'DescribeClusterRequest' => [ 'type' => 'structure', 'required' => [ 'ClusterName', ], 'members' => [ 'ClusterName' => [ 'shape' => 'ClusterNameOrArn', ], ], ], 'DescribeClusterResponse' => [ 'type' => 'structure', 'required' => [ 'ClusterArn', 'ClusterStatus', 'InstanceGroups', ], 'members' => [ 'ClusterArn' => [ 'shape' => 'ClusterArn', ], 'ClusterName' => [ 'shape' => 'ClusterName', ], 'ClusterStatus' => [ 'shape' => 'ClusterStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'FailureMessage' => [ 'shape' => 'String', ], 'InstanceGroups' => [ 'shape' => 'ClusterInstanceGroupDetailsList', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], ], ], 'DescribeCodeRepositoryInput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeCodeRepositoryOutput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', 'CodeRepositoryArn', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], 'CodeRepositoryArn' => [ 'shape' => 'CodeRepositoryArn', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'GitConfig' => [ 'shape' => 'GitConfig', ], ], ], 'DescribeCompilationJobRequest' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeCompilationJobResponse' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', 'CompilationJobArn', 'CompilationJobStatus', 'StoppingCondition', 'CreationTime', 'LastModifiedTime', 'FailureReason', 'ModelArtifacts', 'RoleArn', 'InputConfig', 'OutputConfig', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobArn' => [ 'shape' => 'CompilationJobArn', ], 'CompilationJobStatus' => [ 'shape' => 'CompilationJobStatus', ], 'CompilationStartTime' => [ 'shape' => 'Timestamp', ], 'CompilationEndTime' => [ 'shape' => 'Timestamp', ], 'StoppingCondition' => [ 'shape' => 'StoppingCondition', ], 'InferenceImage' => [ 'shape' => 'InferenceImage', ], 'ModelPackageVersionArn' => [ 'shape' => 'ModelPackageArn', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ModelArtifacts' => [ 'shape' => 'ModelArtifacts', ], 'ModelDigests' => [ 'shape' => 'ModelDigests', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'InputConfig' => [ 'shape' => 'InputConfig', ], 'OutputConfig' => [ 'shape' => 'OutputConfig', ], 'VpcConfig' => [ 'shape' => 'NeoVpcConfig', ], 'DerivedInformation' => [ 'shape' => 'DerivedInformation', ], ], ], 'DescribeContextRequest' => [ 'type' => 'structure', 'required' => [ 'ContextName', ], 'members' => [ 'ContextName' => [ 'shape' => 'ContextNameOrArn', ], ], ], 'DescribeContextResponse' => [ 'type' => 'structure', 'members' => [ 'ContextName' => [ 'shape' => 'ContextName', ], 'ContextArn' => [ 'shape' => 'ContextArn', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeDataQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeDataQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'DataQualityAppSpecification', 'DataQualityJobInput', 'DataQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'DataQualityBaselineConfig' => [ 'shape' => 'DataQualityBaselineConfig', ], 'DataQualityAppSpecification' => [ 'shape' => 'DataQualityAppSpecification', ], 'DataQualityJobInput' => [ 'shape' => 'DataQualityJobInput', ], 'DataQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeDeviceFleetRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeDeviceFleetResponse' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'DeviceFleetArn', 'OutputConfig', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'DeviceFleetArn' => [ 'shape' => 'DeviceFleetArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'Description' => [ 'shape' => 'DeviceFleetDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'IotRoleAlias' => [ 'shape' => 'IotRoleAlias', ], ], ], 'DescribeDeviceRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceName', 'DeviceFleetName', ], 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'DeviceName' => [ 'shape' => 'EntityName', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeDeviceResponse' => [ 'type' => 'structure', 'required' => [ 'DeviceName', 'DeviceFleetName', 'RegistrationTime', ], 'members' => [ 'DeviceArn' => [ 'shape' => 'DeviceArn', ], 'DeviceName' => [ 'shape' => 'EntityName', ], 'Description' => [ 'shape' => 'DeviceDescription', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'IotThingName' => [ 'shape' => 'ThingName', ], 'RegistrationTime' => [ 'shape' => 'Timestamp', ], 'LatestHeartbeat' => [ 'shape' => 'Timestamp', ], 'Models' => [ 'shape' => 'EdgeModels', ], 'MaxModels' => [ 'shape' => 'Integer', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'AgentVersion' => [ 'shape' => 'EdgeVersion', ], ], ], 'DescribeDomainRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], ], ], 'DescribeDomainResponse' => [ 'type' => 'structure', 'members' => [ 'DomainArn' => [ 'shape' => 'DomainArn', ], 'DomainId' => [ 'shape' => 'DomainId', ], 'DomainName' => [ 'shape' => 'DomainName', ], 'HomeEfsFileSystemId' => [ 'shape' => 'ResourceId', ], 'SingleSignOnManagedApplicationInstanceId' => [ 'shape' => 'String256', ], 'SingleSignOnApplicationArn' => [ 'shape' => 'SingleSignOnApplicationArn', ], 'Status' => [ 'shape' => 'DomainStatus', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'SecurityGroupIdForDomainBoundary' => [ 'shape' => 'SecurityGroupId', ], 'AuthMode' => [ 'shape' => 'AuthMode', ], 'DefaultUserSettings' => [ 'shape' => 'UserSettings', ], 'DomainSettings' => [ 'shape' => 'DomainSettings', ], 'AppNetworkAccessType' => [ 'shape' => 'AppNetworkAccessType', ], 'HomeEfsFileSystemKmsKeyId' => [ 'shape' => 'KmsKeyId', 'deprecated' => true, 'deprecatedMessage' => 'This property is deprecated, use KmsKeyId instead.', ], 'SubnetIds' => [ 'shape' => 'Subnets', ], 'Url' => [ 'shape' => 'String1024', ], 'VpcId' => [ 'shape' => 'VpcId', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AppSecurityGroupManagement' => [ 'shape' => 'AppSecurityGroupManagement', ], 'DefaultSpaceSettings' => [ 'shape' => 'DefaultSpaceSettings', ], ], ], 'DescribeEdgeDeploymentPlanRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'MaxResults' => [ 'shape' => 'DeploymentStageMaxResults', ], ], ], 'DescribeEdgeDeploymentPlanResponse' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanArn', 'EdgeDeploymentPlanName', 'ModelConfigs', 'DeviceFleetName', 'Stages', ], 'members' => [ 'EdgeDeploymentPlanArn' => [ 'shape' => 'EdgeDeploymentPlanArn', ], 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'ModelConfigs' => [ 'shape' => 'EdgeDeploymentModelConfigs', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'EdgeDeploymentSuccess' => [ 'shape' => 'Integer', ], 'EdgeDeploymentPending' => [ 'shape' => 'Integer', ], 'EdgeDeploymentFailed' => [ 'shape' => 'Integer', ], 'Stages' => [ 'shape' => 'DeploymentStageStatusSummaries', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeEdgePackagingJobRequest' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobName', ], 'members' => [ 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeEdgePackagingJobResponse' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobArn', 'EdgePackagingJobName', 'EdgePackagingJobStatus', ], 'members' => [ 'EdgePackagingJobArn' => [ 'shape' => 'EdgePackagingJobArn', ], 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'ModelName' => [ 'shape' => 'EntityName', ], 'ModelVersion' => [ 'shape' => 'EdgeVersion', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'ResourceKey' => [ 'shape' => 'KmsKeyId', ], 'EdgePackagingJobStatus' => [ 'shape' => 'EdgePackagingJobStatus', ], 'EdgePackagingJobStatusMessage' => [ 'shape' => 'String', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'ModelArtifact' => [ 'shape' => 'S3Uri', ], 'ModelSignature' => [ 'shape' => 'String', ], 'PresetDeploymentOutput' => [ 'shape' => 'EdgePresetDeploymentOutput', ], ], ], 'DescribeEndpointConfigInput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], ], ], 'DescribeEndpointConfigOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', 'EndpointConfigArn', 'ProductionVariants', 'CreationTime', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'EndpointConfigArn' => [ 'shape' => 'EndpointConfigArn', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfig', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'ExecutionRoleArn' => [ 'shape' => 'RoleArn', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'EnableNetworkIsolation' => [ 'shape' => 'Boolean', ], ], ], 'DescribeEndpointInput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], ], ], 'DescribeEndpointOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', 'EndpointArn', 'EndpointStatus', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointArn' => [ 'shape' => 'EndpointArn', ], 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantSummaryList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfigSummary', ], 'EndpointStatus' => [ 'shape' => 'EndpointStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastDeploymentConfig' => [ 'shape' => 'DeploymentConfig', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'PendingDeploymentSummary' => [ 'shape' => 'PendingDeploymentSummary', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantSummaryList', ], ], ], 'DescribeExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'ExperimentName', ], 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DescribeExperimentResponse' => [ 'type' => 'structure', 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], 'ExperimentArn' => [ 'shape' => 'ExperimentArn', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ExperimentSource', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeFeatureGroupRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupNameOrArn', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'DescribeFeatureGroupResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', 'FeatureGroupName', 'RecordIdentifierFeatureName', 'EventTimeFeatureName', 'FeatureDefinitions', 'CreationTime', 'NextToken', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'RecordIdentifierFeatureName' => [ 'shape' => 'FeatureName', ], 'EventTimeFeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureDefinitions' => [ 'shape' => 'FeatureDefinitions', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'OnlineStoreConfig' => [ 'shape' => 'OnlineStoreConfig', ], 'OfflineStoreConfig' => [ 'shape' => 'OfflineStoreConfig', ], 'ThroughputConfig' => [ 'shape' => 'ThroughputConfigDescription', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'FeatureGroupStatus' => [ 'shape' => 'FeatureGroupStatus', ], 'OfflineStoreStatus' => [ 'shape' => 'OfflineStoreStatus', ], 'LastUpdateStatus' => [ 'shape' => 'LastUpdateStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'Description' => [ 'shape' => 'Description', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'OnlineStoreTotalSizeBytes' => [ 'shape' => 'OnlineStoreTotalSizeBytes', ], ], ], 'DescribeFeatureMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', 'FeatureName', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupNameOrArn', ], 'FeatureName' => [ 'shape' => 'FeatureName', ], ], ], 'DescribeFeatureMetadataResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', 'FeatureGroupName', 'FeatureName', 'FeatureType', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'FeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureType' => [ 'shape' => 'FeatureType', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'Description' => [ 'shape' => 'FeatureDescription', ], 'Parameters' => [ 'shape' => 'FeatureParameters', ], ], ], 'DescribeFlowDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionName', ], 'members' => [ 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], ], ], 'DescribeFlowDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionArn', 'FlowDefinitionName', 'FlowDefinitionStatus', 'CreationTime', 'OutputConfig', 'RoleArn', ], 'members' => [ 'FlowDefinitionArn' => [ 'shape' => 'FlowDefinitionArn', ], 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], 'FlowDefinitionStatus' => [ 'shape' => 'FlowDefinitionStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'HumanLoopRequestSource' => [ 'shape' => 'HumanLoopRequestSource', ], 'HumanLoopActivationConfig' => [ 'shape' => 'HumanLoopActivationConfig', ], 'HumanLoopConfig' => [ 'shape' => 'HumanLoopConfig', ], 'OutputConfig' => [ 'shape' => 'FlowDefinitionOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], ], ], 'DescribeHubContentRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubContentType', 'HubContentName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], ], ], 'DescribeHubContentResponse' => [ 'type' => 'structure', 'required' => [ 'HubContentName', 'HubContentArn', 'HubContentVersion', 'HubContentType', 'DocumentSchemaVersion', 'HubName', 'HubArn', 'HubContentDocument', 'HubContentStatus', 'CreationTime', ], 'members' => [ 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentArn' => [ 'shape' => 'HubContentArn', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'DocumentSchemaVersion' => [ 'shape' => 'DocumentSchemaVersion', ], 'HubName' => [ 'shape' => 'HubName', ], 'HubArn' => [ 'shape' => 'HubArn', ], 'HubContentDisplayName' => [ 'shape' => 'HubContentDisplayName', ], 'HubContentDescription' => [ 'shape' => 'HubContentDescription', ], 'HubContentMarkdown' => [ 'shape' => 'HubContentMarkdown', ], 'HubContentDocument' => [ 'shape' => 'HubContentDocument', ], 'HubContentSearchKeywords' => [ 'shape' => 'HubContentSearchKeywordList', ], 'HubContentDependencies' => [ 'shape' => 'HubContentDependencyList', ], 'HubContentStatus' => [ 'shape' => 'HubContentStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], ], ], 'DescribeHubResponse' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubArn', 'HubStatus', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubArn' => [ 'shape' => 'HubArn', ], 'HubDisplayName' => [ 'shape' => 'HubDisplayName', ], 'HubDescription' => [ 'shape' => 'HubDescription', ], 'HubSearchKeywords' => [ 'shape' => 'HubSearchKeywordList', ], 'S3StorageConfig' => [ 'shape' => 'HubS3StorageConfig', ], 'HubStatus' => [ 'shape' => 'HubStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], ], ], 'DescribeHumanTaskUiResponse' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiArn', 'HumanTaskUiName', 'CreationTime', 'UiTemplate', ], 'members' => [ 'HumanTaskUiArn' => [ 'shape' => 'HumanTaskUiArn', ], 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], 'HumanTaskUiStatus' => [ 'shape' => 'HumanTaskUiStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'UiTemplate' => [ 'shape' => 'UiTemplateInfo', ], ], ], 'DescribeHyperParameterTuningJobRequest' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], ], ], 'DescribeHyperParameterTuningJobResponse' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', 'HyperParameterTuningJobArn', 'HyperParameterTuningJobConfig', 'HyperParameterTuningJobStatus', 'CreationTime', 'TrainingJobStatusCounters', 'ObjectiveStatusCounters', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], 'HyperParameterTuningJobArn' => [ 'shape' => 'HyperParameterTuningJobArn', ], 'HyperParameterTuningJobConfig' => [ 'shape' => 'HyperParameterTuningJobConfig', ], 'TrainingJobDefinition' => [ 'shape' => 'HyperParameterTrainingJobDefinition', ], 'TrainingJobDefinitions' => [ 'shape' => 'HyperParameterTrainingJobDefinitions', ], 'HyperParameterTuningJobStatus' => [ 'shape' => 'HyperParameterTuningJobStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'HyperParameterTuningEndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'TrainingJobStatusCounters' => [ 'shape' => 'TrainingJobStatusCounters', ], 'ObjectiveStatusCounters' => [ 'shape' => 'ObjectiveStatusCounters', ], 'BestTrainingJob' => [ 'shape' => 'HyperParameterTrainingJobSummary', ], 'OverallBestTrainingJob' => [ 'shape' => 'HyperParameterTrainingJobSummary', ], 'WarmStartConfig' => [ 'shape' => 'HyperParameterTuningJobWarmStartConfig', ], 'Autotune' => [ 'shape' => 'Autotune', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'TuningJobCompletionDetails' => [ 'shape' => 'HyperParameterTuningJobCompletionDetails', ], 'ConsumedResources' => [ 'shape' => 'HyperParameterTuningJobConsumedResources', ], ], ], 'DescribeImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], ], ], 'DescribeImageResponse' => [ 'type' => 'structure', 'members' => [ 'CreationTime' => [ 'shape' => 'Timestamp', ], 'Description' => [ 'shape' => 'ImageDescription', ], 'DisplayName' => [ 'shape' => 'ImageDisplayName', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ImageArn' => [ 'shape' => 'ImageArn', ], 'ImageName' => [ 'shape' => 'ImageName', ], 'ImageStatus' => [ 'shape' => 'ImageStatus', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], ], ], 'DescribeImageVersionRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], 'Version' => [ 'shape' => 'ImageVersionNumber', ], 'Alias' => [ 'shape' => 'SageMakerImageVersionAlias', ], ], ], 'DescribeImageVersionResponse' => [ 'type' => 'structure', 'members' => [ 'BaseImage' => [ 'shape' => 'ImageBaseImage', ], 'ContainerImage' => [ 'shape' => 'ImageContainerImage', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ImageArn' => [ 'shape' => 'ImageArn', ], 'ImageVersionArn' => [ 'shape' => 'ImageVersionArn', ], 'ImageVersionStatus' => [ 'shape' => 'ImageVersionStatus', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'Version' => [ 'shape' => 'ImageVersionNumber', ], 'VendorGuidance' => [ 'shape' => 'VendorGuidance', ], 'JobType' => [ 'shape' => 'JobType', ], 'MLFramework' => [ 'shape' => 'MLFramework', ], 'ProgrammingLang' => [ 'shape' => 'ProgrammingLang', ], 'Processor' => [ 'shape' => 'Processor', ], 'Horovod' => [ 'shape' => 'Horovod', ], 'ReleaseNotes' => [ 'shape' => 'ReleaseNotes', ], ], ], 'DescribeInferenceComponentInput' => [ 'type' => 'structure', 'required' => [ 'InferenceComponentName', ], 'members' => [ 'InferenceComponentName' => [ 'shape' => 'InferenceComponentName', ], ], ], 'DescribeInferenceComponentOutput' => [ 'type' => 'structure', 'required' => [ 'InferenceComponentName', 'InferenceComponentArn', 'EndpointName', 'EndpointArn', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'InferenceComponentName' => [ 'shape' => 'InferenceComponentName', ], 'InferenceComponentArn' => [ 'shape' => 'InferenceComponentArn', ], 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointArn' => [ 'shape' => 'EndpointArn', ], 'VariantName' => [ 'shape' => 'VariantName', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'Specification' => [ 'shape' => 'InferenceComponentSpecificationSummary', ], 'RuntimeConfig' => [ 'shape' => 'InferenceComponentRuntimeConfigSummary', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'InferenceComponentStatus' => [ 'shape' => 'InferenceComponentStatus', ], ], ], 'DescribeInferenceExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'Name', ], 'members' => [ 'Name' => [ 'shape' => 'InferenceExperimentName', ], ], ], 'DescribeInferenceExperimentResponse' => [ 'type' => 'structure', 'required' => [ 'Arn', 'Name', 'Type', 'Status', 'EndpointMetadata', 'ModelVariants', ], 'members' => [ 'Arn' => [ 'shape' => 'InferenceExperimentArn', ], 'Name' => [ 'shape' => 'InferenceExperimentName', ], 'Type' => [ 'shape' => 'InferenceExperimentType', ], 'Schedule' => [ 'shape' => 'InferenceExperimentSchedule', ], 'Status' => [ 'shape' => 'InferenceExperimentStatus', ], 'StatusReason' => [ 'shape' => 'InferenceExperimentStatusReason', ], 'Description' => [ 'shape' => 'InferenceExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CompletionTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'EndpointMetadata' => [ 'shape' => 'EndpointMetadata', ], 'ModelVariants' => [ 'shape' => 'ModelVariantConfigSummaryList', ], 'DataStorageConfig' => [ 'shape' => 'InferenceExperimentDataStorageConfig', ], 'ShadowModeConfig' => [ 'shape' => 'ShadowModeConfig', ], 'KmsKey' => [ 'shape' => 'KmsKeyId', ], ], ], 'DescribeInferenceRecommendationsJobRequest' => [ 'type' => 'structure', 'required' => [ 'JobName', ], 'members' => [ 'JobName' => [ 'shape' => 'RecommendationJobName', ], ], ], 'DescribeInferenceRecommendationsJobResponse' => [ 'type' => 'structure', 'required' => [ 'JobName', 'JobType', 'JobArn', 'RoleArn', 'Status', 'CreationTime', 'LastModifiedTime', 'InputConfig', ], 'members' => [ 'JobName' => [ 'shape' => 'RecommendationJobName', ], 'JobDescription' => [ 'shape' => 'RecommendationJobDescription', ], 'JobType' => [ 'shape' => 'RecommendationJobType', ], 'JobArn' => [ 'shape' => 'RecommendationJobArn', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Status' => [ 'shape' => 'RecommendationJobStatus', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'CompletionTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'InputConfig' => [ 'shape' => 'RecommendationJobInputConfig', ], 'StoppingConditions' => [ 'shape' => 'RecommendationJobStoppingConditions', ], 'InferenceRecommendations' => [ 'shape' => 'InferenceRecommendations', ], 'EndpointPerformances' => [ 'shape' => 'EndpointPerformances', ], ], ], 'DescribeLabelingJobRequest' => [ 'type' => 'structure', 'required' => [ 'LabelingJobName', ], 'members' => [ 'LabelingJobName' => [ 'shape' => 'LabelingJobName', ], ], ], 'DescribeLabelingJobResponse' => [ 'type' => 'structure', 'required' => [ 'LabelingJobStatus', 'LabelCounters', 'CreationTime', 'LastModifiedTime', 'JobReferenceCode', 'LabelingJobName', 'LabelingJobArn', 'InputConfig', 'OutputConfig', 'RoleArn', 'HumanTaskConfig', ], 'members' => [ 'LabelingJobStatus' => [ 'shape' => 'LabelingJobStatus', ], 'LabelCounters' => [ 'shape' => 'LabelCounters', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'JobReferenceCode' => [ 'shape' => 'JobReferenceCode', ], 'LabelingJobName' => [ 'shape' => 'LabelingJobName', ], 'LabelingJobArn' => [ 'shape' => 'LabelingJobArn', ], 'LabelAttributeName' => [ 'shape' => 'LabelAttributeName', ], 'InputConfig' => [ 'shape' => 'LabelingJobInputConfig', ], 'OutputConfig' => [ 'shape' => 'LabelingJobOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'LabelCategoryConfigS3Uri' => [ 'shape' => 'S3Uri', ], 'StoppingConditions' => [ 'shape' => 'LabelingJobStoppingConditions', ], 'LabelingJobAlgorithmsConfig' => [ 'shape' => 'LabelingJobAlgorithmsConfig', ], 'HumanTaskConfig' => [ 'shape' => 'HumanTaskConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'LabelingJobOutput' => [ 'shape' => 'LabelingJobOutput', ], ], ], 'DescribeLineageGroupRequest' => [ 'type' => 'structure', 'required' => [ 'LineageGroupName', ], 'members' => [ 'LineageGroupName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DescribeLineageGroupResponse' => [ 'type' => 'structure', 'members' => [ 'LineageGroupName' => [ 'shape' => 'ExperimentEntityName', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeModelBiasJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelBiasJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelBiasAppSpecification', 'ModelBiasJobInput', 'ModelBiasJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelBiasBaselineConfig' => [ 'shape' => 'ModelBiasBaselineConfig', ], 'ModelBiasAppSpecification' => [ 'shape' => 'ModelBiasAppSpecification', ], 'ModelBiasJobInput' => [ 'shape' => 'ModelBiasJobInput', ], 'ModelBiasJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeModelCardExportJobRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardExportJobArn', ], 'members' => [ 'ModelCardExportJobArn' => [ 'shape' => 'ModelCardExportJobArn', ], ], ], 'DescribeModelCardExportJobResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardExportJobName', 'ModelCardExportJobArn', 'Status', 'ModelCardName', 'ModelCardVersion', 'OutputConfig', 'CreatedAt', 'LastModifiedAt', ], 'members' => [ 'ModelCardExportJobName' => [ 'shape' => 'EntityName', ], 'ModelCardExportJobArn' => [ 'shape' => 'ModelCardExportJobArn', ], 'Status' => [ 'shape' => 'ModelCardExportJobStatus', ], 'ModelCardName' => [ 'shape' => 'EntityName', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'OutputConfig' => [ 'shape' => 'ModelCardExportOutputConfig', ], 'CreatedAt' => [ 'shape' => 'Timestamp', ], 'LastModifiedAt' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ExportArtifacts' => [ 'shape' => 'ModelCardExportArtifacts', ], ], ], 'DescribeModelCardRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'ModelCardNameOrArn', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], ], ], 'DescribeModelCardResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardArn', 'ModelCardName', 'ModelCardVersion', 'Content', 'ModelCardStatus', 'CreationTime', 'CreatedBy', ], 'members' => [ 'ModelCardArn' => [ 'shape' => 'ModelCardArn', ], 'ModelCardName' => [ 'shape' => 'EntityName', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'Content' => [ 'shape' => 'ModelCardContent', ], 'ModelCardStatus' => [ 'shape' => 'ModelCardStatus', ], 'SecurityConfig' => [ 'shape' => 'ModelCardSecurityConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'ModelCardProcessingStatus' => [ 'shape' => 'ModelCardProcessingStatus', ], ], ], 'DescribeModelExplainabilityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelExplainabilityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelExplainabilityAppSpecification', 'ModelExplainabilityJobInput', 'ModelExplainabilityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelExplainabilityBaselineConfig' => 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'TargetCpuUtilizationPerCore' => [ 'shape' => 'UtilizationPercentagePerCore', ], 'ScalingPolicyObjective' => [ 'shape' => 'ScalingPolicyObjective', ], 'Metric' => [ 'shape' => 'ScalingPolicyMetric', ], 'DynamicScalingConfiguration' => [ 'shape' => 'DynamicScalingConfiguration', ], ], ], 'GetSearchSuggestionsRequest' => [ 'type' => 'structure', 'required' => [ 'Resource', ], 'members' => [ 'Resource' => [ 'shape' => 'ResourceType', ], 'SuggestionQuery' => [ 'shape' => 'SuggestionQuery', ], ], ], 'GetSearchSuggestionsResponse' => [ 'type' => 'structure', 'members' => [ 'PropertyNameSuggestions' => [ 'shape' => 'PropertyNameSuggestionList', ], ], ], 'Gid' => [ 'type' => 'long', 'max' => 4000000, 'min' => 1001, ], 'GitConfig' => [ 'type' => 'structure', 'required' => [ 'RepositoryUrl', ], 'members' => [ 'RepositoryUrl' => [ 'shape' => 'GitConfigUrl', ], 'Branch' => [ 'shape' => 'Branch', ], 'SecretArn' => [ 'shape' => 'SecretArn', ], ], ], 'GitConfigForUpdate' => [ 'type' => 'structure', 'members' => [ 'SecretArn' => [ 'shape' => 'SecretArn', ], ], ], 'GitConfigUrl' => [ 'type' => 'string', 'max' => 1024, 'min' => 11, 'pattern' => '^https://([^/]+)/?.{3,1016}$', ], 'Group' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '[\\p{L}\\p{M}\\p{S}\\p{N}\\p{P}]+', ], 'GroupingAttributeName' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'GroupingAttributeNames' => [ 'type' => 'list', 'member' => [ 'shape' => 'GroupingAttributeName', ], 'max' => 5, 'min' => 1, ], 'Groups' => [ 'type' => 'list', 'member' => [ 'shape' => 'Group', ], 'max' => 10, 'min' => 1, ], 'HolidayConfig' => [ 'type' => 'list', 'member' => [ 'shape' => 'HolidayConfigAttributes', ], 'max' => 1, 'min' => 1, ], 'HolidayConfigAttributes' => [ 'type' => 'structure', 'members' => [ 'CountryCode' => [ 'shape' => 'CountryCode', ], ], ], 'HookParameters' => [ 'type' => 'map', 'key' => [ 'shape' => 'ConfigKey', ], 'value' => [ 'shape' => 'ConfigValue', ], 'max' => 20, 'min' => 0, ], 'Horovod' => [ 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=> 'NotebookInstanceLifecycleConfigName', ], 'OnCreate' => [ 'shape' => 'NotebookInstanceLifecycleConfigList', ], 'OnStart' => [ 'shape' => 'NotebookInstanceLifecycleConfigList', ], ], ], 'UpdateNotebookInstanceLifecycleConfigOutput' => [ 'type' => 'structure', 'members' => [], ], 'UpdateNotebookInstanceOutput' => [ 'type' => 'structure', 'members' => [], ], 'UpdatePipelineExecutionRequest' => [ 'type' => 'structure', 'required' => [ 'PipelineExecutionArn', ], 'members' => [ 'PipelineExecutionArn' => [ 'shape' => 'PipelineExecutionArn', ], 'PipelineExecutionDescription' => [ 'shape' => 'PipelineExecutionDescription', ], 'PipelineExecutionDisplayName' => [ 'shape' => 'PipelineExecutionName', ], 'ParallelismConfiguration' => [ 'shape' => 'ParallelismConfiguration', ], ], ], 'UpdatePipelineExecutionResponse' => [ 'type' => 'structure', 'members' => [ 'PipelineExecutionArn' => [ 'shape' => 'PipelineExecutionArn', ], ], ], 'UpdatePipelineRequest' => [ 'type' => 'structure', 'required' => [ 'PipelineName', ], 'members' => [ 'PipelineName' => [ 'shape' => 'PipelineName', ], 'PipelineDisplayName' => [ 'shape' => 'PipelineName', ], 'PipelineDefinition' => [ 'shape' => 'PipelineDefinition', ], 'PipelineDefinitionS3Location' => [ 'shape' => 'PipelineDefinitionS3Location', ], 'PipelineDescription' => [ 'shape' => 'PipelineDescription', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'ParallelismConfiguration' => [ 'shape' => 'ParallelismConfiguration', ], ], ], 'UpdatePipelineResponse' => [ 'type' => 'structure', 'members' => [ 'PipelineArn' => [ 'shape' => 'PipelineArn', ], ], ], 'UpdateProjectInput' => [ 'type' => 'structure', 'required' => [ 'ProjectName', ], 'members' => [ 'ProjectName' => [ 'shape' => 'ProjectEntityName', ], 'ProjectDescription' => [ 'shape' => 'EntityDescription', ], 'ServiceCatalogProvisioningUpdateDetails' => [ 'shape' => 'ServiceCatalogProvisioningUpdateDetails', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'UpdateProjectOutput' => [ 'type' => 'structure', 'required' => [ 'ProjectArn', ], 'members' => [ 'ProjectArn' => [ 'shape' => 'ProjectArn', ], ], ], 'UpdateSpaceRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'SpaceName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], 'SpaceSettings' => [ 'shape' => 'SpaceSettings', ], 'SpaceDisplayName' => [ 'shape' => 'NonEmptyString64', ], ], ], 'UpdateSpaceResponse' => [ 'type' => 'structure', 'members' => [ 'SpaceArn' => [ 'shape' => 'SpaceArn', ], ], ], 'UpdateTrainingJobRequest' => [ 'type' => 'structure', 'required' => [ 'TrainingJobName', ], 'members' => [ 'TrainingJobName' => [ 'shape' => 'TrainingJobName', ], 'ProfilerConfig' => [ 'shape' => 'ProfilerConfigForUpdate', ], 'ProfilerRuleConfigurations' => [ 'shape' => 'ProfilerRuleConfigurations', ], 'ResourceConfig' => [ 'shape' => 'ResourceConfigForUpdate', ], 'RemoteDebugConfig' => [ 'shape' => 'RemoteDebugConfigForUpdate', ], ], ], 'UpdateTrainingJobResponse' => [ 'type' => 'structure', 'required' => [ 'TrainingJobArn', ], 'members' => [ 'TrainingJobArn' => [ 'shape' => 'TrainingJobArn', ], ], ], 'UpdateTrialComponentRequest' => [ 'type' => 'structure', 'required' => [ 'TrialComponentName', ], 'members' => [ 'TrialComponentName' => [ 'shape' => 'ExperimentEntityName', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Status' => [ 'shape' => 'TrialComponentStatus', ], 'StartTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], 'Parameters' => [ 'shape' => 'TrialComponentParameters', ], 'ParametersToRemove' => [ 'shape' => 'ListTrialComponentKey256', ], 'InputArtifacts' => [ 'shape' => 'TrialComponentArtifacts', ], 'InputArtifactsToRemove' => [ 'shape' => 'ListTrialComponentKey256', ], 'OutputArtifacts' => [ 'shape' => 'TrialComponentArtifacts', ], 'OutputArtifactsToRemove' => [ 'shape' => 'ListTrialComponentKey256', ], ], ], 'UpdateTrialComponentResponse' => [ 'type' => 'structure', 'members' => [ 'TrialComponentArn' => [ 'shape' => 'TrialComponentArn', ], ], ], 'UpdateTrialRequest' => [ 'type' => 'structure', 'required' => [ 'TrialName', ], 'members' => [ 'TrialName' => [ 'shape' => 'ExperimentEntityName', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'UpdateTrialResponse' => [ 'type' => 'structure', 'members' => [ 'TrialArn' => [ 'shape' => 'TrialArn', ], ], ], 'UpdateUserProfileRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'UserProfileName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'UserSettings' => [ 'shape' => 'UserSettings', ], ], ], 'UpdateUserProfileResponse' => [ 'type' => 'structure', 'members' => [ 'UserProfileArn' => [ 'shape' => 'UserProfileArn', ], ], ], 'UpdateWorkforceRequest' => [ 'type' => 'structure', 'required' => [ 'WorkforceName', ], 'members' => [ 'WorkforceName' => [ 'shape' => 'WorkforceName', ], 'SourceIpConfig' => [ 'shape' => 'SourceIpConfig', ], 'OidcConfig' => [ 'shape' => 'OidcConfig', ], 'WorkforceVpcConfig' => [ 'shape' => 'WorkforceVpcConfigRequest', ], ], ], 'UpdateWorkforceResponse' => [ 'type' => 'structure', 'required' => [ 'Workforce', ], 'members' => [ 'Workforce' => [ 'shape' => 'Workforce', ], ], ], 'UpdateWorkteamRequest' => [ 'type' => 'structure', 'required' => [ 'WorkteamName', ], 'members' => [ 'WorkteamName' => [ 'shape' => 'WorkteamName', ], 'MemberDefinitions' => [ 'shape' => 'MemberDefinitions', ], 'Description' => [ 'shape' => 'String200', ], 'NotificationConfiguration' => [ 'shape' => 'NotificationConfiguration', ], ], ], 'UpdateWorkteamResponse' => [ 'type' => 'structure', 'required' => [ 'Workteam', ], 'members' => [ 'Workteam' => [ 'shape' => 'Workteam', ], ], ], 'Url' => [ 'type' => 'string', 'max' => 1024, 'pattern' => '^(https|s3)://([^/]+)/?(.*)$', ], 'UserContext' => [ 'type' => 'structure', 'members' => [ 'UserProfileArn' => [ 'shape' => 'String', ], 'UserProfileName' => [ 'shape' => 'String', ], 'DomainId' => [ 'shape' => 'String', ], 'IamIdentity' => [ 'shape' => 'IamIdentity', ], ], ], 'UserProfileArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:user-profile/.*', ], 'UserProfileDetails' => [ 'type' => 'structure', 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'Status' => [ 'shape' => 'UserProfileStatus', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], ], ], 'UserProfileList' => [ 'type' => 'list', 'member' => [ 'shape' => 'UserProfileDetails', ], ], 'UserProfileName' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'UserProfileSortKey' => [ 'type' => 'string', 'enum' => [ 'CreationTime', 'LastModifiedTime', ], ], 'UserProfileStatus' => [ 'type' => 'string', 'enum' => [ 'Deleting', 'Failed', 'InService', 'Pending', 'Updating', 'Update_Failed', 'Delete_Failed', ], ], 'UserSettings' => [ 'type' => 'structure', 'members' => [ 'ExecutionRole' => [ 'shape' => 'RoleArn', ], 'SecurityGroups' => [ 'shape' => 'SecurityGroupIds', ], 'SharingSettings' => [ 'shape' => 'SharingSettings', ], 'JupyterServerAppSettings' => [ 'shape' => 'JupyterServerAppSettings', ], 'KernelGatewayAppSettings' => [ 'shape' => 'KernelGatewayAppSettings', ], 'TensorBoardAppSettings' => [ 'shape' => 'TensorBoardAppSettings', ], 'RStudioServerProAppSettings' => [ 'shape' => 'RStudioServerProAppSettings', ], 'RSessionAppSettings' => [ 'shape' => 'RSessionAppSettings', ], 'CanvasAppSettings' => [ 'shape' => 'CanvasAppSettings', ], 'CodeEditorAppSettings' => [ 'shape' => 'CodeEditorAppSettings', ], 'JupyterLabAppSettings' => [ 'shape' => 'JupyterLabAppSettings', ], 'SpaceStorageSettings' => [ 'shape' => 'DefaultSpaceStorageSettings', ], 'DefaultLandingUri' => [ 'shape' => 'LandingUri', ], 'StudioWebPortal' => [ 'shape' => 'StudioWebPortal', ], 'CustomPosixUserConfig' => [ 'shape' => 'CustomPosixUserConfig', ], 'CustomFileSystemConfigs' => [ 'shape' => 'CustomFileSystemConfigs', ], ], ], 'UsersPerStep' => [ 'type' => 'integer', 'max' => 3, 'min' => 1, ], 'UtilizationMetric' => [ 'type' => 'float', 'min' => 0.0, ], 'UtilizationPercentagePerCore' => [ 'type' => 'integer', 'max' => 100, 'min' => 1, ], 'ValidationFraction' => [ 'type' => 'float', 'max' => 1, 'min' => 0, ], 'VariantName' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'VariantProperty' => [ 'type' => 'structure', 'required' => [ 'VariantPropertyType', ], 'members' => [ 'VariantPropertyType' => [ 'shape' => 'VariantPropertyType', ], ], ], 'VariantPropertyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VariantProperty', ], 'max' => 3, 'min' => 0, ], 'VariantPropertyType' => [ 'type' => 'string', 'enum' => [ 'DesiredInstanceCount', 'DesiredWeight', 'DataCaptureConfig', ], ], 'VariantStatus' => [ 'type' => 'string', 'enum' => [ 'Creating', 'Updating', 'Deleting', 'ActivatingTraffic', 'Baking', ], ], 'VariantStatusMessage' => [ 'type' => 'string', 'max' => 1024, ], 'VariantWeight' => [ 'type' => 'float', 'min' => 0, ], 'VectorConfig' => [ 'type' => 'structure', 'required' => [ 'Dimension', ], 'members' => [ 'Dimension' => [ 'shape' => 'Dimension', ], ], ], 'VendorGuidance' => [ 'type' => 'string', 'enum' => [ 'NOT_PROVIDED', 'STABLE', 'TO_BE_ARCHIVED', 'ARCHIVED', ], ], 'VersionId' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '.+', ], 'VersionedArnOrName' => [ 'type' => 'string', 'max' => 176, 'min' => 1, 'pattern' => '(arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:[a-z\\-]*\\/)?([a-zA-Z0-9]([a-zA-Z0-9-]){0,62})(? [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'AssociationEntityArn', ], 'Type' => [ 'shape' => 'String40', ], 'LineageType' => [ 'shape' => 'LineageType', ], ], ], 'Vertices' => [ 'type' => 'list', 'member' => [ 'shape' => 'Vertex', ], ], 'VisibilityConditions' => [ 'type' => 'structure', 'members' => [ 'Key' => [ 'shape' => 'VisibilityConditionsKey', ], 'Value' => [ 'shape' => 'VisibilityConditionsValue', ], ], ], 'VisibilityConditionsKey' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:/=+\\-@]*)$', ], 'VisibilityConditionsList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VisibilityConditions', ], 'max' => 5, 'min' => 1, ], 'VisibilityConditionsValue' => [ 'type' => 'string', 'max' => 256, 'min' => 0, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:/=+\\-@]*)$', ], 'VolumeSizeInGB' => [ 'type' => 'integer', 'min' => 1, ], 'VpcConfig' => [ 'type' => 'structure', 'required' => [ 'SecurityGroupIds', 'Subnets', ], 'members' => [ 'SecurityGroupIds' => [ 'shape' => 'VpcSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'Subnets', ], ], ], 'VpcId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '[-0-9a-zA-Z]+', ], 'VpcOnlyTrustedAccounts' => [ 'type' => 'list', 'member' => [ 'shape' => 'AccountId', ], 'max' => 10, ], 'VpcSecurityGroupIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityGroupId', ], 'max' => 5, 'min' => 1, ], 'WaitIntervalInSeconds' => [ 'type' => 'integer', 'max' => 3600, 'min' => 0, ], 'WarmPoolResourceStatus' => [ 'type' => 'string', 'enum' => [ 'Available', 'Terminated', 'Reused', 'InUse', ], ], 'WarmPoolStatus' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'WarmPoolResourceStatus', ], 'ResourceRetainedBillableTimeInSeconds' => [ 'shape' => 'ResourceRetainedBillableTimeInSeconds', ], 'ReusedByJob' => [ 'shape' => 'TrainingJobName', ], ], ], 'Workforce' => [ 'type' => 'structure', 'required' => [ 'WorkforceName', 'WorkforceArn', ], 'members' => [ 'WorkforceName' => [ 'shape' => 'WorkforceName', ], 'WorkforceArn' => [ 'shape' => 'WorkforceArn', ], 'LastUpdatedDate' => [ 'shape' => 'Timestamp', ], 'SourceIpConfig' => [ 'shape' => 'SourceIpConfig', ], 'SubDomain' => [ 'shape' => 'String', ], 'CognitoConfig' => [ 'shape' => 'CognitoConfig', ], 'OidcConfig' => [ 'shape' => 'OidcConfigForResponse', ], 'CreateDate' => [ 'shape' => 'Timestamp', ], 'WorkforceVpcConfig' => [ 'shape' => 'WorkforceVpcConfigResponse', ], 'Status' => [ 'shape' => 'WorkforceStatus', ], 'FailureReason' => [ 'shape' => 'WorkforceFailureReason', ], ], ], 'WorkforceArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:workforce/.*', ], 'WorkforceFailureReason' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '.+', ], 'WorkforceName' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '^[a-zA-Z0-9]([a-zA-Z0-9\\-]){0,62}$', ], 'WorkforceSecurityGroupId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^sg-[0-9a-z]*$', ], 'WorkforceSecurityGroupIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'WorkforceSecurityGroupId', ], 'max' => 5, 'min' => 1, ], 'WorkforceStatus' => [ 'type' => 'string', 'enum' => [ 'Initializing', 'Updating', 'Deleting', 'Failed', 'Active', ], ], 'WorkforceSubnetId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^subnet-[0-9a-z]*$', ], 'WorkforceSubnets' => [ 'type' => 'list', 'member' => [ 'shape' => 'WorkforceSubnetId', ], 'max' => 16, 'min' => 1, ], 'WorkforceVpcConfigRequest' => [ 'type' => 'structure', 'members' => [ 'VpcId' => [ 'shape' => 'WorkforceVpcId', ], 'SecurityGroupIds' => [ 'shape' => 'WorkforceSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'WorkforceSubnets', ], ], ], 'WorkforceVpcConfigResponse' => [ 'type' => 'structure', 'required' => [ 'VpcId', 'SecurityGroupIds', 'Subnets', ], 'members' => [ 'VpcId' => [ 'shape' => 'WorkforceVpcId', ], 'SecurityGroupIds' => [ 'shape' => 'WorkforceSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'WorkforceSubnets', ], 'VpcEndpointId' => [ 'shape' => 'WorkforceVpcEndpointId', ], ], ], 'WorkforceVpcEndpointId' => [ 'type' => 'string', 'max' => 255, 'min' => 1, 'pattern' => '^vpce-[0-9a-z]*$', ], 'WorkforceVpcId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^vpc-[0-9a-z]*$', ], 'Workforces' => [ 'type' => 'list', 'member' => [ 'shape' => 'Workforce', ], ], 'WorkspaceSettings' => [ 'type' => 'structure', 'members' => [ 'S3ArtifactPath' => [ 'shape' => 'S3Uri', ], 'S3KmsKeyId' => [ 'shape' => 'KmsKeyId', ], ], ], 'Workteam' => [ 'type' => 'structure', 'required' => [ 'WorkteamName', 'MemberDefinitions', 'WorkteamArn', 'Description', ], 'members' => [ 'WorkteamName' => [ 'shape' => 'WorkteamName', ], 'MemberDefinitions' => [ 'shape' => 'MemberDefinitions', ], 'WorkteamArn' => [ 'shape' => 'WorkteamArn', ], 'WorkforceArn' => [ 'shape' => 'WorkforceArn', ], 'ProductListingIds' => [ 'shape' => 'ProductListings', ], 'Description' => [ 'shape' => 'String200', ], 'SubDomain' => [ 'shape' => 'String', ], 'CreateDate' => [ 'shape' => 'Timestamp', ], 'LastUpdatedDate' => [ 'shape' => 'Timestamp', ], 'NotificationConfiguration' => [ 'shape' => 'NotificationConfiguration', ], ], ], 'WorkteamArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:workteam/.*', ], 'WorkteamName' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'Workteams' => [ 'type' => 'list', 'member' => [ 'shape' => 'Workteam', ], ], ],]; +return [ 'version' => '2.0', 'metadata' => [ 'apiVersion' => '2017-07-24', 'endpointPrefix' => 'api.sagemaker', 'jsonVersion' => '1.1', 'protocol' => 'json', 'serviceAbbreviation' => 'SageMaker', 'serviceFullName' => 'Amazon SageMaker Service', 'serviceId' => 'SageMaker', 'signatureVersion' => 'v4', 'signingName' => 'sagemaker', 'targetPrefix' => 'SageMaker', 'uid' => 'sagemaker-2017-07-24', ], 'operations' => [ 'AddAssociation' => [ 'name' => 'AddAssociation', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AddAssociationRequest', ], 'output' => [ 'shape' => 'AddAssociationResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'AddTags' => [ 'name' => 'AddTags', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AddTagsInput', ], 'output' => [ 'shape' => 'AddTagsOutput', ], ], 'AssociateTrialComponent' => [ 'name' => 'AssociateTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AssociateTrialComponentRequest', ], 'output' => [ 'shape' => 'AssociateTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'BatchDescribeModelPackage' => [ 'name' => 'BatchDescribeModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'BatchDescribeModelPackageInput', ], 'output' => [ 'shape' => 'BatchDescribeModelPackageOutput', ], ], 'CreateAction' => [ 'name' => 'CreateAction', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateActionRequest', ], 'output' => [ 'shape' => 'CreateActionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAlgorithm' => [ 'name' => 'CreateAlgorithm', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAlgorithmInput', ], 'output' => [ 'shape' => 'CreateAlgorithmOutput', ], ], 'CreateApp' => [ 'name' => 'CreateApp', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAppRequest', ], 'output' => [ 'shape' => 'CreateAppResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateAppImageConfig' => [ 'name' => 'CreateAppImageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAppImageConfigRequest', ], 'output' => [ 'shape' => 'CreateAppImageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'CreateArtifact' => [ 'name' => 'CreateArtifact', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateArtifactRequest', ], 'output' => [ 'shape' => 'CreateArtifactResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAutoMLJob' => [ 'name' => 'CreateAutoMLJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAutoMLJobRequest', ], 'output' => [ 'shape' => 'CreateAutoMLJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAutoMLJobV2' => [ 'name' => 'CreateAutoMLJobV2', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAutoMLJobV2Request', ], 'output' => [ 'shape' => 'CreateAutoMLJobV2Response', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateCluster' => [ 'name' => 'CreateCluster', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateClusterRequest', ], 'output' => [ 'shape' => 'CreateClusterResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateCodeRepository' => [ 'name' => 'CreateCodeRepository', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateCodeRepositoryInput', ], 'output' => [ 'shape' => 'CreateCodeRepositoryOutput', ], ], 'CreateCompilationJob' => [ 'name' => 'CreateCompilationJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateCompilationJobRequest', ], 'output' => [ 'shape' => 'CreateCompilationJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateContext' => [ 'name' => 'CreateContext', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateContextRequest', ], 'output' => [ 'shape' => 'CreateContextResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateDataQualityJobDefinition' => [ 'name' => 'CreateDataQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDataQualityJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateDataQualityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateDeviceFleet' => [ 'name' => 'CreateDeviceFleet', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDeviceFleetRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateDomain' => [ 'name' => 'CreateDomain', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDomainRequest', ], 'output' => [ 'shape' => 'CreateDomainResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateEdgeDeploymentPlan' => [ 'name' => 'CreateEdgeDeploymentPlan', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgeDeploymentPlanRequest', ], 'output' => [ 'shape' => 'CreateEdgeDeploymentPlanResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEdgeDeploymentStage' => [ 'name' => 'CreateEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgeDeploymentStageRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEdgePackagingJob' => [ 'name' => 'CreateEdgePackagingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgePackagingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEndpoint' => [ 'name' => 'CreateEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEndpointInput', ], 'output' => [ 'shape' => 'CreateEndpointOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEndpointConfig' => [ 'name' => 'CreateEndpointConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEndpointConfigInput', ], 'output' => [ 'shape' => 'CreateEndpointConfigOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateExperiment' => [ 'name' => 'CreateExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateExperimentRequest', ], 'output' => [ 'shape' => 'CreateExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateFeatureGroup' => [ 'name' => 'CreateFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateFeatureGroupRequest', ], 'output' => [ 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'ListDataQualityJobDefinitionsResponse', ], ], 'ListDeviceFleets' => [ 'name' => 'ListDeviceFleets', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListDeviceFleetsRequest', ], 'output' => [ 'shape' => 'ListDeviceFleetsResponse', ], ], 'ListDevices' => [ 'name' => 'ListDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListDevicesRequest', ], 'output' => [ 'shape' => 'ListDevicesResponse', ], ], 'ListDomains' => [ 'name' => 'ListDomains', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListDomainsRequest', ], 'output' => [ 'shape' => 'ListDomainsResponse', ], ], 'ListEdgeDeploymentPlans' => [ 'name' => 'ListEdgeDeploymentPlans', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListEdgeDeploymentPlansRequest', ], 'output' => [ 'shape' => 'ListEdgeDeploymentPlansResponse', ], ], 'ListEdgePackagingJobs' => [ 'name' => 'ListEdgePackagingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListEdgePackagingJobsRequest', ], 'output' => [ 'shape' => 'ListEdgePackagingJobsResponse', ], ], 'ListEndpointConfigs' => [ 'name' => 'ListEndpointConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListEndpointConfigsInput', ], 'output' => [ 'shape' => 'ListEndpointConfigsOutput', ], ], 'ListEndpoints' => [ 'name' => 'ListEndpoints', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListEndpointsInput', ], 'output' => [ 'shape' => 'ListEndpointsOutput', ], ], 'ListExperiments' => [ 'name' => 'ListExperiments', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListExperimentsRequest', ], 'output' => [ 'shape' => 'ListExperimentsResponse', ], ], 'ListFeatureGroups' => [ 'name' => 'ListFeatureGroups', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListFeatureGroupsRequest', ], 'output' => [ 'shape' => 'ListFeatureGroupsResponse', ], ], 'ListFlowDefinitions' => [ 'name' => 'ListFlowDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListFlowDefinitionsRequest', ], 'output' => [ 'shape' => 'ListFlowDefinitionsResponse', ], ], 'ListHubContentVersions' => [ 'name' => 'ListHubContentVersions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHubContentVersionsRequest', ], 'output' => [ 'shape' => 'ListHubContentVersionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListHubContents' => [ 'name' => 'ListHubContents', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHubContentsRequest', ], 'output' => [ 'shape' => 'ListHubContentsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListHubs' => [ 'name' => 'ListHubs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHubsRequest', ], 'output' => [ 'shape' => 'ListHubsResponse', ], ], 'ListHumanTaskUis' => [ 'name' => 'ListHumanTaskUis', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHumanTaskUisRequest', ], 'output' => [ 'shape' => 'ListHumanTaskUisResponse', ], ], 'ListHyperParameterTuningJobs' => [ 'name' => 'ListHyperParameterTuningJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHyperParameterTuningJobsRequest', ], 'output' => [ 'shape' => 'ListHyperParameterTuningJobsResponse', ], ], 'ListImageVersions' => [ 'name' => 'ListImageVersions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListImageVersionsRequest', ], 'output' => [ 'shape' => 'ListImageVersionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListImages' => [ 'name' => 'ListImages', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListImagesRequest', ], 'output' => [ 'shape' => 'ListImagesResponse', ], ], 'ListInferenceComponents' => [ 'name' => 'ListInferenceComponents', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceComponentsInput', ], 'output' => [ 'shape' => 'ListInferenceComponentsOutput', ], ], 'ListInferenceExperiments' => [ 'name' => 'ListInferenceExperiments', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceExperimentsRequest', ], 'output' => [ 'shape' => 'ListInferenceExperimentsResponse', ], ], 'ListInferenceRecommendationsJobSteps' => [ 'name' => 'ListInferenceRecommendationsJobSteps', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceRecommendationsJobStepsRequest', ], 'output' => [ 'shape' => 'ListInferenceRecommendationsJobStepsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListInferenceRecommendationsJobs' => [ 'name' => 'ListInferenceRecommendationsJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceRecommendationsJobsRequest', ], 'output' => [ 'shape' => 'ListInferenceRecommendationsJobsResponse', ], ], 'ListLabelingJobs' => [ 'name' => 'ListLabelingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListLabelingJobsRequest', ], 'output' => [ 'shape' => 'ListLabelingJobsResponse', ], ], 'ListLabelingJobsForWorkteam' => [ 'name' => 'ListLabelingJobsForWorkteam', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListLabelingJobsForWorkteamRequest', ], 'output' => [ 'shape' => 'ListLabelingJobsForWorkteamResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListLineageGroups' => [ 'name' => 'ListLineageGroups', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListLineageGroupsRequest', ], 'output' => [ 'shape' => 'ListLineageGroupsResponse', ], ], 'ListModelBiasJobDefinitions' => [ 'name' => 'ListModelBiasJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelBiasJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelBiasJobDefinitionsResponse', ], ], 'ListModelCardExportJobs' => [ 'name' => 'ListModelCardExportJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardExportJobsRequest', ], 'output' => [ 'shape' => 'ListModelCardExportJobsResponse', ], ], 'ListModelCardVersions' => [ 'name' => 'ListModelCardVersions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardVersionsRequest', ], 'output' => [ 'shape' => 'ListModelCardVersionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListModelCards' => [ 'name' => 'ListModelCards', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardsRequest', ], 'output' => [ 'shape' => 'ListModelCardsResponse', ], ], 'ListModelExplainabilityJobDefinitions' => [ 'name' => 'ListModelExplainabilityJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelExplainabilityJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelExplainabilityJobDefinitionsResponse', ], ], 'ListModelMetadata' => [ 'name' => 'ListModelMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelMetadataRequest', ], 'output' => [ 'shape' => 'ListModelMetadataResponse', ], ], 'ListModelPackageGroups' => [ 'name' => 'ListModelPackageGroups', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelPackageGroupsInput', ], 'output' => [ 'shape' => 'ListModelPackageGroupsOutput', ], ], 'ListModelPackages' => [ 'name' => 'ListModelPackages', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelPackagesInput', ], 'output' => [ 'shape' => 'ListModelPackagesOutput', ], ], 'ListModelQualityJobDefinitions' => [ 'name' => 'ListModelQualityJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelQualityJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelQualityJobDefinitionsResponse', ], ], 'ListModels' => [ 'name' => 'ListModels', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelsInput', ], 'output' => [ 'shape' => 'ListModelsOutput', ], ], 'ListMonitoringAlertHistory' => [ 'name' => 'ListMonitoringAlertHistory', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListMonitoringAlertHistoryRequest', ], 'output' => [ 'shape' => 'ListMonitoringAlertHistoryResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListMonitoringAlerts' => [ 'name' => 'ListMonitoringAlerts', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListMonitoringAlertsRequest', ], 'output' => [ 'shape' => 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'requestUri' => '/', ], 'input' => [ 'shape' => 'ListNotebookInstancesInput', ], 'output' => [ 'shape' => 'ListNotebookInstancesOutput', ], ], 'ListPipelineExecutionSteps' => [ 'name' => 'ListPipelineExecutionSteps', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineExecutionStepsRequest', ], 'output' => [ 'shape' => 'ListPipelineExecutionStepsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelineExecutions' => [ 'name' => 'ListPipelineExecutions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineExecutionsRequest', ], 'output' => [ 'shape' => 'ListPipelineExecutionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelineParametersForExecution' => [ 'name' => 'ListPipelineParametersForExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineParametersForExecutionRequest', ], 'output' => [ 'shape' => 'ListPipelineParametersForExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelines' => [ 'name' => 'ListPipelines', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelinesRequest', ], 'output' => [ 'shape' => 'ListPipelinesResponse', ], ], 'ListProcessingJobs' => [ 'name' => 'ListProcessingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListProcessingJobsRequest', ], 'output' => [ 'shape' => 'ListProcessingJobsResponse', ], ], 'ListProjects' => [ 'name' => 'ListProjects', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListProjectsInput', ], 'output' => [ 'shape' => 'ListProjectsOutput', ], ], 'ListResourceCatalogs' => [ 'name' => 'ListResourceCatalogs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListResourceCatalogsRequest', ], 'output' => [ 'shape' => 'ListResourceCatalogsResponse', ], ], 'ListSpaces' => [ 'name' => 'ListSpaces', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListSpacesRequest', ], 'output' => [ 'shape' => 'ListSpacesResponse', ], ], 'ListStageDevices' => [ 'name' => 'ListStageDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListStageDevicesRequest', ], 'output' => [ 'shape' => 'ListStageDevicesResponse', ], ], 'ListStudioLifecycleConfigs' => [ 'name' => 'ListStudioLifecycleConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListStudioLifecycleConfigsRequest', ], 'output' => [ 'shape' => 'ListStudioLifecycleConfigsResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'ListSubscribedWorkteams' => [ 'name' => 'ListSubscribedWorkteams', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListSubscribedWorkteamsRequest', ], 'output' => [ 'shape' => 'ListSubscribedWorkteamsResponse', ], ], 'ListTags' => [ 'name' => 'ListTags', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTagsInput', ], 'output' => [ 'shape' => 'ListTagsOutput', ], ], 'ListTrainingJobs' => [ 'name' => 'ListTrainingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrainingJobsRequest', ], 'output' => [ 'shape' => 'ListTrainingJobsResponse', ], ], 'ListTrainingJobsForHyperParameterTuningJob' => [ 'name' => 'ListTrainingJobsForHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrainingJobsForHyperParameterTuningJobRequest', ], 'output' => [ 'shape' => 'ListTrainingJobsForHyperParameterTuningJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListTransformJobs' => [ 'name' => 'ListTransformJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTransformJobsRequest', ], 'output' => [ 'shape' => 'ListTransformJobsResponse', ], ], 'ListTrialComponents' => [ 'name' => 'ListTrialComponents', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrialComponentsRequest', ], 'output' => [ 'shape' => 'ListTrialComponentsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListTrials' => [ 'name' => 'ListTrials', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrialsRequest', ], 'output' => [ 'shape' => 'ListTrialsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListUserProfiles' => [ 'name' => 'ListUserProfiles', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListUserProfilesRequest', ], 'output' => [ 'shape' => 'ListUserProfilesResponse', ], ], 'ListWorkforces' => [ 'name' => 'ListWorkforces', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListWorkforcesRequest', ], 'output' => [ 'shape' => 'ListWorkforcesResponse', ], ], 'ListWorkteams' => [ 'name' => 'ListWorkteams', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListWorkteamsRequest', ], 'output' => [ 'shape' => 'ListWorkteamsResponse', ], ], 'PutModelPackageGroupPolicy' => [ 'name' => 'PutModelPackageGroupPolicy', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'PutModelPackageGroupPolicyInput', ], 'output' => [ 'shape' => 'PutModelPackageGroupPolicyOutput', ], 'errors' => [ [ 'shape' => 'ConflictException', ], ], ], 'QueryLineage' => [ 'name' => 'QueryLineage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'QueryLineageRequest', ], 'output' => [ 'shape' => 'QueryLineageResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'RegisterDevices' => [ 'name' => 'RegisterDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RegisterDevicesRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'RenderUiTemplate' => [ 'name' => 'RenderUiTemplate', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RenderUiTemplateRequest', ], 'output' => [ 'shape' => 'RenderUiTemplateResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'RetryPipelineExecution' => [ 'name' => 'RetryPipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RetryPipelineExecutionRequest', ], 'output' => [ 'shape' => 'RetryPipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'Search' => [ 'name' => 'Search', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SearchRequest', ], 'output' => [ 'shape' => 'SearchResponse', ], ], 'SendPipelineExecutionStepFailure' => [ 'name' => 'SendPipelineExecutionStepFailure', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SendPipelineExecutionStepFailureRequest', ], 'output' => [ 'shape' => 'SendPipelineExecutionStepFailureResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'SendPipelineExecutionStepSuccess' => [ 'name' => 'SendPipelineExecutionStepSuccess', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SendPipelineExecutionStepSuccessRequest', ], 'output' => [ 'shape' => 'SendPipelineExecutionStepSuccessResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'StartEdgeDeploymentStage' => [ 'name' => 'StartEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartEdgeDeploymentStageRequest', ], ], 'StartInferenceExperiment' => [ 'name' => 'StartInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartInferenceExperimentRequest', ], 'output' => [ 'shape' => 'StartInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'StartMonitoringSchedule' => [ 'name' => 'StartMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartMonitoringScheduleRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StartNotebookInstance' => [ 'name' => 'StartNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartNotebookInstanceInput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'StartPipelineExecution' => [ 'name' => 'StartPipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartPipelineExecutionRequest', ], 'output' => [ 'shape' => 'StartPipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 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'/', ], 'input' => [ 'shape' => 'StopHyperParameterTuningJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopInferenceExperiment' => [ 'name' => 'StopInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopInferenceExperimentRequest', ], 'output' => [ 'shape' => 'StopInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'StopInferenceRecommendationsJob' => [ 'name' => 'StopInferenceRecommendationsJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopInferenceRecommendationsJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopLabelingJob' => [ 'name' => 'StopLabelingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopLabelingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopMonitoringSchedule' => [ 'name' => 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100, 'min' => 1, ], 'ContainerConfig' => [ 'type' => 'structure', 'members' => [ 'ContainerArguments' => [ 'shape' => 'CustomImageContainerArguments', ], 'ContainerEntrypoint' => [ 'shape' => 'CustomImageContainerEntrypoint', ], 'ContainerEnvironmentVariables' => [ 'shape' => 'CustomImageContainerEnvironmentVariables', ], ], ], 'ContainerDefinition' => [ 'type' => 'structure', 'members' => [ 'ContainerHostname' => [ 'shape' => 'ContainerHostname', ], 'Image' => [ 'shape' => 'ContainerImage', ], 'ImageConfig' => [ 'shape' => 'ImageConfig', ], 'Mode' => [ 'shape' => 'ContainerMode', ], 'ModelDataUrl' => [ 'shape' => 'Url', ], 'ModelDataSource' => [ 'shape' => 'ModelDataSource', ], 'Environment' => [ 'shape' => 'EnvironmentMap', ], 'ModelPackageName' => [ 'shape' => 'VersionedArnOrName', ], 'InferenceSpecificationName' => [ 'shape' => 'InferenceSpecificationName', ], 'MultiModelConfig' => [ 'shape' => 'MultiModelConfig', ], ], ], 'ContainerDefinitionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContainerDefinition', ], 'max' => 15, ], 'ContainerEntrypoint' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContainerEntrypointString', ], 'max' => 100, 'min' => 1, ], 'ContainerEntrypointString' => [ 'type' => 'string', 'max' => 256, 'pattern' => '.*', ], 'ContainerHostname' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'ContainerImage' => [ 'type' => 'string', 'max' => 255, 'pattern' => '[\\S]+', ], 'ContainerMode' => [ 'type' => 'string', 'enum' => [ 'SingleModel', 'MultiModel', ], ], 'ContentClassifier' => [ 'type' => 'string', 'enum' => [ 'FreeOfPersonallyIdentifiableInformation', 'FreeOfAdultContent', ], ], 'ContentClassifiers' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContentClassifier', ], 'max' => 256, ], 'ContentColumn' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'ContentDigest' => [ 'type' => 'string', 'max' => 72, 'pattern' => '^[Ss][Hh][Aa]256:[0-9a-fA-F]{64}$', ], 'ContentType' => [ 'type' 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], 'ContextName' => [ 'shape' => 'ContextName', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'ContinuousParameterRange' => [ 'type' => 'structure', 'required' => [ 'Name', 'MinValue', 'MaxValue', ], 'members' => [ 'Name' => [ 'shape' => 'ParameterKey', ], 'MinValue' => [ 'shape' => 'ParameterValue', ], 'MaxValue' => [ 'shape' => 'ParameterValue', ], 'ScalingType' => [ 'shape' => 'HyperParameterScalingType', ], ], ], 'ContinuousParameterRangeSpecification' => [ 'type' => 'structure', 'required' => [ 'MinValue', 'MaxValue', ], 'members' => [ 'MinValue' => [ 'shape' => 'ParameterValue', ], 'MaxValue' => [ 'shape' => 'ParameterValue', ], ], ], 'ContinuousParameterRanges' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContinuousParameterRange', ], 'max' => 30, 'min' => 0, ], 'ConvergenceDetected' => [ 'type' => 'structure', 'members' => [ 'CompleteOnConvergence' => [ 'shape' => 'CompleteOnConvergence', ], ], ], 'CountryCode' => [ 'type' => 'string', 'max' => 2, 'min' => 2, 'pattern' => '[A-Z]{2}', ], 'CreateActionRequest' => [ 'type' => 'structure', 'required' => [ 'ActionName', 'Source', 'ActionType', ], 'members' => [ 'ActionName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ActionSource', ], 'ActionType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Status' => [ 'shape' => 'ActionStatus', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateActionResponse' => [ 'type' => 'structure', 'members' => [ 'ActionArn' => [ 'shape' => 'ActionArn', ], ], ], 'CreateAlgorithmInput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmName', 'TrainingSpecification', ], 'members' => [ 'AlgorithmName' => [ 'shape' => 'EntityName', ], 'AlgorithmDescription' => [ 'shape' => 'EntityDescription', ], 'TrainingSpecification' => [ 'shape' => 'TrainingSpecification', ], 'InferenceSpecification' => [ 'shape' => 'InferenceSpecification', ], 'ValidationSpecification' => [ 'shape' => 'AlgorithmValidationSpecification', ], 'CertifyForMarketplace' => [ 'shape' => 'CertifyForMarketplace', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateAlgorithmOutput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmArn', ], 'members' => [ 'AlgorithmArn' => [ 'shape' => 'AlgorithmArn', ], ], ], 'CreateAppImageConfigRequest' => [ 'type' => 'structure', 'required' => [ 'AppImageConfigName', ], 'members' => [ 'AppImageConfigName' => [ 'shape' => 'AppImageConfigName', ], 'Tags' => [ 'shape' => 'TagList', ], 'KernelGatewayImageConfig' => [ 'shape' => 'KernelGatewayImageConfig', ], 'JupyterLabAppImageConfig' => [ 'shape' => 'JupyterLabAppImageConfig', ], ], ], 'CreateAppImageConfigResponse' => [ 'type' => 'structure', 'members' => [ 'AppImageConfigArn' => [ 'shape' => 'AppImageConfigArn', ], ], ], 'CreateAppRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'AppType', 'AppName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], 'AppType' => [ 'shape' => 'AppType', ], 'AppName' => [ 'shape' => 'AppName', ], 'Tags' => [ 'shape' => 'TagList', ], 'ResourceSpec' => [ 'shape' => 'ResourceSpec', ], ], ], 'CreateAppResponse' => [ 'type' => 'structure', 'members' => [ 'AppArn' => [ 'shape' => 'AppArn', ], ], ], 'CreateArtifactRequest' => [ 'type' => 'structure', 'required' => [ 'Source', 'ArtifactType', ], 'members' => [ 'ArtifactName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ArtifactSource', ], 'ArtifactType' => [ 'shape' => 'String256', ], 'Properties' => [ 'shape' => 'ArtifactProperties', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateArtifactResponse' => [ 'type' => 'structure', 'members' => [ 'ArtifactArn' => [ 'shape' => 'ArtifactArn', ], ], ], 'CreateAutoMLJobRequest' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'InputDataConfig', 'OutputDataConfig', 'RoleArn', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'InputDataConfig' => [ 'shape' => 'AutoMLInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'ProblemType' => [ 'shape' => 'ProblemType', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'AutoMLJobConfig' => [ 'shape' => 'AutoMLJobConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'GenerateCandidateDefinitionsOnly' => [ 'shape' => 'GenerateCandidateDefinitionsOnly', ], 'Tags' => [ 'shape' => 'TagList', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], ], ], 'CreateAutoMLJobResponse' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobArn', ], 'members' => [ 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], ], ], 'CreateAutoMLJobV2Request' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobInputDataConfig', 'OutputDataConfig', 'AutoMLProblemTypeConfig', 'RoleArn', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobInputDataConfig' => [ 'shape' => 'AutoMLJobInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'AutoMLProblemTypeConfig' => [ 'shape' => 'AutoMLProblemTypeConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], 'SecurityConfig' => [ 'shape' => 'AutoMLSecurityConfig', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'DataSplitConfig' => [ 'shape' => 'AutoMLDataSplitConfig', ], ], ], 'CreateAutoMLJobV2Response' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobArn', ], 'members' => [ 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], ], ], 'CreateClusterRequest' => [ 'type' => 'structure', 'required' => [ 'ClusterName', 'InstanceGroups', ], 'members' => [ 'ClusterName' => [ 'shape' => 'ClusterName', ], 'InstanceGroups' => [ 'shape' => 'ClusterInstanceGroupSpecifications', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateClusterResponse' => [ 'type' => 'structure', 'required' => [ 'ClusterArn', ], 'members' => [ 'ClusterArn' => [ 'shape' => 'ClusterArn', ], ], ], 'CreateCodeRepositoryInput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', 'GitConfig', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], 'GitConfig' => [ 'shape' => 'GitConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateCodeRepositoryOutput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryArn', ], 'members' => [ 'CodeRepositoryArn' => [ 'shape' => 'CodeRepositoryArn', ], ], ], 'CreateCompilationJobRequest' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', 'RoleArn', 'OutputConfig', 'StoppingCondition', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'ModelPackageVersionArn' => [ 'shape' => 'ModelPackageArn', ], 'InputConfig' => [ 'shape' => 'InputConfig', ], 'OutputConfig' => [ 'shape' => 'OutputConfig', ], 'VpcConfig' => [ 'shape' => 'NeoVpcConfig', ], 'StoppingCondition' => [ 'shape' => 'StoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateCompilationJobResponse' => [ 'type' => 'structure', 'required' => [ 'CompilationJobArn', ], 'members' => [ 'CompilationJobArn' => [ 'shape' => 'CompilationJobArn', ], ], ], 'CreateContextRequest' => [ 'type' => 'structure', 'required' => [ 'ContextName', 'Source', 'ContextType', ], 'members' => [ 'ContextName' => [ 'shape' => 'ContextName', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateContextResponse' => [ 'type' => 'structure', 'members' => [ 'ContextArn' => [ 'shape' => 'ContextArn', ], ], ], 'CreateDataQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'DataQualityAppSpecification', 'DataQualityJobInput', 'DataQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'DataQualityBaselineConfig' => [ 'shape' => 'DataQualityBaselineConfig', ], 'DataQualityAppSpecification' => [ 'shape' => 'DataQualityAppSpecification', ], 'DataQualityJobInput' => [ 'shape' => 'DataQualityJobInput', ], 'DataQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateDataQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateDeviceFleetRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'OutputConfig', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Description' => [ 'shape' => 'DeviceFleetDescription', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'EnableIotRoleAlias' => [ 'shape' => 'EnableIotRoleAlias', ], ], ], 'CreateDomainRequest' => [ 'type' => 'structure', 'required' => [ 'DomainName', 'AuthMode', 'DefaultUserSettings', 'SubnetIds', 'VpcId', ], 'members' => [ 'DomainName' => [ 'shape' => 'DomainName', ], 'AuthMode' => [ 'shape' => 'AuthMode', ], 'DefaultUserSettings' => [ 'shape' => 'UserSettings', ], 'DomainSettings' => [ 'shape' => 'DomainSettings', ], 'SubnetIds' => [ 'shape' => 'Subnets', ], 'VpcId' => [ 'shape' => 'VpcId', ], 'Tags' => [ 'shape' => 'TagList', ], 'AppNetworkAccessType' => [ 'shape' => 'AppNetworkAccessType', ], 'HomeEfsFileSystemKmsKeyId' => [ 'shape' => 'KmsKeyId', 'deprecated' => true, 'deprecatedMessage' => 'This property is deprecated, use KmsKeyId instead.', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AppSecurityGroupManagement' => [ 'shape' => 'AppSecurityGroupManagement', ], 'DefaultSpaceSettings' => [ 'shape' => 'DefaultSpaceSettings', ], ], ], 'CreateDomainResponse' => [ 'type' => 'structure', 'members' => [ 'DomainArn' => [ 'shape' => 'DomainArn', ], 'Url' => [ 'shape' => 'String1024', ], ], ], 'CreateEdgeDeploymentPlanRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', 'ModelConfigs', 'DeviceFleetName', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'ModelConfigs' => [ 'shape' => 'EdgeDeploymentModelConfigs', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'Stages' => [ 'shape' => 'DeploymentStages', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEdgeDeploymentPlanResponse' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanArn', ], 'members' => [ 'EdgeDeploymentPlanArn' => [ 'shape' => 'EdgeDeploymentPlanArn', ], ], ], 'CreateEdgeDeploymentStageRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', 'Stages', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'Stages' => [ 'shape' => 'DeploymentStages', ], ], ], 'CreateEdgePackagingJobRequest' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobName', 'CompilationJobName', 'ModelName', 'ModelVersion', 'RoleArn', 'OutputConfig', ], 'members' => [ 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'ModelName' => [ 'shape' => 'EntityName', ], 'ModelVersion' => [ 'shape' => 'EdgeVersion', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'ResourceKey' => [ 'shape' => 'KmsKeyId', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEndpointConfigInput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', 'ProductionVariants', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'ExecutionRoleArn' => [ 'shape' => 'RoleArn', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'EnableNetworkIsolation' => [ 'shape' => 'Boolean', ], ], ], 'CreateEndpointConfigOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigArn', ], 'members' => [ 'EndpointConfigArn' => [ 'shape' => 'EndpointConfigArn', ], ], ], 'CreateEndpointInput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', 'EndpointConfigName', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'DeploymentConfig' => [ 'shape' => 'DeploymentConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEndpointOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointArn', ], 'members' => [ 'EndpointArn' => [ 'shape' => 'EndpointArn', ], ], ], 'CreateExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'ExperimentName', ], 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateExperimentResponse' => [ 'type' => 'structure', 'members' => [ 'ExperimentArn' => [ 'shape' => 'ExperimentArn', ], ], ], 'CreateFeatureGroupRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', 'RecordIdentifierFeatureName', 'EventTimeFeatureName', 'FeatureDefinitions', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'RecordIdentifierFeatureName' => [ 'shape' => 'FeatureName', ], 'EventTimeFeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureDefinitions' => [ 'shape' => 'FeatureDefinitions', ], 'OnlineStoreConfig' => [ 'shape' => 'OnlineStoreConfig', ], 'OfflineStoreConfig' => [ 'shape' => 'OfflineStoreConfig', ], 'ThroughputConfig' => [ 'shape' => 'ThroughputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Description' => [ 'shape' => 'Description', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateFeatureGroupResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], ], ], 'CreateFlowDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionName', 'OutputConfig', 'RoleArn', ], 'members' => [ 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], 'HumanLoopRequestSource' => [ 'shape' => 'HumanLoopRequestSource', ], 'HumanLoopActivationConfig' => [ 'shape' => 'HumanLoopActivationConfig', ], 'HumanLoopConfig' => [ 'shape' => 'HumanLoopConfig', ], 'OutputConfig' => [ 'shape' => 'FlowDefinitionOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateFlowDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionArn', ], 'members' => [ 'FlowDefinitionArn' => [ 'shape' => 'FlowDefinitionArn', ], ], ], 'CreateHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubDescription', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubDescription' => [ 'shape' => 'HubDescription', ], 'HubDisplayName' => [ 'shape' => 'HubDisplayName', ], 'HubSearchKeywords' => [ 'shape' => 'HubSearchKeywordList', ], 'S3StorageConfig' => [ 'shape' => 'HubS3StorageConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateHubResponse' => [ 'type' => 'structure', 'required' => [ 'HubArn', ], 'members' => [ 'HubArn' => [ 'shape' => 'HubArn', ], ], ], 'CreateHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', 'UiTemplate', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], 'UiTemplate' => [ 'shape' => 'UiTemplate', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateHumanTaskUiResponse' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiArn', ], 'members' => [ 'HumanTaskUiArn' => [ 'shape' => 'HumanTaskUiArn', ], ], ], 'CreateHyperParameterTuningJobRequest' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', 'HyperParameterTuningJobConfig', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], 'HyperParameterTuningJobConfig' => [ 'shape' => 'HyperParameterTuningJobConfig', ], 'TrainingJobDefinition' => [ 'shape' => 'HyperParameterTrainingJobDefinition', ], 'TrainingJobDefinitions' => [ 'shape' => 'HyperParameterTrainingJobDefinitions', ], 'WarmStartConfig' => [ 'shape' => 'HyperParameterTuningJobWarmStartConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'Autotune' => [ 'shape' => 'Autotune', ], ], ], 'CreateHyperParameterTuningJobResponse' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobArn', ], 'members' => [ 'HyperParameterTuningJobArn' => [ 'shape' => 'HyperParameterTuningJobArn', ], ], ], 'CreateImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', 'RoleArn', ], 'members' => [ 'Description' => [ 'shape' => 'ImageDescription', ], 'DisplayName' => [ 'shape' => 'ImageDisplayName', ], 'ImageName' => [ 'shape' => 'ImageName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateImageResponse' => [ 'type' => 'structure', 'members' => [ 'ImageArn' => [ 'shape' => 'ImageArn', ], ], ], 'CreateImageVersionRequest' => [ 'type' => 'structure', 'required' => [ 'BaseImage', 'ClientToken', 'ImageName', ], 'members' => [ 'BaseImage' => [ 'shape' => 'ImageBaseImage', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'ImageName' => [ 'shape' => 'ImageName', ], 'Aliases' => [ 'shape' => 'SageMakerImageVersionAliases', ], 'VendorGuidance' => [ 'shape' => 'VendorGuidance', ], 'JobType' => [ 'shape' => 'JobType', ], 'MLFramework' => [ 'shape' => 'MLFramework', ], 'ProgrammingLang' => [ 'shape' => 'ProgrammingLang', ], 'Processor' => [ 'shape' => 'Processor', ], 'Horovod' => [ 'shape' => 'Horovod', ], 'ReleaseNotes' => [ 'shape' => 'ReleaseNotes', ], ], ], 'CreateImageVersionResponse' => [ 'type' => 'structure', 'members' => [ 'ImageVersionArn' => [ 'shape' => 'ImageVersionArn', ], ], ], 'CreateInferenceComponentInput' => [ 'type' => 'structure', 'required' => [ 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], 'ArtifactType' => [ 'shape' => 'String256', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeAutoMLJobRequest' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], ], ], 'DescribeAutoMLJobResponse' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobArn', 'InputDataConfig', 'OutputDataConfig', 'RoleArn', 'CreationTime', 'LastModifiedTime', 'AutoMLJobStatus', 'AutoMLJobSecondaryStatus', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], 'InputDataConfig' => [ 'shape' => 'AutoMLInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'ProblemType' => [ 'shape' => 'ProblemType', ], 'AutoMLJobConfig' => [ 'shape' => 'AutoMLJobConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'AutoMLFailureReason', ], 'PartialFailureReasons' => [ 'shape' => 'AutoMLPartialFailureReasons', ], 'BestCandidate' => [ 'shape' => 'AutoMLCandidate', ], 'AutoMLJobStatus' => [ 'shape' => 'AutoMLJobStatus', ], 'AutoMLJobSecondaryStatus' => [ 'shape' => 'AutoMLJobSecondaryStatus', ], 'GenerateCandidateDefinitionsOnly' => [ 'shape' => 'GenerateCandidateDefinitionsOnly', ], 'AutoMLJobArtifacts' => [ 'shape' => 'AutoMLJobArtifacts', ], 'ResolvedAttributes' => [ 'shape' => 'ResolvedAttributes', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'ModelDeployResult' => [ 'shape' => 'ModelDeployResult', ], ], ], 'DescribeAutoMLJobV2Request' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], ], ], 'DescribeAutoMLJobV2Response' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobArn', 'AutoMLJobInputDataConfig', 'OutputDataConfig', 'RoleArn', 'CreationTime', 'LastModifiedTime', 'AutoMLJobStatus', 'AutoMLJobSecondaryStatus', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], 'AutoMLJobInputDataConfig' => [ 'shape' => 'AutoMLJobInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'AutoMLProblemTypeConfig' => [ 'shape' => 'AutoMLProblemTypeConfig', ], 'AutoMLProblemTypeConfigName' => [ 'shape' => 'AutoMLProblemTypeConfigName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'AutoMLFailureReason', ], 'PartialFailureReasons' => [ 'shape' => 'AutoMLPartialFailureReasons', ], 'BestCandidate' => [ 'shape' => 'AutoMLCandidate', ], 'AutoMLJobStatus' => [ 'shape' => 'AutoMLJobStatus', ], 'AutoMLJobSecondaryStatus' => [ 'shape' => 'AutoMLJobSecondaryStatus', ], 'AutoMLJobArtifacts' => [ 'shape' => 'AutoMLJobArtifacts', ], 'ResolvedAttributes' => [ 'shape' => 'AutoMLResolvedAttributes', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'ModelDeployResult' => [ 'shape' => 'ModelDeployResult', ], 'DataSplitConfig' => [ 'shape' => 'AutoMLDataSplitConfig', ], 'SecurityConfig' => [ 'shape' => 'AutoMLSecurityConfig', ], ], ], 'DescribeClusterNodeRequest' => [ 'type' => 'structure', 'required' => [ 'ClusterName', 'NodeId', ], 'members' => [ 'ClusterName' => [ 'shape' => 'ClusterNameOrArn', ], 'NodeId' => [ 'shape' => 'ClusterNodeId', ], ], ], 'DescribeClusterNodeResponse' => [ 'type' => 'structure', 'required' => [ 'NodeDetails', ], 'members' => [ 'NodeDetails' => [ 'shape' => 'ClusterNodeDetails', ], ], ], 'DescribeClusterRequest' => [ 'type' => 'structure', 'required' => [ 'ClusterName', ], 'members' => [ 'ClusterName' => [ 'shape' => 'ClusterNameOrArn', ], ], ], 'DescribeClusterResponse' => [ 'type' => 'structure', 'required' => [ 'ClusterArn', 'ClusterStatus', 'InstanceGroups', ], 'members' => [ 'ClusterArn' => [ 'shape' => 'ClusterArn', ], 'ClusterName' => [ 'shape' => 'ClusterName', ], 'ClusterStatus' => [ 'shape' => 'ClusterStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'FailureMessage' => [ 'shape' => 'String', ], 'InstanceGroups' => [ 'shape' => 'ClusterInstanceGroupDetailsList', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], ], ], 'DescribeCodeRepositoryInput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeCodeRepositoryOutput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', 'CodeRepositoryArn', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], 'CodeRepositoryArn' => [ 'shape' => 'CodeRepositoryArn', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'GitConfig' => [ 'shape' => 'GitConfig', ], ], ], 'DescribeCompilationJobRequest' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeCompilationJobResponse' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', 'CompilationJobArn', 'CompilationJobStatus', 'StoppingCondition', 'CreationTime', 'LastModifiedTime', 'FailureReason', 'ModelArtifacts', 'RoleArn', 'InputConfig', 'OutputConfig', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobArn' => [ 'shape' => 'CompilationJobArn', ], 'CompilationJobStatus' => [ 'shape' => 'CompilationJobStatus', ], 'CompilationStartTime' => [ 'shape' => 'Timestamp', ], 'CompilationEndTime' => [ 'shape' => 'Timestamp', ], 'StoppingCondition' => [ 'shape' => 'StoppingCondition', ], 'InferenceImage' => [ 'shape' => 'InferenceImage', ], 'ModelPackageVersionArn' => [ 'shape' => 'ModelPackageArn', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ModelArtifacts' => [ 'shape' => 'ModelArtifacts', ], 'ModelDigests' => [ 'shape' => 'ModelDigests', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'InputConfig' => [ 'shape' => 'InputConfig', ], 'OutputConfig' => [ 'shape' => 'OutputConfig', ], 'VpcConfig' => [ 'shape' => 'NeoVpcConfig', ], 'DerivedInformation' => [ 'shape' => 'DerivedInformation', ], ], ], 'DescribeContextRequest' => [ 'type' => 'structure', 'required' => [ 'ContextName', ], 'members' => [ 'ContextName' => [ 'shape' => 'ContextNameOrArn', ], ], ], 'DescribeContextResponse' => [ 'type' => 'structure', 'members' => [ 'ContextName' => [ 'shape' => 'ContextName', ], 'ContextArn' => [ 'shape' => 'ContextArn', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeDataQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeDataQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'DataQualityAppSpecification', 'DataQualityJobInput', 'DataQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'DataQualityBaselineConfig' => [ 'shape' => 'DataQualityBaselineConfig', ], 'DataQualityAppSpecification' => [ 'shape' => 'DataQualityAppSpecification', ], 'DataQualityJobInput' => [ 'shape' => 'DataQualityJobInput', ], 'DataQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeDeviceFleetRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeDeviceFleetResponse' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'DeviceFleetArn', 'OutputConfig', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'DeviceFleetArn' => [ 'shape' => 'DeviceFleetArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'Description' => [ 'shape' => 'DeviceFleetDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'IotRoleAlias' => [ 'shape' => 'IotRoleAlias', ], ], ], 'DescribeDeviceRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceName', 'DeviceFleetName', ], 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'DeviceName' => [ 'shape' => 'EntityName', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeDeviceResponse' => [ 'type' => 'structure', 'required' => [ 'DeviceName', 'DeviceFleetName', 'RegistrationTime', ], 'members' => [ 'DeviceArn' => [ 'shape' => 'DeviceArn', ], 'DeviceName' => [ 'shape' => 'EntityName', ], 'Description' => [ 'shape' => 'DeviceDescription', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'IotThingName' => [ 'shape' => 'ThingName', ], 'RegistrationTime' => [ 'shape' => 'Timestamp', ], 'LatestHeartbeat' => [ 'shape' => 'Timestamp', ], 'Models' => [ 'shape' => 'EdgeModels', ], 'MaxModels' => [ 'shape' => 'Integer', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'AgentVersion' => [ 'shape' => 'EdgeVersion', ], ], ], 'DescribeDomainRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], ], ], 'DescribeDomainResponse' => [ 'type' => 'structure', 'members' => [ 'DomainArn' => [ 'shape' => 'DomainArn', ], 'DomainId' => [ 'shape' => 'DomainId', ], 'DomainName' => [ 'shape' => 'DomainName', ], 'HomeEfsFileSystemId' => [ 'shape' => 'ResourceId', ], 'SingleSignOnManagedApplicationInstanceId' => [ 'shape' => 'String256', ], 'SingleSignOnApplicationArn' => [ 'shape' => 'SingleSignOnApplicationArn', ], 'Status' => [ 'shape' => 'DomainStatus', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'SecurityGroupIdForDomainBoundary' => [ 'shape' => 'SecurityGroupId', ], 'AuthMode' => [ 'shape' => 'AuthMode', ], 'DefaultUserSettings' => [ 'shape' => 'UserSettings', ], 'DomainSettings' => [ 'shape' => 'DomainSettings', ], 'AppNetworkAccessType' => [ 'shape' => 'AppNetworkAccessType', ], 'HomeEfsFileSystemKmsKeyId' => [ 'shape' => 'KmsKeyId', 'deprecated' => true, 'deprecatedMessage' => 'This property is deprecated, use KmsKeyId instead.', ], 'SubnetIds' => [ 'shape' => 'Subnets', ], 'Url' => [ 'shape' => 'String1024', ], 'VpcId' => [ 'shape' => 'VpcId', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AppSecurityGroupManagement' => [ 'shape' => 'AppSecurityGroupManagement', ], 'DefaultSpaceSettings' => [ 'shape' => 'DefaultSpaceSettings', ], ], ], 'DescribeEdgeDeploymentPlanRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'MaxResults' => [ 'shape' => 'DeploymentStageMaxResults', ], ], ], 'DescribeEdgeDeploymentPlanResponse' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanArn', 'EdgeDeploymentPlanName', 'ModelConfigs', 'DeviceFleetName', 'Stages', ], 'members' => [ 'EdgeDeploymentPlanArn' => [ 'shape' => 'EdgeDeploymentPlanArn', ], 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'ModelConfigs' => [ 'shape' => 'EdgeDeploymentModelConfigs', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'EdgeDeploymentSuccess' => [ 'shape' => 'Integer', ], 'EdgeDeploymentPending' => [ 'shape' => 'Integer', ], 'EdgeDeploymentFailed' => [ 'shape' => 'Integer', ], 'Stages' => [ 'shape' => 'DeploymentStageStatusSummaries', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeEdgePackagingJobRequest' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobName', ], 'members' => [ 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeEdgePackagingJobResponse' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobArn', 'EdgePackagingJobName', 'EdgePackagingJobStatus', ], 'members' => [ 'EdgePackagingJobArn' => [ 'shape' => 'EdgePackagingJobArn', ], 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'ModelName' => [ 'shape' => 'EntityName', ], 'ModelVersion' => [ 'shape' => 'EdgeVersion', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'ResourceKey' => [ 'shape' => 'KmsKeyId', ], 'EdgePackagingJobStatus' => [ 'shape' => 'EdgePackagingJobStatus', ], 'EdgePackagingJobStatusMessage' => [ 'shape' => 'String', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'ModelArtifact' => [ 'shape' => 'S3Uri', ], 'ModelSignature' => [ 'shape' => 'String', ], 'PresetDeploymentOutput' => [ 'shape' => 'EdgePresetDeploymentOutput', ], ], ], 'DescribeEndpointConfigInput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], ], ], 'DescribeEndpointConfigOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', 'EndpointConfigArn', 'ProductionVariants', 'CreationTime', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'EndpointConfigArn' => [ 'shape' => 'EndpointConfigArn', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfig', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'ExecutionRoleArn' => [ 'shape' => 'RoleArn', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'EnableNetworkIsolation' => [ 'shape' => 'Boolean', ], ], ], 'DescribeEndpointInput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], ], ], 'DescribeEndpointOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', 'EndpointArn', 'EndpointStatus', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointArn' => [ 'shape' => 'EndpointArn', ], 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantSummaryList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfigSummary', ], 'EndpointStatus' => [ 'shape' => 'EndpointStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastDeploymentConfig' => [ 'shape' => 'DeploymentConfig', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'PendingDeploymentSummary' => [ 'shape' => 'PendingDeploymentSummary', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantSummaryList', ], ], ], 'DescribeExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'ExperimentName', ], 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DescribeExperimentResponse' => [ 'type' => 'structure', 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], 'ExperimentArn' => [ 'shape' => 'ExperimentArn', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ExperimentSource', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeFeatureGroupRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupNameOrArn', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'DescribeFeatureGroupResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', 'FeatureGroupName', 'RecordIdentifierFeatureName', 'EventTimeFeatureName', 'FeatureDefinitions', 'CreationTime', 'NextToken', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'RecordIdentifierFeatureName' => [ 'shape' => 'FeatureName', ], 'EventTimeFeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureDefinitions' => [ 'shape' => 'FeatureDefinitions', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'OnlineStoreConfig' => [ 'shape' => 'OnlineStoreConfig', ], 'OfflineStoreConfig' => [ 'shape' => 'OfflineStoreConfig', ], 'ThroughputConfig' => [ 'shape' => 'ThroughputConfigDescription', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'FeatureGroupStatus' => [ 'shape' => 'FeatureGroupStatus', ], 'OfflineStoreStatus' => [ 'shape' => 'OfflineStoreStatus', ], 'LastUpdateStatus' => [ 'shape' => 'LastUpdateStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'Description' => [ 'shape' => 'Description', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'OnlineStoreTotalSizeBytes' => [ 'shape' => 'OnlineStoreTotalSizeBytes', ], ], ], 'DescribeFeatureMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', 'FeatureName', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupNameOrArn', ], 'FeatureName' => [ 'shape' => 'FeatureName', ], ], ], 'DescribeFeatureMetadataResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', 'FeatureGroupName', 'FeatureName', 'FeatureType', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'FeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureType' => [ 'shape' => 'FeatureType', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'Description' => [ 'shape' => 'FeatureDescription', ], 'Parameters' => [ 'shape' => 'FeatureParameters', ], ], ], 'DescribeFlowDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionName', ], 'members' => [ 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], ], ], 'DescribeFlowDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionArn', 'FlowDefinitionName', 'FlowDefinitionStatus', 'CreationTime', 'OutputConfig', 'RoleArn', ], 'members' => [ 'FlowDefinitionArn' => [ 'shape' => 'FlowDefinitionArn', ], 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], 'FlowDefinitionStatus' => [ 'shape' => 'FlowDefinitionStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'HumanLoopRequestSource' => [ 'shape' => 'HumanLoopRequestSource', ], 'HumanLoopActivationConfig' => [ 'shape' => 'HumanLoopActivationConfig', ], 'HumanLoopConfig' => [ 'shape' => 'HumanLoopConfig', ], 'OutputConfig' => [ 'shape' => 'FlowDefinitionOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], ], ], 'DescribeHubContentRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubContentType', 'HubContentName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], ], ], 'DescribeHubContentResponse' => [ 'type' => 'structure', 'required' => [ 'HubContentName', 'HubContentArn', 'HubContentVersion', 'HubContentType', 'DocumentSchemaVersion', 'HubName', 'HubArn', 'HubContentDocument', 'HubContentStatus', 'CreationTime', ], 'members' => [ 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentArn' => [ 'shape' => 'HubContentArn', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'DocumentSchemaVersion' => [ 'shape' => 'DocumentSchemaVersion', ], 'HubName' => [ 'shape' => 'HubName', ], 'HubArn' => [ 'shape' => 'HubArn', ], 'HubContentDisplayName' => [ 'shape' => 'HubContentDisplayName', ], 'HubContentDescription' => [ 'shape' => 'HubContentDescription', ], 'HubContentMarkdown' => [ 'shape' => 'HubContentMarkdown', ], 'HubContentDocument' => [ 'shape' => 'HubContentDocument', ], 'HubContentSearchKeywords' => [ 'shape' => 'HubContentSearchKeywordList', ], 'HubContentDependencies' => [ 'shape' => 'HubContentDependencyList', ], 'HubContentStatus' => [ 'shape' => 'HubContentStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], ], ], 'DescribeHubResponse' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubArn', 'HubStatus', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubArn' => [ 'shape' => 'HubArn', ], 'HubDisplayName' => [ 'shape' => 'HubDisplayName', ], 'HubDescription' => [ 'shape' => 'HubDescription', ], 'HubSearchKeywords' => [ 'shape' => 'HubSearchKeywordList', ], 'S3StorageConfig' => [ 'shape' => 'HubS3StorageConfig', ], 'HubStatus' => [ 'shape' => 'HubStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], ], ], 'DescribeHumanTaskUiResponse' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiArn', 'HumanTaskUiName', 'CreationTime', 'UiTemplate', ], 'members' => [ 'HumanTaskUiArn' => [ 'shape' => 'HumanTaskUiArn', ], 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], 'HumanTaskUiStatus' => [ 'shape' => 'HumanTaskUiStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'UiTemplate' => [ 'shape' => 'UiTemplateInfo', ], ], ], 'DescribeHyperParameterTuningJobRequest' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], ], ], 'DescribeHyperParameterTuningJobResponse' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', 'HyperParameterTuningJobArn', 'HyperParameterTuningJobConfig', 'HyperParameterTuningJobStatus', 'CreationTime', 'TrainingJobStatusCounters', 'ObjectiveStatusCounters', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], 'HyperParameterTuningJobArn' => [ 'shape' => 'HyperParameterTuningJobArn', ], 'HyperParameterTuningJobConfig' => [ 'shape' => 'HyperParameterTuningJobConfig', ], 'TrainingJobDefinition' => [ 'shape' => 'HyperParameterTrainingJobDefinition', ], 'TrainingJobDefinitions' => [ 'shape' => 'HyperParameterTrainingJobDefinitions', ], 'HyperParameterTuningJobStatus' => [ 'shape' => 'HyperParameterTuningJobStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'HyperParameterTuningEndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'TrainingJobStatusCounters' => [ 'shape' => 'TrainingJobStatusCounters', ], 'ObjectiveStatusCounters' => [ 'shape' => 'ObjectiveStatusCounters', ], 'BestTrainingJob' => [ 'shape' => 'HyperParameterTrainingJobSummary', ], 'OverallBestTrainingJob' => [ 'shape' => 'HyperParameterTrainingJobSummary', ], 'WarmStartConfig' => [ 'shape' => 'HyperParameterTuningJobWarmStartConfig', ], 'Autotune' => [ 'shape' => 'Autotune', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'TuningJobCompletionDetails' => [ 'shape' => 'HyperParameterTuningJobCompletionDetails', ], 'ConsumedResources' => [ 'shape' => 'HyperParameterTuningJobConsumedResources', ], ], ], 'DescribeImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], ], ], 'DescribeImageResponse' => [ 'type' => 'structure', 'members' => [ 'CreationTime' => [ 'shape' => 'Timestamp', ], 'Description' => [ 'shape' => 'ImageDescription', ], 'DisplayName' => [ 'shape' => 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'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeModelBiasJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelBiasJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelBiasAppSpecification', 'ModelBiasJobInput', 'ModelBiasJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelBiasBaselineConfig' => [ 'shape' => 'ModelBiasBaselineConfig', ], 'ModelBiasAppSpecification' => [ 'shape' => 'ModelBiasAppSpecification', ], 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'ModelCardName' => [ 'shape' => 'EntityName', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'OutputConfig' => [ 'shape' => 'ModelCardExportOutputConfig', ], 'CreatedAt' => [ 'shape' => 'Timestamp', ], 'LastModifiedAt' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ExportArtifacts' => [ 'shape' => 'ModelCardExportArtifacts', ], ], ], 'DescribeModelCardRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'ModelCardNameOrArn', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], ], ], 'DescribeModelCardResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardArn', 'ModelCardName', 'ModelCardVersion', 'Content', 'ModelCardStatus', 'CreationTime', 'CreatedBy', ], 'members' => [ 'ModelCardArn' => [ 'shape' => 'ModelCardArn', ], 'ModelCardName' => [ 'shape' => 'EntityName', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'Content' => [ 'shape' => 'ModelCardContent', ], 'ModelCardStatus' => [ 'shape' => 'ModelCardStatus', ], 'SecurityConfig' => [ 'shape' => 'ModelCardSecurityConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'ModelCardProcessingStatus' => [ 'shape' => 'ModelCardProcessingStatus', ], ], ], 'DescribeModelExplainabilityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelExplainabilityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelExplainabilityAppSpecification', 'ModelExplainabilityJobInput', 'ModelExplainabilityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => 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'SecurityGroups' => [ 'shape' => 'SecurityGroupIds', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'NetworkInterfaceId' => [ 'shape' => 'NetworkInterfaceId', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'NotebookInstanceLifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], 'DirectInternetAccess' => [ 'shape' => 'DirectInternetAccess', ], 'VolumeSizeInGB' => [ 'shape' => 'NotebookInstanceVolumeSizeInGB', ], 'AcceleratorTypes' => [ 'shape' => 'NotebookInstanceAcceleratorTypes', ], 'DefaultCodeRepository' => [ 'shape' => 'CodeRepositoryNameOrUrl', ], 'AdditionalCodeRepositories' => [ 'shape' => 'AdditionalCodeRepositoryNamesOrUrls', ], 'RootAccess' => [ 'shape' => 'RootAccess', ], 'PlatformIdentifier' => [ 'shape' => 'PlatformIdentifier', ], 'InstanceMetadataServiceConfiguration' => [ 'shape' => 'InstanceMetadataServiceConfiguration', ], ], ], 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=> 'float', 'min' => 0, ], 'VectorConfig' => [ 'type' => 'structure', 'required' => [ 'Dimension', ], 'members' => [ 'Dimension' => [ 'shape' => 'Dimension', ], ], ], 'VendorGuidance' => [ 'type' => 'string', 'enum' => [ 'NOT_PROVIDED', 'STABLE', 'TO_BE_ARCHIVED', 'ARCHIVED', ], ], 'VersionId' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '.+', ], 'VersionedArnOrName' => [ 'type' => 'string', 'max' => 176, 'min' => 1, 'pattern' => '(arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:[a-z\\-]*\\/)?([a-zA-Z0-9]([a-zA-Z0-9-]){0,62})(? [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'AssociationEntityArn', ], 'Type' => [ 'shape' => 'String40', ], 'LineageType' => [ 'shape' => 'LineageType', ], ], ], 'Vertices' => [ 'type' => 'list', 'member' => [ 'shape' => 'Vertex', ], ], 'VisibilityConditions' => [ 'type' => 'structure', 'members' => [ 'Key' => [ 'shape' => 'VisibilityConditionsKey', ], 'Value' => [ 'shape' => 'VisibilityConditionsValue', ], ], ], 'VisibilityConditionsKey' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:/=+\\-@]*)$', ], 'VisibilityConditionsList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VisibilityConditions', ], 'max' => 5, 'min' => 1, ], 'VisibilityConditionsValue' => [ 'type' => 'string', 'max' => 256, 'min' => 0, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:/=+\\-@]*)$', ], 'VolumeSizeInGB' => [ 'type' => 'integer', 'min' => 1, ], 'VpcConfig' => [ 'type' => 'structure', 'required' => [ 'SecurityGroupIds', 'Subnets', ], 'members' => [ 'SecurityGroupIds' => [ 'shape' => 'VpcSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'Subnets', ], ], ], 'VpcId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '[-0-9a-zA-Z]+', ], 'VpcOnlyTrustedAccounts' => [ 'type' => 'list', 'member' => [ 'shape' => 'AccountId', ], 'max' => 10, ], 'VpcSecurityGroupIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityGroupId', ], 'max' => 5, 'min' => 1, ], 'WaitIntervalInSeconds' => [ 'type' => 'integer', 'max' => 3600, 'min' => 0, ], 'WarmPoolResourceStatus' => [ 'type' => 'string', 'enum' => [ 'Available', 'Terminated', 'Reused', 'InUse', ], ], 'WarmPoolStatus' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'WarmPoolResourceStatus', ], 'ResourceRetainedBillableTimeInSeconds' => [ 'shape' => 'ResourceRetainedBillableTimeInSeconds', ], 'ReusedByJob' => [ 'shape' => 'TrainingJobName', ], ], ], 'Workforce' => [ 'type' => 'structure', 'required' => [ 'WorkforceName', 'WorkforceArn', ], 'members' => [ 'WorkforceName' => [ 'shape' => 'WorkforceName', ], 'WorkforceArn' => [ 'shape' => 'WorkforceArn', ], 'LastUpdatedDate' => [ 'shape' => 'Timestamp', ], 'SourceIpConfig' => [ 'shape' => 'SourceIpConfig', ], 'SubDomain' => [ 'shape' => 'String', ], 'CognitoConfig' => [ 'shape' => 'CognitoConfig', ], 'OidcConfig' => [ 'shape' => 'OidcConfigForResponse', ], 'CreateDate' => [ 'shape' => 'Timestamp', ], 'WorkforceVpcConfig' => [ 'shape' => 'WorkforceVpcConfigResponse', ], 'Status' => [ 'shape' => 'WorkforceStatus', ], 'FailureReason' => [ 'shape' => 'WorkforceFailureReason', ], ], ], 'WorkforceArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:workforce/.*', ], 'WorkforceFailureReason' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '.+', ], 'WorkforceName' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '^[a-zA-Z0-9]([a-zA-Z0-9\\-]){0,62}$', ], 'WorkforceSecurityGroupId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^sg-[0-9a-z]*$', ], 'WorkforceSecurityGroupIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'WorkforceSecurityGroupId', ], 'max' => 5, 'min' => 1, ], 'WorkforceStatus' => [ 'type' => 'string', 'enum' => [ 'Initializing', 'Updating', 'Deleting', 'Failed', 'Active', ], ], 'WorkforceSubnetId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^subnet-[0-9a-z]*$', ], 'WorkforceSubnets' => [ 'type' => 'list', 'member' => [ 'shape' => 'WorkforceSubnetId', ], 'max' => 16, 'min' => 1, ], 'WorkforceVpcConfigRequest' => [ 'type' => 'structure', 'members' => [ 'VpcId' => [ 'shape' => 'WorkforceVpcId', ], 'SecurityGroupIds' => [ 'shape' => 'WorkforceSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'WorkforceSubnets', ], ], ], 'WorkforceVpcConfigResponse' => [ 'type' => 'structure', 'required' => [ 'VpcId', 'SecurityGroupIds', 'Subnets', ], 'members' => [ 'VpcId' => [ 'shape' => 'WorkforceVpcId', ], 'SecurityGroupIds' => [ 'shape' => 'WorkforceSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'WorkforceSubnets', ], 'VpcEndpointId' => [ 'shape' => 'WorkforceVpcEndpointId', ], ], ], 'WorkforceVpcEndpointId' => [ 'type' => 'string', 'max' => 255, 'min' => 1, 'pattern' => '^vpce-[0-9a-z]*$', ], 'WorkforceVpcId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^vpc-[0-9a-z]*$', ], 'Workforces' => [ 'type' => 'list', 'member' => [ 'shape' => 'Workforce', ], ], 'WorkspaceSettings' => [ 'type' => 'structure', 'members' => [ 'S3ArtifactPath' => [ 'shape' => 'S3Uri', ], 'S3KmsKeyId' => [ 'shape' => 'KmsKeyId', ], ], ], 'Workteam' => [ 'type' => 'structure', 'required' => [ 'WorkteamName', 'MemberDefinitions', 'WorkteamArn', 'Description', ], 'members' => [ 'WorkteamName' => [ 'shape' => 'WorkteamName', ], 'MemberDefinitions' => [ 'shape' => 'MemberDefinitions', ], 'WorkteamArn' => [ 'shape' => 'WorkteamArn', ], 'WorkforceArn' => [ 'shape' => 'WorkforceArn', ], 'ProductListingIds' => [ 'shape' => 'ProductListings', ], 'Description' => [ 'shape' => 'String200', ], 'SubDomain' => [ 'shape' => 'String', ], 'CreateDate' => [ 'shape' => 'Timestamp', ], 'LastUpdatedDate' => [ 'shape' => 'Timestamp', ], 'NotificationConfiguration' => [ 'shape' => 'NotificationConfiguration', ], ], ], 'WorkteamArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:workteam/.*', ], 'WorkteamName' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'Workteams' => [ 'type' => 'list', 'member' => [ 'shape' => 'Workteam', ], ], ],]; diff --git a/src/data/sagemaker/2017-07-24/docs-2.json b/src/data/sagemaker/2017-07-24/docs-2.json index b4d2b71859..e4a409ba34 100644 --- a/src/data/sagemaker/2017-07-24/docs-2.json +++ b/src/data/sagemaker/2017-07-24/docs-2.json @@ -19,7 +19,7 @@ "CreateContext": "Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
", "CreateDataQualityJobDefinition": "Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
", "CreateDeviceFleet": "Creates a device fleet.
", - "CreateDomain": "Creates a Domain
. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All traffic between the domain and the EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType
parameter. AppNetworkAccessType
corresponds to the network access type that you choose when you onboard to the domain. The following options are available:
PublicInternetOnly
- Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
VpcOnly
- All traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
When internet access is disabled, you won't be able to run a Amazon SageMaker Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker Studio app successfully.
For more information, see Connect Amazon SageMaker Studio Notebooks to Resources in a VPC.
", + "CreateDomain": "Creates a Domain
. A domain consists of an associated Amazon Elastic File System volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All traffic between the domain and the Amazon EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType
parameter. AppNetworkAccessType
corresponds to the network access type that you choose when you onboard to the domain. The following options are available:
PublicInternetOnly
- Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
VpcOnly
- All traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
When internet access is disabled, you won't be able to run a Amazon SageMaker Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker Studio app successfully.
For more information, see Connect Amazon SageMaker Studio Notebooks to Resources in a VPC.
", "CreateEdgeDeploymentPlan": "Creates an edge deployment plan, consisting of multiple stages. Each stage may have a different deployment configuration and devices.
", "CreateEdgeDeploymentStage": "Creates a new stage in an existing edge deployment plan.
", "CreateEdgePackagingJob": "Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.
", @@ -85,6 +85,7 @@ "DeleteHub": "Delete a hub.
Hub APIs are only callable through SageMaker Studio.
Delete the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
Use this operation to delete a human task user interface (worker task template).
To see a list of human task user interfaces (work task templates) in your account, use ListHumanTaskUis. When you delete a worker task template, it no longer appears when you call ListHumanTaskUis
.
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob
API deletes only the tuning job entry that was created in SageMaker when you called the CreateHyperParameterTuningJob
API. It does not delete training jobs, artifacts, or the IAM role that you specified when creating the model.
Deletes a SageMaker image and all versions of the image. The container images aren't deleted.
", "DeleteImageVersion": "Deletes a version of a SageMaker image. The container image the version represents isn't deleted.
", "DeleteInferenceComponent": "Deletes an inference component.
", @@ -293,7 +294,7 @@ "UpdateDeviceFleet": "Updates a fleet of devices.
", "UpdateDevices": "Updates one or more devices in a fleet.
", "UpdateDomain": "Updates the default settings for new user profiles in the domain.
", - "UpdateEndpoint": "Deploys the new EndpointConfig
specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous EndpointConfig
(there is no availability loss).
When SageMaker receives the request, it sets the endpoint status to Updating
. After updating the endpoint, it sets the status to InService
. To check the status of an endpoint, use the DescribeEndpoint API.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig
.
If you delete the EndpointConfig
of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Deploys the EndpointConfig
specified in the request to a new fleet of instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint configuration and then deletes the old instances using the previous EndpointConfig
(there is no availability loss). For more information about how to control the update and traffic shifting process, see Update models in production.
When SageMaker receives the request, it sets the endpoint status to Updating
. After updating the endpoint, it sets the status to InService
. To check the status of an endpoint, use the DescribeEndpoint API.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig
.
If you delete the EndpointConfig
of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, SageMaker sets the endpoint status to Updating
. After updating the endpoint, it sets the status to InService
. To check the status of an endpoint, use the DescribeEndpoint API.
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
", "UpdateFeatureGroup": "Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the UpdateFeatureGroup
API.
You can add features for your feature group using the FeatureAdditions
request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the OnlineStoreConfig
request parameter. If a TtlDuration
is specified, the default TtlDuration
applies for all records added to the feature group after the feature group is updated. If a record level TtlDuration
exists from using the PutRecord
API, the record level TtlDuration
applies to that record instead of the default TtlDuration
.
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
", "DeleteModelPackageGroupInput$ModelPackageGroupName": "The name of the model group to delete.
", "DescribeAlgorithmInput$AlgorithmName": "The name of the algorithm to describe.
", - "DescribeModelPackageGroupInput$ModelPackageGroupName": "The name of gthe model group to describe.
", + "DescribeModelPackageGroupInput$ModelPackageGroupName": "The name of the model group to describe.
", "HyperParameterAlgorithmSpecification$AlgorithmName": "The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage
.
A filter that returns only model versions that belong to the specified model group.
", "SourceAlgorithm$AlgorithmName": "The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
" @@ -3595,6 +3596,11 @@ "refs": { } }, + "DeleteHyperParameterTuningJobRequest": { + "base": null, + "refs": { + } + }, "DeleteImageRequest": { "base": null, "refs": { @@ -6789,6 +6795,7 @@ "base": null, "refs": { "CreateHyperParameterTuningJobRequest$HyperParameterTuningJobName": "The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
", + "DeleteHyperParameterTuningJobRequest$HyperParameterTuningJobName": "The name of the hyperparameter tuning job that you want to delete.
", "DescribeHyperParameterTuningJobRequest$HyperParameterTuningJobName": "The name of the tuning job.
", "DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobName": "The name of the hyperparameter tuning job.
", "HyperParameterTrainingJobSummary$TuningJobName": "The HyperParameter tuning job that launched the training job.
", @@ -6835,7 +6842,7 @@ "HyperParameterTuningJobStatus": { "base": null, "refs": { - "DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobStatus": "The status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped.
", + "DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobStatus": "The status of the tuning job.
", "HyperParameterTuningJobSearchEntity$HyperParameterTuningJobStatus": "The status of a hyperparameter tuning job.
", "HyperParameterTuningJobSummary$HyperParameterTuningJobStatus": "The status of the tuning job.
", "ListHyperParameterTuningJobsRequest$StatusEquals": "A filter that returns only tuning jobs with the specified status.
" @@ -9342,7 +9349,7 @@ } }, "ModelAccessConfig": { - "base": "The access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig
. For more information, see End-user license agreements.
The access configuration file to control access to the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig
.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
If you are an AutoML user, see the Optional Parameters section of Create an AutoML job to fine-tune text generation models using the API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML API.
Specifies the access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig
. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The ID of the Amazon Elastic File System (EFS) managed by this Domain.
" + "DescribeDomainResponse$HomeEfsFileSystemId": "The ID of the Amazon Elastic File System managed by this Domain.
" } }, "ResourceInUse": { @@ -13078,7 +13085,7 @@ "RecommendationJobCompiledOutputConfig$S3OutputUri": "Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.
", "RecommendationJobPayloadConfig$SamplePayloadUrl": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
", "RedshiftDatasetDefinition$OutputS3Uri": "The location in Amazon S3 where the Redshift query results are stored.
", - "S3DataSource$S3Uri": "Depending on the value specified for the S3DataType
, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix
A manifest might look like this: s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of S3Uri
. Note that the prefix must be a valid non-empty S3Uri
that precludes users from specifying a manifest whose individual S3Uri
is sourced from different S3 buckets.
The following code example shows a valid manifest format:
[ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\"relative/path/to/custdata-1\",
\"relative/path/custdata-2\",
...
\"relative/path/custdata-N\"
]
This JSON is equivalent to the following S3Uri
list:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uri
in this manifest is the input data for the channel for this data source. The object that each S3Uri
points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
", + "S3DataSource$S3Uri": "Depending on the value specified for the S3DataType
, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix/
A manifest might look like this: s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of S3Uri
. Note that the prefix must be a valid non-empty S3Uri
that precludes users from specifying a manifest whose individual S3Uri
is sourced from different S3 buckets.
The following code example shows a valid manifest format:
[ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\"relative/path/to/custdata-1\",
\"relative/path/custdata-2\",
...
\"relative/path/custdata-N\"
]
This JSON is equivalent to the following S3Uri
list:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uri
in this manifest is the input data for the channel for this data source. The object that each S3Uri
points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
", "S3StorageConfig$S3Uri": "The S3 URI, or location in Amazon S3, of OfflineStore
.
S3 URIs have a format similar to the following: s3://example-bucket/prefix/
.
The S3 path where offline records are written.
", "SharingSettings$S3OutputPath": "When NotebookOutputOption
is Allowed
, the Amazon S3 bucket used to store the shared notebook snapshots.
Path to Amazon S3 storage location for TensorBoard output.
", "TimeSeriesForecastingJobConfig$FeatureSpecificationS3Uri": "A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig
. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig
. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig
.
You can input FeatureAttributeNames
(optional) in JSON format as shown below:
{ \"FeatureAttributeNames\":[\"col1\", \"col2\", ...] }
.
You can also specify the data type of the feature (optional) in the format shown below:
{ \"FeatureDataTypes\":{\"col1\":\"numeric\", \"col2\":\"categorical\" ... } }
Autopilot supports the following data types: numeric
, categorical
, text
, and datetime
.
These column keys must not include any column set in TimeSeriesConfig
.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example, s3://bucket-name/key-name-prefix
.
For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out
suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at s3://bucket-name/input-name-prefix/dataset01/data.csv
, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out
. Batch transform doesn't upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out
file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.
Depending on the value specified for the S3DataType
, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix
.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\"relative/path/to/custdata-1\",
\"relative/path/custdata-2\",
...
\"relative/path/custdata-N\"
]
The preceding JSON matches the following S3Uris
:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris
in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris
points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
Depending on the value specified for the S3DataType
, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix/
.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\"relative/path/to/custdata-1\",
\"relative/path/custdata-2\",
...
\"relative/path/custdata-N\"
]
The preceding JSON matches the following S3Uris
:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris
in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris
points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
", "WorkspaceSettings$S3ArtifactPath": "The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users must log out and log back in to apply the new location.
" } @@ -14573,7 +14580,7 @@ } }, "ThroughputConfigDescription": { - "base": "Active throughput configuration of the feature group. Used to set feature group throughput configuration. There are two modes: ON_DEMAND
and PROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use the Standard
tier online store.
Active throughput configuration of the feature group. There are two modes: ON_DEMAND
and PROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use the Standard
tier online store.
Provides APIs for creating and managing SageMaker resources.
Other Resources:
', 'operations' => [ 'AddAssociation' => 'Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'AddTags' => 'Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags
parameter of CreateHyperParameterTuningJob
Tags that you add to a SageMaker Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags
parameter of CreateDomain or CreateUserProfile.
Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
', 'BatchDescribeModelPackage' => 'This action batch describes a list of versioned model packages
', 'CreateAction' => 'Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateAlgorithm' => 'Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
', 'CreateApp' => 'Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
', 'CreateAppImageConfig' => 'Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.
', 'CreateArtifact' => 'Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateAutoMLJob' => 'Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
CreateAutoMLJobV2
can manage tabular problem types identical to those of its previous version CreateAutoMLJob
, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob
to CreateAutoMLJobV2
in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
', 'CreateAutoMLJobV2' => 'Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.
CreateAutoMLJobV2
can manage tabular problem types identical to those of its previous version CreateAutoMLJob
, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob
to CreateAutoMLJobV2
in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2
, see AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
', 'CreateCluster' => 'Creates a SageMaker HyperPod cluster. SageMaker HyperPod is a capability of SageMaker for creating and managing persistent clusters for developing large machine learning models, such as large language models (LLMs) and diffusion models. To learn more, see Amazon SageMaker HyperPod in the Amazon SageMaker Developer Guide.
', 'CreateCodeRepository' => 'Creates a Git repository as a resource in your SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.
', 'CreateCompilationJob' => 'Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
You can also provide a Tag
to track the model compilation job\'s resource use and costs. The response body contains the CompilationJobArn
for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
', 'CreateContext' => 'Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateDataQualityJobDefinition' => 'Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'CreateDeviceFleet' => 'Creates a device fleet.
', 'CreateDomain' => 'Creates a Domain
. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All traffic between the domain and the EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType
parameter. AppNetworkAccessType
corresponds to the network access type that you choose when you onboard to the domain. The following options are available:
PublicInternetOnly
- Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
VpcOnly
- All traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
When internet access is disabled, you won\'t be able to run a Amazon SageMaker Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker Studio app successfully.
For more information, see Connect Amazon SageMaker Studio Notebooks to Resources in a VPC.
', 'CreateEdgeDeploymentPlan' => 'Creates an edge deployment plan, consisting of multiple stages. Each stage may have a different deployment configuration and devices.
', 'CreateEdgeDeploymentStage' => 'Creates a new stage in an existing edge deployment plan.
', 'CreateEdgePackagingJob' => 'Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.
', 'CreateEndpoint' => 'Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
Use this API to deploy models using SageMaker hosting services.
You must not delete an EndpointConfig
that is in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig
.
The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account.
When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads
, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
When SageMaker receives the request, it sets the endpoint status to Creating
. After it creates the endpoint, it sets the status to InService
. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
Option 1: For a full SageMaker access, search and attach the AmazonSageMakerFullAccess
policy.
Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
"Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
"Resource": [
"arn:aws:sagemaker:region:account-id:endpoint/endpointName"
"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
]
For more information, see SageMaker API Permissions: Actions, Permissions, and Resources Reference.
Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel
API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
Use this API if you want to use SageMaker hosting services to deploy models into production.
In the request, you define a ProductionVariant
, for each model that you want to deploy. Each ProductionVariant
parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight
to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads
, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
Creates a SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
In the Studio UI, trials are referred to as run groups and trial components are referred to as runs.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description
parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment\'s properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
', 'CreateFeatureGroup' => 'Create a new FeatureGroup
. A FeatureGroup
is a group of Features
defined in the FeatureStore
to describe a Record
.
The FeatureGroup
defines the schema and features contained in the FeatureGroup
. A FeatureGroup
definition is composed of a list of Features
, a RecordIdentifierFeatureName
, an EventTimeFeatureName
and configurations for its OnlineStore
and OfflineStore
. Check Amazon Web Services service quotas to see the FeatureGroup
s quota for your Amazon Web Services account.
Note that it can take approximately 10-15 minutes to provision an OnlineStore
FeatureGroup
with the InMemory
StorageType
.
You must include at least one of OnlineStoreConfig
and OfflineStoreConfig
to create a FeatureGroup
.
Creates a flow definition.
', 'CreateHub' => 'Create a hub.
Hub APIs are only callable through SageMaker Studio.
Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.
', 'CreateHyperParameterTuningJob' => 'Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Elastic Container Registry (ECR). For more information, see Bring your own SageMaker image.
', 'CreateImageVersion' => 'Creates a version of the SageMaker image specified by ImageName
. The version represents the Amazon Elastic Container Registry (ECR) container image specified by BaseImage
.
Creates an inference component, which is a SageMaker hosting object that you can use to deploy a model to an endpoint. In the inference component settings, you specify the model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You can optimize resource utilization by tailoring how the required CPU cores, accelerators, and memory are allocated. You can deploy multiple inference components to an endpoint, where each inference component contains one model and the resource utilization needs for that individual model. After you deploy an inference component, you can directly invoke the associated model when you use the InvokeEndpoint API action.
', 'CreateInferenceExperiment' => 'Creates an inference experiment using the configurations specified in the request.
Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For more information about inference experiments, see Shadow tests.
Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint\'s model variants based on your specified configuration.
While the experiment is in progress or after it has concluded, you can view metrics that compare your model variants. For more information, see View, monitor, and edit shadow tests.
', 'CreateInferenceRecommendationsJob' => 'Starts a recommendation job. You can create either an instance recommendation or load test job.
', 'CreateLabelingJob' => 'Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models.
You can select your workforce from one of three providers:
A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data.
The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri
have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress
) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
Creates a model in SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
Use this API to create a model if you want to use SageMaker hosting services or run a batch transform job.
To host your model, you create an endpoint configuration with the CreateEndpointConfig
API, and then create an endpoint with the CreateEndpoint
API. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
For an example that calls this method when deploying a model to SageMaker hosting services, see Create a Model (Amazon Web Services SDK for Python (Boto 3)).
To run a batch transform using your model, you start a job with the CreateTransformJob
API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
', 'CreateModelBiasJobDefinition' => 'Creates the definition for a model bias job.
', 'CreateModelCard' => 'Creates an Amazon SageMaker Model Card.
For information about how to use model cards, see Amazon SageMaker Model Card.
', 'CreateModelCardExportJob' => 'Creates an Amazon SageMaker Model Card export job.
', 'CreateModelExplainabilityJobDefinition' => 'Creates the definition for a model explainability job.
', 'CreateModelPackage' => 'Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification
. To create a model from an algorithm resource that you created or subscribed to in Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification
.
There are two types of model packages:
Versioned - a model that is part of a model group in the model registry.
Unversioned - a model package that is not part of a model group.
Creates a model group. A model group contains a group of model versions.
', 'CreateModelQualityJobDefinition' => 'Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'CreateMonitoringSchedule' => 'Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint.
', 'CreateNotebookInstance' => 'Creates an SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
In a CreateNotebookInstance
request, specify the type of ML compute instance that you want to run. SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.
After receiving the request, SageMaker does the following:
Creates a network interface in the SageMaker VPC.
(Option) If you specified SubnetId
, SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the SageMaker VPC. If you specified SubnetId
of your VPC, SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN). You can\'t change the name of a notebook instance after you create it.
After SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker endpoints, and validate hosted models.
For more information, see How It Works.
', 'CreateNotebookInstanceLifecycleConfig' => 'Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH
environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin
.
View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances
in log stream [notebook-instance-name]/[LifecycleConfigHook]
.
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'CreatePipeline' => 'Creates a pipeline using a JSON pipeline definition.
', 'CreatePresignedDomainUrl' => 'Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to the domain, and granted access to all of the Apps and files associated with the Domain\'s Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.
The IAM role or user passed to this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.
You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to Amazon SageMaker Studio Through an Interface VPC Endpoint .
The URL that you get from a call to CreatePresignedDomainUrl
has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds
. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker console, when you choose Open
next to a notebook instance, SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress
condition operator and the aws:SourceIP
condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
Creates a processing job.
', 'CreateProject' => 'Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
', 'CreateSpace' => 'Creates a space used for real time collaboration in a Domain.
', 'CreateStudioLifecycleConfig' => 'Creates a new Amazon SageMaker Studio Lifecycle Configuration.
', 'CreateTrainingJob' => 'Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
If you choose to host your model using SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than SageMaker, provided that you know how to use them for inference.
In the request body, you provide the following:
AlgorithmSpecification
- Identifies the training algorithm to use.
HyperParameters
- Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
InputDataConfig
- Describes the input required by the training job and the Amazon S3, EFS, or FSx location where it is stored.
OutputDataConfig
- Identifies the Amazon S3 bucket where you want SageMaker to save the results of model training.
ResourceConfig
- Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
EnableManagedSpotTraining
- Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training.
RoleArn
- The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training.
StoppingCondition
- To help cap training costs, use MaxRuntimeInSeconds
to set a time limit for training. Use MaxWaitTimeInSeconds
to specify how long a managed spot training job has to complete.
Environment
- The environment variables to set in the Docker container.
RetryStrategy
- The number of times to retry the job when the job fails due to an InternalServerError
.
For more information about SageMaker, see How It Works.
', 'CreateTransformJob' => 'Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
To perform batch transformations, you create a transform job and use the data that you have readily available.
In the request body, you provide the following:
TransformJobName
- Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
ModelName
- Identifies the model to use. ModelName
must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see CreateModel.
TransformInput
- Describes the dataset to be transformed and the Amazon S3 location where it is stored.
TransformOutput
- Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
TransformResources
- Identifies the ML compute instances for the transform job.
For more information about how batch transformation works, see Batch Transform.
', 'CreateTrial' => 'Creates an SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single SageMaker experiment.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial and then use the Search API to search for the tags.
To get a list of all your trials, call the ListTrials API. To view a trial\'s properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
', 'CreateTrialComponent' => 'Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials.
Trial components include pre-processing jobs, training jobs, and batch transform jobs.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial component and then use the Search API to search for the tags.
', 'CreateUserProfile' => 'Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to a domain. If an administrator invites a person by email or imports them from IAM Identity Center, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user\'s private Amazon Elastic File System (EFS) home directory.
', 'CreateWorkforce' => 'Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the DeleteWorkforce API operation to delete the existing workforce and then use CreateWorkforce
to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig
. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig
. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).
Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.
You cannot create more than 25 work teams in an account and region.
', 'DeleteAction' => 'Deletes an action.
', 'DeleteAlgorithm' => 'Removes the specified algorithm from your account.
', 'DeleteApp' => 'Used to stop and delete an app.
', 'DeleteAppImageConfig' => 'Deletes an AppImageConfig.
', 'DeleteArtifact' => 'Deletes an artifact. Either ArtifactArn
or Source
must be specified.
Deletes an association.
', 'DeleteCluster' => 'Delete a SageMaker HyperPod cluster.
', 'DeleteCodeRepository' => 'Deletes the specified Git repository from your account.
', 'DeleteCompilationJob' => 'Deletes the specified compilation job. This action deletes only the compilation job resource in Amazon SageMaker. It doesn\'t delete other resources that are related to that job, such as the model artifacts that the job creates, the compilation logs in CloudWatch, the compiled model, or the IAM role.
You can delete a compilation job only if its current status is COMPLETED
, FAILED
, or STOPPED
. If the job status is STARTING
or INPROGRESS
, stop the job, and then delete it after its status becomes STOPPED
.
Deletes an context.
', 'DeleteDataQualityJobDefinition' => 'Deletes a data quality monitoring job definition.
', 'DeleteDeviceFleet' => 'Deletes a fleet.
', 'DeleteDomain' => 'Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using IAM Identity Center. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
', 'DeleteEdgeDeploymentPlan' => 'Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan.
', 'DeleteEdgeDeploymentStage' => 'Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
', 'DeleteEndpoint' => 'Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don\'t need to use the RevokeGrant API call.
When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn
, otherwise SageMaker cannot delete these resources.
Deletes an endpoint configuration. The DeleteEndpointConfig
API deletes only the specified configuration. It does not delete endpoints created using the configuration.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. If you delete the EndpointConfig
of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Deletes an SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
', 'DeleteFeatureGroup' => 'Delete the FeatureGroup
and any data that was written to the OnlineStore
of the FeatureGroup
. Data cannot be accessed from the OnlineStore
immediately after DeleteFeatureGroup
is called.
Data written into the OfflineStore
will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your OfflineStore
are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore
FeatureGroup
with the InMemory
StorageType
.
Deletes the specified flow definition.
', 'DeleteHub' => 'Delete a hub.
Hub APIs are only callable through SageMaker Studio.
Delete the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
Use this operation to delete a human task user interface (worker task template).
To see a list of human task user interfaces (work task templates) in your account, use ListHumanTaskUis. When you delete a worker task template, it no longer appears when you call ListHumanTaskUis
.
Deletes a SageMaker image and all versions of the image. The container images aren\'t deleted.
', 'DeleteImageVersion' => 'Deletes a version of a SageMaker image. The container image the version represents isn\'t deleted.
', 'DeleteInferenceComponent' => 'Deletes an inference component.
', 'DeleteInferenceExperiment' => 'Deletes an inference experiment.
This operation does not delete your endpoint, variants, or any underlying resources. This operation only deletes the metadata of your experiment.
Deletes a model. The DeleteModel
API deletes only the model entry that was created in SageMaker when you called the CreateModel
API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
Deletes an Amazon SageMaker model bias job definition.
', 'DeleteModelCard' => 'Deletes an Amazon SageMaker Model Card.
', 'DeleteModelExplainabilityJobDefinition' => 'Deletes an Amazon SageMaker model explainability job definition.
', 'DeleteModelPackage' => 'Deletes a model package.
A model package is used to create SageMaker models or list on Amazon Web Services Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
', 'DeleteModelPackageGroup' => 'Deletes the specified model group.
', 'DeleteModelPackageGroupPolicy' => 'Deletes a model group resource policy.
', 'DeleteModelQualityJobDefinition' => 'Deletes the secified model quality monitoring job definition.
', 'DeleteMonitoringSchedule' => 'Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.
', 'DeleteNotebookInstance' => ' Deletes an SageMaker notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance
API.
When you delete a notebook instance, you lose all of your data. SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
Deletes a notebook instance lifecycle configuration.
', 'DeletePipeline' => 'Deletes a pipeline if there are no running instances of the pipeline. To delete a pipeline, you must stop all running instances of the pipeline using the StopPipelineExecution
API. When you delete a pipeline, all instances of the pipeline are deleted.
Delete the specified project.
', 'DeleteSpace' => 'Used to delete a space.
', 'DeleteStudioLifecycleConfig' => 'Deletes the Amazon SageMaker Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.
', 'DeleteTags' => 'Deletes the specified tags from an SageMaker resource.
To list a resource\'s tags, use the ListTags
API.
When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.
When you call this API to delete tags from a SageMaker Domain or User Profile, the deleted tags are not removed from Apps that the SageMaker Domain or User Profile launched before you called this API.
Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.
', 'DeleteTrialComponent' => 'Deletes the specified trial component. A trial component must be disassociated from all trials before the trial component can be deleted. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
', 'DeleteUserProfile' => 'Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
', 'DeleteWorkforce' => 'Use this operation to delete a workforce.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use this operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
If a private workforce contains one or more work teams, you must use the DeleteWorkteam operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse
error.
Deletes an existing work team. This operation can\'t be undone.
', 'DeregisterDevices' => 'Deregisters the specified devices. After you deregister a device, you will need to re-register the devices.
', 'DescribeAction' => 'Describes an action.
', 'DescribeAlgorithm' => 'Returns a description of the specified algorithm that is in your account.
', 'DescribeApp' => 'Describes the app.
', 'DescribeAppImageConfig' => 'Describes an AppImageConfig.
', 'DescribeArtifact' => 'Describes an artifact.
', 'DescribeAutoMLJob' => 'Returns information about an AutoML job created by calling CreateAutoMLJob.
AutoML jobs created by calling CreateAutoMLJobV2 cannot be described by DescribeAutoMLJob
.
Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob.
', 'DescribeCluster' => 'Retrieves information of a SageMaker HyperPod cluster.
', 'DescribeClusterNode' => 'Retrieves information of an instance (also called a node interchangeably) of a SageMaker HyperPod cluster.
', 'DescribeCodeRepository' => 'Gets details about the specified Git repository.
', 'DescribeCompilationJob' => 'Returns information about a model compilation job.
To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
', 'DescribeContext' => 'Describes a context.
', 'DescribeDataQualityJobDefinition' => 'Gets the details of a data quality monitoring job definition.
', 'DescribeDevice' => 'Describes the device.
', 'DescribeDeviceFleet' => 'A description of the fleet the device belongs to.
', 'DescribeDomain' => 'The description of the domain.
', 'DescribeEdgeDeploymentPlan' => 'Describes an edge deployment plan with deployment status per stage.
', 'DescribeEdgePackagingJob' => 'A description of edge packaging jobs.
', 'DescribeEndpoint' => 'Returns the description of an endpoint.
', 'DescribeEndpointConfig' => 'Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
Provides a list of an experiment\'s properties.
', 'DescribeFeatureGroup' => 'Use this operation to describe a FeatureGroup
. The response includes information on the creation time, FeatureGroup
name, the unique identifier for each FeatureGroup
, and more.
Shows the metadata for a feature within a feature group.
', 'DescribeFlowDefinition' => 'Returns information about the specified flow definition.
', 'DescribeHub' => 'Describe a hub.
Hub APIs are only callable through SageMaker Studio.
Describe the content of a hub.
Hub APIs are only callable through SageMaker Studio.
Returns information about the requested human task user interface (worker task template).
', 'DescribeHyperParameterTuningJob' => 'Returns a description of a hyperparameter tuning job, depending on the fields selected. These fields can include the name, Amazon Resource Name (ARN), job status of your tuning job and more.
', 'DescribeImage' => 'Describes a SageMaker image.
', 'DescribeImageVersion' => 'Describes a version of a SageMaker image.
', 'DescribeInferenceComponent' => 'Returns information about an inference component.
', 'DescribeInferenceExperiment' => 'Returns details about an inference experiment.
', 'DescribeInferenceRecommendationsJob' => 'Provides the results of the Inference Recommender job. One or more recommendation jobs are returned.
', 'DescribeLabelingJob' => 'Gets information about a labeling job.
', 'DescribeLineageGroup' => 'Provides a list of properties for the requested lineage group. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
', 'DescribeModel' => 'Describes a model that you created using the CreateModel
API.
Returns a description of a model bias job definition.
', 'DescribeModelCard' => 'Describes the content, creation time, and security configuration of an Amazon SageMaker Model Card.
', 'DescribeModelCardExportJob' => 'Describes an Amazon SageMaker Model Card export job.
', 'DescribeModelExplainabilityJobDefinition' => 'Returns a description of a model explainability job definition.
', 'DescribeModelPackage' => 'Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
To create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
', 'DescribeModelPackageGroup' => 'Gets a description for the specified model group.
', 'DescribeModelQualityJobDefinition' => 'Returns a description of a model quality job definition.
', 'DescribeMonitoringSchedule' => 'Describes the schedule for a monitoring job.
', 'DescribeNotebookInstance' => 'Returns information about a notebook instance.
', 'DescribeNotebookInstanceLifecycleConfig' => 'Returns a description of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'DescribePipeline' => 'Describes the details of a pipeline.
', 'DescribePipelineDefinitionForExecution' => 'Describes the details of an execution\'s pipeline definition.
', 'DescribePipelineExecution' => 'Describes the details of a pipeline execution.
', 'DescribeProcessingJob' => 'Returns a description of a processing job.
', 'DescribeProject' => 'Describes the details of a project.
', 'DescribeSpace' => 'Describes the space.
', 'DescribeStudioLifecycleConfig' => 'Describes the Amazon SageMaker Studio Lifecycle Configuration.
', 'DescribeSubscribedWorkteam' => 'Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the Amazon Web Services Marketplace.
', 'DescribeTrainingJob' => 'Returns information about a training job.
Some of the attributes below only appear if the training job successfully starts. If the training job fails, TrainingJobStatus
is Failed
and, depending on the FailureReason
, attributes like TrainingStartTime
, TrainingTimeInSeconds
, TrainingEndTime
, and BillableTimeInSeconds
may not be present in the response.
Returns information about a transform job.
', 'DescribeTrial' => 'Provides a list of a trial\'s properties.
', 'DescribeTrialComponent' => 'Provides a list of a trials component\'s properties.
', 'DescribeUserProfile' => 'Describes a user profile. For more information, see CreateUserProfile
.
Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team\'s Amazon Resource Name (ARN).
', 'DisableSagemakerServicecatalogPortfolio' => 'Disables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'DisassociateTrialComponent' => 'Disassociates a trial component from a trial. This doesn\'t effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API.
To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent
for the Resource
parameter. The list appears in the response under Results.TrialComponent.Parents
.
Enables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'GetDeviceFleetReport' => 'Describes a fleet.
', 'GetLineageGroupPolicy' => 'The resource policy for the lineage group.
', 'GetModelPackageGroupPolicy' => 'Gets a resource policy that manages access for a model group. For information about resource policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
', 'GetSagemakerServicecatalogPortfolioStatus' => 'Gets the status of Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'GetScalingConfigurationRecommendation' => 'Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.
', 'GetSearchSuggestions' => 'An auto-complete API for the search functionality in the SageMaker console. It returns suggestions of possible matches for the property name to use in Search
queries. Provides suggestions for HyperParameters
, Tags
, and Metrics
.
Import hub content.
Hub APIs are only callable through SageMaker Studio.
Lists the actions in your account and their properties.
', 'ListAlgorithms' => 'Lists the machine learning algorithms that have been created.
', 'ListAliases' => 'Lists the aliases of a specified image or image version.
', 'ListAppImageConfigs' => 'Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.
', 'ListApps' => 'Lists apps.
', 'ListArtifacts' => 'Lists the artifacts in your account and their properties.
', 'ListAssociations' => 'Lists the associations in your account and their properties.
', 'ListAutoMLJobs' => 'Request a list of jobs.
', 'ListCandidatesForAutoMLJob' => 'List the candidates created for the job.
', 'ListClusterNodes' => 'Retrieves the list of instances (also called nodes interchangeably) in a SageMaker HyperPod cluster.
', 'ListClusters' => 'Retrieves the list of SageMaker HyperPod clusters.
', 'ListCodeRepositories' => 'Gets a list of the Git repositories in your account.
', 'ListCompilationJobs' => 'Lists model compilation jobs that satisfy various filters.
To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
', 'ListContexts' => 'Lists the contexts in your account and their properties.
', 'ListDataQualityJobDefinitions' => 'Lists the data quality job definitions in your account.
', 'ListDeviceFleets' => 'Returns a list of devices in the fleet.
', 'ListDevices' => 'A list of devices.
', 'ListDomains' => 'Lists the domains.
', 'ListEdgeDeploymentPlans' => 'Lists all edge deployment plans.
', 'ListEdgePackagingJobs' => 'Returns a list of edge packaging jobs.
', 'ListEndpointConfigs' => 'Lists endpoint configurations.
', 'ListEndpoints' => 'Lists endpoints.
', 'ListExperiments' => 'Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
', 'ListFeatureGroups' => 'List FeatureGroup
s based on given filter and order.
Returns information about the flow definitions in your account.
', 'ListHubContentVersions' => 'List hub content versions.
Hub APIs are only callable through SageMaker Studio.
List the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
List all existing hubs.
Hub APIs are only callable through SageMaker Studio.
Returns information about the human task user interfaces in your account.
', 'ListHyperParameterTuningJobs' => 'Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
', 'ListImageVersions' => 'Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.
', 'ListImages' => 'Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.
', 'ListInferenceComponents' => 'Lists the inference components in your account and their properties.
', 'ListInferenceExperiments' => 'Returns the list of all inference experiments.
', 'ListInferenceRecommendationsJobSteps' => 'Returns a list of the subtasks for an Inference Recommender job.
The supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
', 'ListInferenceRecommendationsJobs' => 'Lists recommendation jobs that satisfy various filters.
', 'ListLabelingJobs' => 'Gets a list of labeling jobs.
', 'ListLabelingJobsForWorkteam' => 'Gets a list of labeling jobs assigned to a specified work team.
', 'ListLineageGroups' => 'A list of lineage groups shared with your Amazon Web Services account. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
', 'ListModelBiasJobDefinitions' => 'Lists model bias jobs definitions that satisfy various filters.
', 'ListModelCardExportJobs' => 'List the export jobs for the Amazon SageMaker Model Card.
', 'ListModelCardVersions' => 'List existing versions of an Amazon SageMaker Model Card.
', 'ListModelCards' => 'List existing model cards.
', 'ListModelExplainabilityJobDefinitions' => 'Lists model explainability job definitions that satisfy various filters.
', 'ListModelMetadata' => 'Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
', 'ListModelPackageGroups' => 'Gets a list of the model groups in your Amazon Web Services account.
', 'ListModelPackages' => 'Lists the model packages that have been created.
', 'ListModelQualityJobDefinitions' => 'Gets a list of model quality monitoring job definitions in your account.
', 'ListModels' => 'Lists models created with the CreateModel
API.
Gets a list of past alerts in a model monitoring schedule.
', 'ListMonitoringAlerts' => 'Gets the alerts for a single monitoring schedule.
', 'ListMonitoringExecutions' => 'Returns list of all monitoring job executions.
', 'ListMonitoringSchedules' => 'Returns list of all monitoring schedules.
', 'ListNotebookInstanceLifecycleConfigs' => 'Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
', 'ListNotebookInstances' => 'Returns a list of the SageMaker notebook instances in the requester\'s account in an Amazon Web Services Region.
', 'ListPipelineExecutionSteps' => 'Gets a list of PipeLineExecutionStep
objects.
Gets a list of the pipeline executions.
', 'ListPipelineParametersForExecution' => 'Gets a list of parameters for a pipeline execution.
', 'ListPipelines' => 'Gets a list of pipelines.
', 'ListProcessingJobs' => 'Lists processing jobs that satisfy various filters.
', 'ListProjects' => 'Gets a list of the projects in an Amazon Web Services account.
', 'ListResourceCatalogs' => ' Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of ResourceCatalog
s viewable is 1000.
Lists spaces.
', 'ListStageDevices' => 'Lists devices allocated to the stage, containing detailed device information and deployment status.
', 'ListStudioLifecycleConfigs' => 'Lists the Amazon SageMaker Studio Lifecycle Configurations in your Amazon Web Services Account.
', 'ListSubscribedWorkteams' => 'Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains
parameter.
Returns the tags for the specified SageMaker resource.
', 'ListTrainingJobs' => 'Lists training jobs.
When StatusEquals
and MaxResults
are set at the same time, the MaxResults
number of training jobs are first retrieved ignoring the StatusEquals
parameter and then they are filtered by the StatusEquals
parameter, which is returned as a response.
For example, if ListTrainingJobs
is invoked with the following parameters:
{ ... MaxResults: 100, StatusEquals: InProgress ... }
First, 100 trainings jobs with any status, including those other than InProgress
, are selected (sorted according to the creation time, from the most current to the oldest). Next, those with a status of InProgress
are returned.
You can quickly test the API using the following Amazon Web Services CLI code.
aws sagemaker list-training-jobs --max-results 100 --status-equals InProgress
Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
', 'ListTransformJobs' => 'Lists transform jobs.
', 'ListTrialComponents' => 'Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
ExperimentName
SourceArn
TrialName
Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
', 'ListUserProfiles' => 'Lists user profiles.
', 'ListWorkforces' => 'Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only have one private workforce per Amazon Web Services Region.
', 'ListWorkteams' => 'Gets a list of private work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains
parameter.
Adds a resouce policy to control access to a model group. For information about resoure policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
', 'QueryLineage' => 'Use this action to inspect your lineage and discover relationships between entities. For more information, see Querying Lineage Entities in the Amazon SageMaker Developer Guide.
', 'RegisterDevices' => 'Register devices.
', 'RenderUiTemplate' => 'Renders the UI template so that you can preview the worker\'s experience.
', 'RetryPipelineExecution' => 'Retry the execution of the pipeline.
', 'Search' => 'Finds SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord
objects in the response. You can sort the search results by any resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
The Search API may provide access to otherwise restricted data. See Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference for more information.
Notifies the pipeline that the execution of a callback step failed, along with a message describing why. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
', 'SendPipelineExecutionStepSuccess' => 'Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step\'s output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
', 'StartEdgeDeploymentStage' => 'Starts a stage in an edge deployment plan.
', 'StartInferenceExperiment' => 'Starts an inference experiment.
', 'StartMonitoringSchedule' => 'Starts a previously stopped monitoring schedule.
By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled
.
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker sets the notebook instance status to InService
. A notebook instance\'s status must be InService
before you can connect to your Jupyter notebook.
Starts a pipeline execution.
', 'StopAutoMLJob' => 'A method for forcing a running job to shut down.
', 'StopCompilationJob' => 'Stops a model compilation job.
To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn\'t stopped, it sends the SIGKILL signal.
When it receives a StopCompilationJob
request, Amazon SageMaker changes the CompilationJobStatus
of the job to Stopping
. After Amazon SageMaker stops the job, it sets the CompilationJobStatus
to Stopped
.
Stops a stage in an edge deployment plan.
', 'StopEdgePackagingJob' => 'Request to stop an edge packaging job.
', 'StopHyperParameterTuningJob' => 'Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped
state, it releases all reserved resources for the tuning job.
Stops an inference experiment.
', 'StopInferenceRecommendationsJob' => 'Stops an Inference Recommender job.
', 'StopLabelingJob' => 'Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
', 'StopMonitoringSchedule' => 'Stops a previously started monitoring schedule.
', 'StopNotebookInstance' => 'Terminates the ML compute instance. Before terminating the instance, SageMaker disconnects the ML storage volume from it. SageMaker preserves the ML storage volume. SageMaker stops charging you for the ML compute instance when you call StopNotebookInstance
.
To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance
API. StartNotebookInstance
launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.
Stops a pipeline execution.
Callback Step
A pipeline execution won\'t stop while a callback step is running. When you call StopPipelineExecution
on a pipeline execution with a running callback step, SageMaker Pipelines sends an additional Amazon SQS message to the specified SQS queue. The body of the SQS message contains a "Status" field which is set to "Stopping".
You should add logic to your Amazon SQS message consumer to take any needed action (for example, resource cleanup) upon receipt of the message followed by a call to SendPipelineExecutionStepSuccess
or SendPipelineExecutionStepFailure
.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
Lambda Step
A pipeline execution can\'t be stopped while a lambda step is running because the Lambda function invoked by the lambda step can\'t be stopped. If you attempt to stop the execution while the Lambda function is running, the pipeline waits for the Lambda function to finish or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function finishes, the pipeline execution status is Stopped
. If the timeout is hit the pipeline execution status is Failed
.
Stops a processing job.
', 'StopTrainingJob' => 'Stops a training job. To stop a job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost.
When it receives a StopTrainingJob
request, SageMaker changes the status of the job to Stopping
. After SageMaker stops the job, it sets the status to Stopped
.
Stops a batch transform job.
When Amazon SageMaker receives a StopTransformJob
request, the status of the job changes to Stopping
. After Amazon SageMaker stops the job, the status is set to Stopped
. When you stop a batch transform job before it is completed, Amazon SageMaker doesn\'t store the job\'s output in Amazon S3.
Updates an action.
', 'UpdateAppImageConfig' => 'Updates the properties of an AppImageConfig.
', 'UpdateArtifact' => 'Updates an artifact.
', 'UpdateCluster' => 'Update a SageMaker HyperPod cluster.
', 'UpdateCodeRepository' => 'Updates the specified Git repository with the specified values.
', 'UpdateContext' => 'Updates a context.
', 'UpdateDeviceFleet' => 'Updates a fleet of devices.
', 'UpdateDevices' => 'Updates one or more devices in a fleet.
', 'UpdateDomain' => 'Updates the default settings for new user profiles in the domain.
', 'UpdateEndpoint' => 'Deploys the new EndpointConfig
specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous EndpointConfig
(there is no availability loss).
When SageMaker receives the request, it sets the endpoint status to Updating
. After updating the endpoint, it sets the status to InService
. To check the status of an endpoint, use the DescribeEndpoint API.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig
.
If you delete the EndpointConfig
of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, SageMaker sets the endpoint status to Updating
. After updating the endpoint, it sets the status to InService
. To check the status of an endpoint, use the DescribeEndpoint API.
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
', 'UpdateFeatureGroup' => 'Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the UpdateFeatureGroup
API.
You can add features for your feature group using the FeatureAdditions
request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the OnlineStoreConfig
request parameter. If a TtlDuration
is specified, the default TtlDuration
applies for all records added to the feature group after the feature group is updated. If a record level TtlDuration
exists from using the PutRecord
API, the record level TtlDuration
applies to that record instead of the default TtlDuration
.
Updates the description and parameters of the feature group.
', 'UpdateHub' => 'Update a hub.
Hub APIs are only callable through SageMaker Studio.
Updates the properties of a SageMaker image. To change the image\'s tags, use the AddTags and DeleteTags APIs.
', 'UpdateImageVersion' => 'Updates the properties of a SageMaker image version.
', 'UpdateInferenceComponent' => 'Updates an inference component.
', 'UpdateInferenceComponentRuntimeConfig' => 'Runtime settings for a model that is deployed with an inference component.
', 'UpdateInferenceExperiment' => ' Updates an inference experiment that you created. The status of the inference experiment has to be either Created
, Running
. For more information on the status of an inference experiment, see DescribeInferenceExperiment.
Update an Amazon SageMaker Model Card.
You cannot update both model card content and model card status in a single call.
Updates a versioned model.
', 'UpdateMonitoringAlert' => 'Update the parameters of a model monitor alert.
', 'UpdateMonitoringSchedule' => 'Updates a previously created schedule.
', 'UpdateNotebookInstance' => 'Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
', 'UpdateNotebookInstanceLifecycleConfig' => 'Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
', 'UpdatePipeline' => 'Updates a pipeline.
', 'UpdatePipelineExecution' => 'Updates a pipeline execution.
', 'UpdateProject' => 'Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
You must not update a project that is in use. If you update the ServiceCatalogProvisioningUpdateDetails
of a project that is active or being created, or updated, you may lose resources already created by the project.
Updates the settings of a space.
', 'UpdateTrainingJob' => 'Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.
', 'UpdateTrial' => 'Updates the display name of a trial.
', 'UpdateTrialComponent' => 'Updates one or more properties of a trial component.
', 'UpdateUserProfile' => 'Updates a user profile.
', 'UpdateWorkforce' => 'Use this operation to update your workforce. You can use this operation to require that workers use specific IP addresses to work on tasks and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.
The worker portal is now supported in VPC and public internet.
Use SourceIpConfig
to restrict worker access to tasks to a specific range of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs. By default, a workforce isn\'t restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied and get a Not Found
error message on the worker portal.
To restrict access to all the workers in public internet, add the SourceIpConfig
CIDR value as "10.0.0.0/16".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
Use OidcConfig
to update the configuration of a workforce created using your own OIDC IdP.
You can only update your OIDC IdP configuration when there are no work teams associated with your workforce. You can delete work teams using the DeleteWorkteam operation.
After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you can view details about your update workforce using the DescribeWorkforce operation.
This operation only applies to private workforces.
Updates an existing work team with new member definitions or description.
', ], 'shapes' => [ 'Accept' => [ 'base' => NULL, 'refs' => [ 'TransformOutput$Accept' => 'The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
', ], ], 'AcceptEula' => [ 'base' => NULL, 'refs' => [ 'ModelAccessConfig$AcceptEula' => 'Specifies agreement to the model end-user license agreement (EULA). The AcceptEula
value must be explicitly defined as True
in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The Amazon Web Services account ID of the account used to start the labeling job.
', 'VpcOnlyTrustedAccounts$member' => NULL, ], ], 'ActionArn' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'CreateActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'DeleteActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'DescribeActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'UpdateActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', ], ], 'ActionSource' => [ 'base' => 'A structure describing the source of an action.
', 'refs' => [ 'ActionSummary$Source' => 'The source of the action.
', 'CreateActionRequest$Source' => 'The source type, ID, and URI.
', 'DescribeActionResponse$Source' => 'The source of the action.
', ], ], 'ActionStatus' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$Status' => 'The status of the action.
', 'CreateActionRequest$Status' => 'The status of the action.
', 'DescribeActionResponse$Status' => 'The status of the action.
', 'UpdateActionRequest$Status' => 'The new status for the action.
', ], ], 'ActionSummaries' => [ 'base' => NULL, 'refs' => [ 'ListActionsResponse$ActionSummaries' => 'A list of actions and their properties.
', ], ], 'ActionSummary' => [ 'base' => 'Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.
', 'refs' => [ 'ActionSummaries$member' => NULL, ], ], 'AddAssociationRequest' => [ 'base' => NULL, 'refs' => [], ], 'AddAssociationResponse' => [ 'base' => NULL, 'refs' => [], ], 'AddTagsInput' => [ 'base' => NULL, 'refs' => [], ], 'AddTagsOutput' => [ 'base' => NULL, 'refs' => [], ], 'AdditionalCodeRepositoryNamesOrUrls' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$AdditionalCodeRepositories' => 'An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'DescribeNotebookInstanceOutput$AdditionalCodeRepositories' => 'An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'NotebookInstanceSummary$AdditionalCodeRepositories' => 'An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'UpdateNotebookInstanceInput$AdditionalCodeRepositories' => 'An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', ], ], 'AdditionalInferenceSpecificationDefinition' => [ 'base' => 'A structure of additional Inference Specification. Additional Inference Specification specifies details about inference jobs that can be run with models based on this model package
', 'refs' => [ 'AdditionalInferenceSpecifications$member' => NULL, ], ], 'AdditionalInferenceSpecifications' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', 'DescribeModelPackageOutput$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', 'ModelPackage$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects.
', 'UpdateModelPackageInput$AdditionalInferenceSpecificationsToAdd' => 'An array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', ], ], 'AdditionalS3DataSource' => [ 'base' => 'A data source used for training or inference that is in addition to the input dataset or model data.
', 'refs' => [ 'ModelPackageContainerDefinition$AdditionalS3DataSource' => 'The additional data source that is used during inference in the Docker container for your model package.
', 'TrainingSpecification$AdditionalS3DataSource' => 'The additional data source used during the training job.
', ], ], 'AdditionalS3DataSourceDataType' => [ 'base' => NULL, 'refs' => [ 'AdditionalS3DataSource$S3DataType' => 'The data type of the additional data source that you specify for use in inference or training.
', ], ], 'AgentVersion' => [ 'base' => 'Edge Manager agent version.
', 'refs' => [ 'AgentVersions$member' => NULL, ], ], 'AgentVersions' => [ 'base' => NULL, 'refs' => [ 'GetDeviceFleetReportResponse$AgentVersions' => 'The versions of Edge Manager agent deployed on the fleet.
', ], ], 'AggregationTransformationValue' => [ 'base' => NULL, 'refs' => [ 'AggregationTransformations$value' => NULL, ], ], 'AggregationTransformations' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesTransformations$Aggregation' => 'A key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.
The supported aggregation methods are sum
(default), avg
, first
, min
, max
.
Aggregation is only supported for the target column.
An Amazon CloudWatch alarm configured to monitor metrics on an endpoint.
', 'refs' => [ 'AlarmList$member' => NULL, ], ], 'AlarmList' => [ 'base' => NULL, 'refs' => [ 'AutoRollbackConfig$Alarms' => 'List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.
', ], ], 'AlarmName' => [ 'base' => NULL, 'refs' => [ 'Alarm$AlarmName' => 'The name of a CloudWatch alarm in your account.
', ], ], 'AlgorithmArn' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the algorithm.
', 'CreateAlgorithmOutput$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the new algorithm.
', 'DescribeAlgorithmOutput$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the algorithm.
', ], ], 'AlgorithmImage' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$TrainingImage' => 'The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information about using your custom training container, see Using Your Own Algorithms with Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName
parameter or the image URI of the algorithm container to the TrainingImage
parameter.
For more information, see the note in the AlgorithmName
parameter description.
The Amazon Elastic Container (ECR) Image for the managed rule evaluation.
', 'HyperParameterAlgorithmSpecification$TrainingImage' => ' The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. SageMaker supports both registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The Amazon Elastic Container Registry Image for the managed rule evaluation.
', ], ], 'AlgorithmSortBy' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsInput$SortBy' => 'The parameter by which to sort the results. The default is CreationTime
.
Specifies the training algorithm to use in a CreateTrainingJob request.
For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
', 'refs' => [ 'CreateTrainingJobRequest$AlgorithmSpecification' => 'The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about providing your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
', 'DescribeTrainingJobResponse$AlgorithmSpecification' => 'Information about the algorithm used for training, and algorithm metadata.
', 'TrainingJob$AlgorithmSpecification' => 'Information about the algorithm used for training, and algorithm metadata.
', ], ], 'AlgorithmStatus' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$AlgorithmStatus' => 'The overall status of the algorithm.
', 'DescribeAlgorithmOutput$AlgorithmStatus' => 'The current status of the algorithm.
', ], ], 'AlgorithmStatusDetails' => [ 'base' => 'Specifies the validation and image scan statuses of the algorithm.
', 'refs' => [ 'DescribeAlgorithmOutput$AlgorithmStatusDetails' => 'Details about the current status of the algorithm.
', ], ], 'AlgorithmStatusItem' => [ 'base' => 'Represents the overall status of an algorithm.
', 'refs' => [ 'AlgorithmStatusItemList$member' => NULL, ], ], 'AlgorithmStatusItemList' => [ 'base' => NULL, 'refs' => [ 'AlgorithmStatusDetails$ValidationStatuses' => 'The status of algorithm validation.
', 'AlgorithmStatusDetails$ImageScanStatuses' => 'The status of the scan of the algorithm\'s Docker image container.
', ], ], 'AlgorithmSummary' => [ 'base' => 'Provides summary information about an algorithm.
', 'refs' => [ 'AlgorithmSummaryList$member' => NULL, ], ], 'AlgorithmSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsOutput$AlgorithmSummaryList' => '>An array of AlgorithmSummary
objects, each of which lists an algorithm.
Defines a training job and a batch transform job that SageMaker runs to validate your algorithm.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
', 'refs' => [ 'AlgorithmValidationProfiles$member' => NULL, ], ], 'AlgorithmValidationProfiles' => [ 'base' => NULL, 'refs' => [ 'AlgorithmValidationSpecification$ValidationProfiles' => 'An array of AlgorithmValidationProfile
objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm.
Specifies configurations for one or more training jobs that SageMaker runs to test the algorithm.
', 'refs' => [ 'CreateAlgorithmInput$ValidationSpecification' => 'Specifies configurations for one or more training jobs and that SageMaker runs to test the algorithm\'s training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm\'s inference code.
', 'DescribeAlgorithmOutput$ValidationSpecification' => 'Details about configurations for one or more training jobs that SageMaker runs to test the algorithm.
', ], ], 'AnnotationConsolidationConfig' => [ 'base' => 'Configures how labels are consolidated across human workers and processes output data.
', 'refs' => [ 'HumanTaskConfig$AnnotationConsolidationConfig' => 'Configures how labels are consolidated across human workers.
', ], ], 'AppArn' => [ 'base' => NULL, 'refs' => [ 'CreateAppResponse$AppArn' => 'The Amazon Resource Name (ARN) of the app.
', 'DescribeAppResponse$AppArn' => 'The Amazon Resource Name (ARN) of the app.
', ], ], 'AppDetails' => [ 'base' => 'Details about an Amazon SageMaker app.
', 'refs' => [ 'AppList$member' => NULL, ], ], 'AppImageConfigArn' => [ 'base' => NULL, 'refs' => [ 'AppImageConfigDetails$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'CreateAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'DescribeAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'UpdateAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) for the AppImageConfig.
', ], ], 'AppImageConfigDetails' => [ 'base' => 'The configuration for running a SageMaker image as a KernelGateway app.
', 'refs' => [ 'AppImageConfigList$member' => NULL, ], ], 'AppImageConfigList' => [ 'base' => NULL, 'refs' => [ 'ListAppImageConfigsResponse$AppImageConfigs' => 'A list of AppImageConfigs and their properties.
', ], ], 'AppImageConfigName' => [ 'base' => NULL, 'refs' => [ 'AppImageConfigDetails$AppImageConfigName' => 'The name of the AppImageConfig. Must be unique to your account.
', 'CreateAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig. Must be unique to your account.
', 'CustomImage$AppImageConfigName' => 'The name of the AppImageConfig.
', 'DeleteAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to delete.
', 'DescribeAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to describe.
', 'DescribeAppImageConfigResponse$AppImageConfigName' => 'The name of the AppImageConfig.
', 'ListAppImageConfigsRequest$NameContains' => 'A filter that returns only AppImageConfigs whose name contains the specified string.
', 'UpdateAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to update.
', ], ], 'AppImageConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListAppImageConfigsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime
.
The instance type that the image version runs on.
JupyterServer apps only support the system
value.
For KernelGateway apps, the system
value is translated to ml.t3.medium
. KernelGateway apps also support all other values for available instance types.
The list of apps.
', ], ], 'AppManaged' => [ 'base' => NULL, 'refs' => [ 'ProcessingInput$AppManaged' => 'When True
, input operations such as data download are managed natively by the processing job application. When False
(default), input operations are managed by Amazon SageMaker.
When True
, output operations such as data upload are managed natively by the processing job application. When False
(default), output operations are managed by Amazon SageMaker.
The name of the app.
', 'CreateAppRequest$AppName' => 'The name of the app.
', 'DeleteAppRequest$AppName' => 'The name of the app.
', 'DescribeAppRequest$AppName' => 'The name of the app.
', 'DescribeAppResponse$AppName' => 'The name of the app.
', ], ], 'AppNetworkAccessType' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$AppNetworkAccessType' => 'Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly
.
PublicInternetOnly
- Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly
- All traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly
.
PublicInternetOnly
- Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly
- All traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic.
PublicInternetOnly
- Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access.
VpcOnly
- All Studio traffic is through the specified VPC and subnets.
This configuration can only be modified if there are no apps in the InService
, Pending
, or Deleting
state. The configuration cannot be updated if DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is already set or DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided as part of the same request.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly
mode. Required when CreateDomain.AppNetworkAccessType
is VPCOnly
and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided. If setting up the domain for use with RStudio, this value must be set to Service
.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly
mode. Required when CreateDomain.AppNetworkAccessType
is VPCOnly
and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly
mode. Required when CreateDomain.AppNetworkAccessType
is VPCOnly
and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided. If setting up the domain for use with RStudio, this value must be set to Service
.
The parameter by which to sort the results. The default is CreationTime.
', ], ], 'AppSpecification' => [ 'base' => 'Configuration to run a processing job in a specified container image.
', 'refs' => [ 'CreateProcessingJobRequest$AppSpecification' => 'Configures the processing job to run a specified Docker container image.
', 'DescribeProcessingJobResponse$AppSpecification' => 'Configures the processing job to run a specified container image.
', 'ProcessingJob$AppSpecification' => NULL, ], ], 'AppStatus' => [ 'base' => NULL, 'refs' => [ 'AppDetails$Status' => 'The status.
', 'DescribeAppResponse$Status' => 'The status.
', ], ], 'AppType' => [ 'base' => NULL, 'refs' => [ 'AppDetails$AppType' => 'The type of app.
', 'CreateAppRequest$AppType' => 'The type of app.
', 'DeleteAppRequest$AppType' => 'The type of app.
', 'DescribeAppRequest$AppType' => 'The type of app.
', 'DescribeAppResponse$AppType' => 'The type of app.
', 'SpaceSettings$AppType' => 'The type of app created within the space.
', 'SpaceSettingsSummary$AppType' => 'The type of app created within the space.
', ], ], 'ApprovalDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeModelPackageOutput$ApprovalDescription' => 'A description provided for the model approval.
', 'ModelPackage$ApprovalDescription' => 'A description provided when the model approval is set.
', 'UpdateModelPackageInput$ApprovalDescription' => 'A description for the approval status of the model.
', ], ], 'ArnOrName' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$AlgorithmName' => 'The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the AlgorithmName
parameter or the image URI of the algorithm container to the TrainingImage
parameter.
Note that the AlgorithmName
parameter is mutually exclusive with the TrainingImage
parameter. If you specify a value for the AlgorithmName
parameter, you can\'t specify a value for TrainingImage
, and vice versa.
If you specify values for both parameters, the training job might break; if you don\'t specify any value for both parameters, the training job might raise a null
error.
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
', 'DeleteModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group to delete.
', 'DescribeAlgorithmInput$AlgorithmName' => 'The name of the algorithm to describe.
', 'DescribeModelPackageGroupInput$ModelPackageGroupName' => 'The name of gthe model group to describe.
', 'HyperParameterAlgorithmSpecification$AlgorithmName' => 'The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage
.
A filter that returns only model versions that belong to the specified model group.
', 'SourceAlgorithm$AlgorithmName' => 'The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
', ], ], 'ArtifactArn' => [ 'base' => NULL, 'refs' => [ 'ArtifactSummary$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'CreateArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'DeleteArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to delete.
', 'DeleteArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'DescribeArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to describe.
', 'DescribeArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'UpdateArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to update.
', 'UpdateArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', ], ], 'ArtifactDigest' => [ 'base' => NULL, 'refs' => [ 'ModelDigests$ArtifactDigest' => 'Provides a hash value that uniquely identifies the stored model artifacts.
', ], ], 'ArtifactProperties' => [ 'base' => NULL, 'refs' => [ 'CreateArtifactRequest$Properties' => 'A list of properties to add to the artifact.
', 'UpdateArtifactRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', ], ], 'ArtifactPropertyValue' => [ 'base' => NULL, 'refs' => [ 'ArtifactProperties$value' => NULL, ], ], 'ArtifactSource' => [ 'base' => 'A structure describing the source of an artifact.
', 'refs' => [ 'ArtifactSummary$Source' => 'The source of the artifact.
', 'CreateArtifactRequest$Source' => 'The ID, ID type, and URI of the source.
', 'DeleteArtifactRequest$Source' => 'The URI of the source.
', 'DescribeArtifactResponse$Source' => 'The source of the artifact.
', ], ], 'ArtifactSourceIdType' => [ 'base' => NULL, 'refs' => [ 'ArtifactSourceType$SourceIdType' => 'The type of ID.
', ], ], 'ArtifactSourceType' => [ 'base' => 'The ID and ID type of an artifact source.
', 'refs' => [ 'ArtifactSourceTypes$member' => NULL, ], ], 'ArtifactSourceTypes' => [ 'base' => NULL, 'refs' => [ 'ArtifactSource$SourceTypes' => 'A list of source types.
', ], ], 'ArtifactSummaries' => [ 'base' => NULL, 'refs' => [ 'ListArtifactsResponse$ArtifactSummaries' => 'A list of artifacts and their properties.
', ], ], 'ArtifactSummary' => [ 'base' => 'Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.
', 'refs' => [ 'ArtifactSummaries$member' => NULL, ], ], 'AssemblyType' => [ 'base' => NULL, 'refs' => [ 'TransformOutput$AssembleWith' => 'Defines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None
. To add a newline character at the end of every transformed record, specify Line
.
The type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.
ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.
AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.
DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.
Produced - The source generated the destination. For example, a training job produced a model artifact.
The type of the association.
', 'Edge$AssociationType' => 'The type of the Association(Edge) between the source and destination. For example ContributedTo
, Produced
, or DerivedFrom
.
A filter that returns only associations of the specified type.
', ], ], 'AssociationEntityArn' => [ 'base' => NULL, 'refs' => [ 'AddAssociationRequest$SourceArn' => 'The ARN of the source.
', 'AddAssociationRequest$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'AddAssociationResponse$SourceArn' => 'The ARN of the source.
', 'AddAssociationResponse$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'AssociationSummary$SourceArn' => 'The ARN of the source.
', 'AssociationSummary$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'DeleteAssociationRequest$SourceArn' => 'The ARN of the source.
', 'DeleteAssociationRequest$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'DeleteAssociationResponse$SourceArn' => 'The ARN of the source.
', 'DeleteAssociationResponse$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'Edge$SourceArn' => 'The Amazon Resource Name (ARN) of the source lineage entity of the directed edge.
', 'Edge$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination lineage entity of the directed edge.
', 'ListAssociationsRequest$SourceArn' => 'A filter that returns only associations with the specified source ARN.
', 'ListAssociationsRequest$DestinationArn' => 'A filter that returns only associations with the specified destination Amazon Resource Name (ARN).
', 'QueryLineageStartArns$member' => NULL, 'Vertex$Arn' => 'The Amazon Resource Name (ARN) of the lineage entity resource.
', ], ], 'AssociationSummaries' => [ 'base' => NULL, 'refs' => [ 'ListAssociationsResponse$AssociationSummaries' => 'A list of associations and their properties.
', ], ], 'AssociationSummary' => [ 'base' => 'Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.
', 'refs' => [ 'AssociationSummaries$member' => NULL, ], ], 'AsyncInferenceClientConfig' => [ 'base' => 'Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
', 'refs' => [ 'AsyncInferenceConfig$ClientConfig' => 'Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
', ], ], 'AsyncInferenceConfig' => [ 'base' => 'Specifies configuration for how an endpoint performs asynchronous inference.
', 'refs' => [ 'CreateEndpointConfigInput$AsyncInferenceConfig' => 'Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
', 'DescribeEndpointConfigOutput$AsyncInferenceConfig' => 'Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
Specifies the configuration for notifications of inference results for asynchronous inference.
', 'refs' => [ 'AsyncInferenceOutputConfig$NotificationConfig' => 'Specifies the configuration for notifications of inference results for asynchronous inference.
', ], ], 'AsyncInferenceOutputConfig' => [ 'base' => 'Specifies the configuration for asynchronous inference invocation outputs.
', 'refs' => [ 'AsyncInferenceConfig$OutputConfig' => 'Specifies the configuration for asynchronous inference invocation outputs.
', ], ], 'AsyncNotificationTopicTypeList' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceNotificationConfig$IncludeInferenceResponseIn' => 'The Amazon SNS topics where you want the inference response to be included.
The inference response is included only if the response size is less than or equal to 128 KB.
The name of the data catalog used in Athena query execution.
', 'refs' => [ 'AthenaDatasetDefinition$Catalog' => NULL, ], ], 'AthenaDatabase' => [ 'base' => 'The name of the database used in the Athena query execution.
', 'refs' => [ 'AthenaDatasetDefinition$Database' => NULL, ], ], 'AthenaDatasetDefinition' => [ 'base' => 'Configuration for Athena Dataset Definition input.
', 'refs' => [ 'DatasetDefinition$AthenaDatasetDefinition' => NULL, ], ], 'AthenaQueryString' => [ 'base' => 'The SQL query statements, to be executed.
', 'refs' => [ 'AthenaDatasetDefinition$QueryString' => NULL, ], ], 'AthenaResultCompressionType' => [ 'base' => 'The compression used for Athena query results.
', 'refs' => [ 'AthenaDatasetDefinition$OutputCompression' => NULL, ], ], 'AthenaResultFormat' => [ 'base' => 'The data storage format for Athena query results.
', 'refs' => [ 'AthenaDatasetDefinition$OutputFormat' => NULL, ], ], 'AthenaWorkGroup' => [ 'base' => 'The name of the workgroup in which the Athena query is being started.
', 'refs' => [ 'AthenaDatasetDefinition$WorkGroup' => NULL, ], ], 'AttributeName' => [ 'base' => NULL, 'refs' => [ 'AttributeNames$member' => NULL, ], ], 'AttributeNames' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$AttributeNames' => 'A list of one or more attribute names to use that are found in a specified augmented manifest file.
', ], ], 'AuthMode' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$AuthMode' => 'The mode of authentication that members use to access the domain.
', 'DescribeDomainResponse$AuthMode' => 'The domain\'s authentication mode.
', ], ], 'AutoGenerateEndpointName' => [ 'base' => NULL, 'refs' => [ 'ModelDeployConfig$AutoGenerateEndpointName' => 'Set to True
to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False
otherwise. The default value is False
.
If you set AutoGenerateEndpointName
to True
, do not specify the EndpointName
; otherwise a 400 error is thrown.
The collection of algorithms run on a dataset for training the model candidates of an Autopilot job.
', 'refs' => [ 'AutoMLAlgorithmsConfig$member' => NULL, ], ], 'AutoMLAlgorithms' => [ 'base' => NULL, 'refs' => [ 'AutoMLAlgorithmConfig$AutoMLAlgorithms' => 'The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (ENSEMBLING
or HYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.
In ENSEMBLING
mode:
"catboost"
"extra-trees"
"fastai"
"lightgbm"
"linear-learner"
"nn-torch"
"randomforest"
"xgboost"
In HYPERPARAMETER_TUNING
mode:
"linear-learner"
"mlp"
"xgboost"
Stores the configuration information for the selection of algorithms used to train the model candidates.
The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode
.
AlgorithmsConfig
should not be set in AUTO
training mode.
When AlgorithmsConfig
is provided, one AutoMLAlgorithms
attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms
is empty, AutoMLCandidateGenerationConfig
uses the full set of algorithms for the given training mode.
When AlgorithmsConfig
is not provided, AutoMLCandidateGenerationConfig
uses the full set of algorithms for the given training mode.
For the list of all algorithms per training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
', 'CandidateGenerationConfig$AlgorithmsConfig' => 'Stores the configuration information for the selection of algorithms used to train model candidates on tabular data.
The list of available algorithms to choose from depends on the training mode set in TabularJobConfig.Mode
.
AlgorithmsConfig
should not be set in AUTO
training mode.
When AlgorithmsConfig
is provided, one AutoMLAlgorithms
attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms
is empty, CandidateGenerationConfig
uses the full set of algorithms for the given training mode.
When AlgorithmsConfig
is not provided, CandidateGenerationConfig
uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
', ], ], 'AutoMLCandidate' => [ 'base' => 'Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.
', 'refs' => [ 'AutoMLCandidates$member' => NULL, 'DescribeAutoMLJobResponse$BestCandidate' => 'The best model candidate selected by SageMaker Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.
', 'DescribeAutoMLJobV2Response$BestCandidate' => 'Information about the candidate produced by an AutoML training job V2, including its status, steps, and other properties.
', ], ], 'AutoMLCandidateGenerationConfig' => [ 'base' => 'Stores the configuration information for how a candidate is generated (optional).
', 'refs' => [ 'AutoMLJobConfig$CandidateGenerationConfig' => 'The configuration for generating a candidate for an AutoML job (optional).
', ], ], 'AutoMLCandidateStep' => [ 'base' => 'Information about the steps for a candidate and what step it is working on.
', 'refs' => [ 'CandidateSteps$member' => NULL, ], ], 'AutoMLCandidates' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobResponse$Candidates' => 'Summaries about the AutoMLCandidates
.
A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.
A validation dataset must contain the same headers as the training dataset.
The channel type (optional) is an enum
string. The default value is training
. Channels for training and validation must share the same ContentType
and TargetAttributeName
. For information on specifying training and validation channel types, see How to specify training and validation datasets.
The type of channel. Defines whether the data are used for training or validation. The default value is training
. Channels for training
and validation
must share the same ContentType
The type of channel defaults to training
for the time-series forecasting problem type.
A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see ContainerDefinition.
', 'refs' => [ 'AutoMLContainerDefinitions$member' => NULL, ], ], 'AutoMLContainerDefinitions' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$InferenceContainers' => 'Information about the recommended inference container definitions.
', 'AutoMLInferenceContainerDefinitions$value' => 'Information about the recommended inference container definitions.
', ], ], 'AutoMLDataSource' => [ 'base' => 'The data source for the Autopilot job.
', 'refs' => [ 'AutoMLChannel$DataSource' => 'The data source for an AutoML channel.
', 'AutoMLJobChannel$DataSource' => 'The data source for an AutoML channel (Required).
', ], ], 'AutoMLDataSplitConfig' => [ 'base' => 'This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob
, the validation dataset must be less than 2 GB in size.
The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
', 'CreateAutoMLJobV2Request$DataSplitConfig' => 'This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob
, the validation dataset must be less than 2 GB in size.
This attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.
Returns the configuration settings of how the data are split into train and validation datasets.
', ], ], 'AutoMLFailureReason' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$FailureReason' => 'The failure reason.
', 'AutoMLJobSummary$FailureReason' => 'The failure reason of an AutoML job.
', 'AutoMLPartialFailureReason$PartialFailureMessage' => 'The message containing the reason for a partial failure of an AutoML job.
', 'DescribeAutoMLJobResponse$FailureReason' => 'Returns the failure reason for an AutoML job, when applicable.
', 'DescribeAutoMLJobV2Response$FailureReason' => 'Returns the reason for the failure of the AutoML job V2, when applicable.
', ], ], 'AutoMLInferenceContainerDefinitions' => [ 'base' => 'The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the V2 API only (for example, for jobs created by calling CreateAutoMLJobV2
).
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the AutoML jobs V2 (for example, for jobs created by calling CreateAutoMLJobV2
) related to image or text classification problem types only.
An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig
supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.
Returns the input data configuration for the AutoML job.
', ], ], 'AutoMLJobArn' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the AutoML job.
', 'AutoMLJobSummary$AutoMLJobArn' => 'The ARN of the AutoML job.
', 'CreateAutoMLJobResponse$AutoMLJobArn' => 'The unique ARN assigned to the AutoML job when it is created.
', 'CreateAutoMLJobV2Response$AutoMLJobArn' => 'The unique ARN assigned to the AutoMLJob when it is created.
', 'DescribeAutoMLJobResponse$AutoMLJobArn' => 'Returns the ARN of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobArn' => 'Returns the Amazon Resource Name (ARN) of the AutoML job V2.
', 'DescribeProcessingJobResponse$AutoMLJobArn' => 'The ARN of an AutoML job associated with this processing job.
', 'DescribeTrainingJobResponse$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of an AutoML job.
', 'DescribeTransformJobResponse$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML transform job.
', 'ProcessingJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.
', 'TrainingJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the job.
', 'TransformJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML job that created the transform job.
', ], ], 'AutoMLJobArtifacts' => [ 'base' => 'The artifacts that are generated during an AutoML job.
', 'refs' => [ 'DescribeAutoMLJobResponse$AutoMLJobArtifacts' => 'Returns information on the job\'s artifacts found in AutoMLJobArtifacts
.
A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
', 'refs' => [ 'AutoMLJobInputDataConfig$member' => NULL, ], ], 'AutoMLJobCompletionCriteria' => [ 'base' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'refs' => [ 'AutoMLJobConfig$CompletionCriteria' => 'How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
', 'AutoMLResolvedAttributes$CompletionCriteria' => NULL, 'ImageClassificationJobConfig$CompletionCriteria' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'ResolvedAttributes$CompletionCriteria' => NULL, 'TabularJobConfig$CompletionCriteria' => NULL, 'TextClassificationJobConfig$CompletionCriteria' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'TextGenerationJobConfig$CompletionCriteria' => 'How long a fine-tuning job is allowed to run. For TextGenerationJobConfig
problem types, the MaxRuntimePerTrainingJobInSeconds
attribute of AutoMLJobCompletionCriteria
defaults to 72h (259200s).
A collection of settings used for an AutoML job.
', 'refs' => [ 'CreateAutoMLJobRequest$AutoMLJobConfig' => 'A collection of settings used to configure an AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobConfig' => 'Returns the configuration for the AutoML job.
', ], ], 'AutoMLJobInputDataConfig' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobV2Request$AutoMLJobInputDataConfig' => 'An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob
input parameters. The supported formats depend on the problem type:
For tabular problem types: S3Prefix
, ManifestFile
.
For image classification: S3Prefix
, ManifestFile
, AugmentedManifestFile
.
For text classification: S3Prefix
.
For time-series forecasting: S3Prefix
.
For text generation (LLMs fine-tuning): S3Prefix
.
Returns an array of channel objects describing the input data and their location.
', ], ], 'AutoMLJobName' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobName' => 'The name of the AutoML job you are requesting.
', 'CreateAutoMLJobRequest$AutoMLJobName' => 'Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
', 'CreateAutoMLJobV2Request$AutoMLJobName' => 'Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
', 'DescribeAutoMLJobRequest$AutoMLJobName' => 'Requests information about an AutoML job using its unique name.
', 'DescribeAutoMLJobResponse$AutoMLJobName' => 'Returns the name of the AutoML job.
', 'DescribeAutoMLJobV2Request$AutoMLJobName' => 'Requests information about an AutoML job V2 using its unique name.
', 'DescribeAutoMLJobV2Response$AutoMLJobName' => 'Returns the name of the AutoML job V2.
', 'ListCandidatesForAutoMLJobRequest$AutoMLJobName' => 'List the candidates created for the job by providing the job\'s name.
', 'StopAutoMLJobRequest$AutoMLJobName' => 'The name of the object you are requesting.
', ], ], 'AutoMLJobObjective' => [ 'base' => 'Specifies a metric to minimize or maximize as the objective of an AutoML job.
', 'refs' => [ 'AutoMLResolvedAttributes$AutoMLJobObjective' => NULL, 'CreateAutoMLJobRequest$AutoMLJobObjective' => 'Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
', 'CreateAutoMLJobV2Request$AutoMLJobObjective' => 'Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.
For tabular problem types: You must either provide both the AutoMLJobObjective
and indicate the type of supervised learning problem in AutoMLProblemTypeConfig
(TabularJobConfig.ProblemType
), or none at all.
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective
field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
Returns the job\'s objective.
', 'DescribeAutoMLJobV2Response$AutoMLJobObjective' => 'Returns the job\'s objective.
', 'ResolvedAttributes$AutoMLJobObjective' => NULL, ], ], 'AutoMLJobObjectiveType' => [ 'base' => NULL, 'refs' => [ 'FinalAutoMLJobObjectiveMetric$Type' => 'The type of metric with the best result.
', ], ], 'AutoMLJobSecondaryStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobSecondaryStatus' => 'The secondary status of the AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobSecondaryStatus' => 'Returns the secondary status of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobSecondaryStatus' => 'Returns the secondary status of the AutoML job V2.
', ], ], 'AutoMLJobStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobStatus' => 'The status of the AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobStatus' => 'Returns the status of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobStatus' => 'Returns the status of the AutoML job V2.
', 'ListAutoMLJobsRequest$StatusEquals' => 'Request a list of jobs, using a filter for status.
', ], ], 'AutoMLJobStepMetadata' => [ 'base' => 'Metadata for an AutoML job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$AutoMLJob' => 'The Amazon Resource Name (ARN) of the AutoML job that was run by this step.
', ], ], 'AutoMLJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsResponse$AutoMLJobSummaries' => 'Returns a summary list of jobs.
', ], ], 'AutoMLJobSummary' => [ 'base' => 'Provides a summary about an AutoML job.
', 'refs' => [ 'AutoMLJobSummaries$member' => NULL, ], ], 'AutoMLMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsRequest$MaxResults' => 'Request a list of jobs up to a specified limit.
', ], ], 'AutoMLMaxResultsForTrials' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobRequest$MaxResults' => 'List the job\'s candidates up to a specified limit.
', ], ], 'AutoMLMetricEnum' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobObjective$MetricName' => 'The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model\'s parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.
The list of available metrics supported by Autopilot and the default metric applied when you do not specify a metric name explicitly depend on the problem type.
For tabular problem types:
List of available metrics:
Regression: InferenceLatency
, MAE
, MSE
, R2
, RMSE
Binary classification: Accuracy
, AUC
, BalancedAccuracy
, F1
, InferenceLatency
, LogLoss
, Precision
, Recall
Multiclass classification: Accuracy
, BalancedAccuracy
, F1macro
, InferenceLatency
, LogLoss
, PrecisionMacro
, RecallMacro
For a description of each metric, see Autopilot metrics for classification and regression.
Default objective metrics:
Regression: MSE
.
Binary classification: F1
.
Multiclass classification: Accuracy
.
For image or text classification problem types:
List of available metrics: Accuracy
For a description of each metric, see Autopilot metrics for text and image classification.
Default objective metrics: Accuracy
For time-series forecasting problem types:
List of available metrics: RMSE
, wQL
, Average wQL
, MASE
, MAPE
, WAPE
For a description of each metric, see Autopilot metrics for time-series forecasting.
Default objective metrics: AverageWeightedQuantileLoss
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective
field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.
', 'FinalAutoMLJobObjectiveMetric$StandardMetricName' => 'The name of the standard metric. For a description of the standard metrics, see Autopilot candidate metrics.
', 'MetricDatum$MetricName' => 'The name of the metric.
', ], ], 'AutoMLMetricExtendedEnum' => [ 'base' => NULL, 'refs' => [ 'MetricDatum$StandardMetricName' => 'The name of the standard metric.
For definitions of the standard metrics, see Autopilot candidate metrics
.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO
. In AUTO
mode, Autopilot chooses ENSEMBLING
for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING
for larger ones.
The ENSEMBLING
mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING
mode.
The HYPERPARAMETER_TUNING
(HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING
mode.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO
. In AUTO
mode, Autopilot chooses ENSEMBLING
for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING
for larger ones.
The ENSEMBLING
mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING
mode.
The HYPERPARAMETER_TUNING
(HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING
mode.
Request a list of jobs, using a search filter for name.
', ], ], 'AutoMLOutputDataConfig' => [ 'base' => 'The output data configuration.
', 'refs' => [ 'CreateAutoMLJobRequest$OutputDataConfig' => 'Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
', 'CreateAutoMLJobV2Request$OutputDataConfig' => 'Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
', 'DescribeAutoMLJobResponse$OutputDataConfig' => 'Returns the job\'s output data config.
', 'DescribeAutoMLJobV2Response$OutputDataConfig' => 'Returns the job\'s output data config.
', ], ], 'AutoMLPartialFailureReason' => [ 'base' => 'The reason for a partial failure of an AutoML job.
', 'refs' => [ 'AutoMLPartialFailureReasons$member' => NULL, ], ], 'AutoMLPartialFailureReasons' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$PartialFailureReasons' => 'The list of reasons for partial failures within an AutoML job.
', 'DescribeAutoMLJobResponse$PartialFailureReasons' => 'Returns a list of reasons for partial failures within an AutoML job.
', 'DescribeAutoMLJobV2Response$PartialFailureReasons' => 'Returns a list of reasons for partial failures within an AutoML job V2.
', ], ], 'AutoMLProblemTypeConfig' => [ 'base' => 'A collection of settings specific to the problem type used to configure an AutoML job V2. There must be one and only one config of the following type.
', 'refs' => [ 'CreateAutoMLJobV2Request$AutoMLProblemTypeConfig' => 'Defines the configuration settings of one of the supported problem types.
', 'DescribeAutoMLJobV2Response$AutoMLProblemTypeConfig' => 'Returns the configuration settings of the problem type set for the AutoML job V2.
', ], ], 'AutoMLProblemTypeConfigName' => [ 'base' => NULL, 'refs' => [ 'DescribeAutoMLJobV2Response$AutoMLProblemTypeConfigName' => 'Returns the name of the problem type configuration set for the AutoML job V2.
', ], ], 'AutoMLProblemTypeResolvedAttributes' => [ 'base' => 'Stores resolved attributes specific to the problem type of an AutoML job V2.
', 'refs' => [ 'AutoMLResolvedAttributes$AutoMLProblemTypeResolvedAttributes' => 'Defines the resolved attributes specific to a problem type.
', ], ], 'AutoMLProcessingUnit' => [ 'base' => NULL, 'refs' => [ 'AutoMLInferenceContainerDefinitions$key' => 'Processing unit for an inference container. Currently Autopilot only supports CPU
or GPU
.
The resolved attributes used to configure an AutoML job V2.
', 'refs' => [ 'DescribeAutoMLJobV2Response$ResolvedAttributes' => 'Returns the resolved attributes used by the AutoML job V2.
', ], ], 'AutoMLS3DataSource' => [ 'base' => 'Describes the Amazon S3 data source.
', 'refs' => [ 'AutoMLDataSource$S3DataSource' => 'The Amazon S3 location of the input data.
', ], ], 'AutoMLS3DataType' => [ 'base' => NULL, 'refs' => [ 'AutoMLS3DataSource$S3DataType' => 'The data type.
If you choose S3Prefix
, S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
The S3Prefix
should have the following format:
s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE
If you choose ManifestFile
, S3Uri
identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
A ManifestFile
should have the format shown below:
[ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"},
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",
... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]
If you choose AugmentedManifestFile
, S3Uri
identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile
is available for V2 API jobs only (for example, for jobs created by calling CreateAutoMLJobV2
).
Here is a minimal, single-record example of an AugmentedManifestFile
:
{"source-ref": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",
"label-metadata": {"class-name": "cat"
}
For more information on AugmentedManifestFile
, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.
Security options.
', 'refs' => [ 'AutoMLJobConfig$SecurityConfig' => 'The security configuration for traffic encryption or Amazon VPC settings.
', 'CreateAutoMLJobV2Request$SecurityConfig' => 'The security configuration for traffic encryption or Amazon VPC settings.
', 'DescribeAutoMLJobV2Response$SecurityConfig' => 'Returns the security configuration for traffic encryption or Amazon VPC settings.
', ], ], 'AutoMLSortBy' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsRequest$SortBy' => 'The parameter by which to sort the results. The default is Name
.
The sort order for the results. The default is Descending
.
The sort order for the results. The default is Ascending
.
The name and an example value of the hyperparameter that you want to use in Autotune. If Automatic model tuning (AMT) determines that your hyperparameter is eligible for Autotune, an optimal hyperparameter range is selected for you.
', 'refs' => [ 'AutoParameters$member' => NULL, ], ], 'AutoParameters' => [ 'base' => NULL, 'refs' => [ 'ParameterRanges$AutoParameters' => 'A list containing hyperparameter names and example values to be used by Autotune to determine optimal ranges for your tuning job.
', ], ], 'AutoRollbackConfig' => [ 'base' => 'Automatic rollback configuration for handling endpoint deployment failures and recovery.
', 'refs' => [ 'DeploymentConfig$AutoRollbackConfiguration' => 'Automatic rollback configuration for handling endpoint deployment failures and recovery.
', ], ], 'Autotune' => [ 'base' => 'A flag to indicate if you want to use Autotune to automatically find optimal values for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
A flag to indicate if autotune is enabled for the hyperparameter tuning job.
', ], ], 'AutotuneMode' => [ 'base' => NULL, 'refs' => [ 'Autotune$Mode' => 'Set Mode
to Enabled
if you want to use Autotune.
Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. The default field settings and JSON parsing rules are different based on the integration source. Valid values:
', ], ], 'BacktestResultsLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$BacktestResults' => 'The Amazon S3 prefix to the accuracy metrics and the inference results observed over the testing window. Available only for the time-series forecasting problem type.
', ], ], 'BaseModelName' => [ 'base' => NULL, 'refs' => [ 'TextGenerationJobConfig$BaseModelName' => 'The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no BaseModelName
is provided, the default model used is Falcon7BInstruct.
The name of the base model to fine-tune.
', ], ], 'BatchDataCaptureConfig' => [ 'base' => 'Configuration to control how SageMaker captures inference data for batch transform jobs.
', 'refs' => [ 'CreateTransformJobRequest$DataCaptureConfig' => 'Configuration to control how SageMaker captures inference data.
', 'DescribeTransformJobResponse$DataCaptureConfig' => 'Configuration to control how SageMaker captures inference data.
', 'TransformJob$DataCaptureConfig' => NULL, ], ], 'BatchDescribeModelPackageError' => [ 'base' => 'The error code and error description associated with the resource.
', 'refs' => [ 'BatchDescribeModelPackageErrorMap$value' => NULL, ], ], 'BatchDescribeModelPackageErrorMap' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageOutput$BatchDescribeModelPackageErrorMap' => 'A map of the resource and BatchDescribeModelPackageError objects reporting the error associated with describing the model package.
', ], ], 'BatchDescribeModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'BatchDescribeModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'BatchDescribeModelPackageSummary' => [ 'base' => 'Provides summary information about the model package.
', 'refs' => [ 'ModelPackageSummaries$value' => NULL, ], ], 'BatchStrategy' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$BatchStrategy' => 'Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set the SplitType
property to Line
, RecordIO
, or TFRecord
.
To use only one record when making an HTTP invocation request to a container, set BatchStrategy
to SingleRecord
and SplitType
to Line
.
To fit as many records in a mini-batch as can fit within the MaxPayloadInMB
limit, set BatchStrategy
to MultiRecord
and SplitType
to Line
.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set SplitType
to Line
, RecordIO
, or TFRecord
.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
', 'TransformJobDefinition$BatchStrategy' => 'A string that determines the number of records included in a single mini-batch.
SingleRecord
means only one record is used per mini-batch. MultiRecord
means a mini-batch is set to contain as many records that can fit within the MaxPayloadInMB
limit.
Input object for the batch transform job.
', 'refs' => [ 'DataQualityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelBiasJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelDashboardMonitoringSchedule$BatchTransformInput' => NULL, 'ModelExplainabilityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelQualityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'MonitoringInput$BatchTransformInput' => 'Input object for the batch transform job.
', ], ], 'BestObjectiveNotImproving' => [ 'base' => 'A structure that keeps track of which training jobs launched by your hyperparameter tuning job are not improving model performance as evaluated against an objective function.
', 'refs' => [ 'TuningJobCompletionCriteria$BestObjectiveNotImproving' => 'A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.
', ], ], 'Bias' => [ 'base' => 'Contains bias metrics for a model.
', 'refs' => [ 'ModelMetrics$Bias' => 'Metrics that measure bais in a model.
', ], ], 'BillableTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$BillableTimeInSeconds' => 'The billable time in seconds. Billable time refers to the absolute wall-clock time.
Multiply BillableTimeInSeconds
by the number of instances (InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: BillableTimeInSeconds * InstanceCount
.
You can calculate the savings from using managed spot training using the formula (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100
. For example, if BillableTimeInSeconds
is 100 and TrainingTimeInSeconds
is 500, the savings is 80%.
The billable time in seconds.
', ], ], 'BlockedReason' => [ 'base' => NULL, 'refs' => [ 'OfflineStoreStatus$BlockedReason' => 'The justification for why the OfflineStoreStatus is Blocked (if applicable).
', ], ], 'BlueGreenUpdatePolicy' => [ 'base' => 'Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
', 'refs' => [ 'DeploymentConfig$BlueGreenUpdatePolicy' => 'Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
', ], ], 'Boolean' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$EnableSageMakerMetricsTimeSeries' => 'To generate and save time-series metrics during training, set to true
. The default is false
and time-series metrics aren\'t generated except in the following cases:
You use one of the SageMaker built-in algorithms
You use one of the following Prebuilt SageMaker Docker Images:
Tensorflow (version >= 1.15)
MXNet (version >= 1.6)
PyTorch (version >= 1.3)
You specify at least one MetricDefinition
Whether to use traffic encryption between the container layers.
', 'BatchDataCaptureConfig$GenerateInferenceId' => 'Flag that indicates whether to append inference id to the output.
', 'ChannelSpecification$IsRequired' => 'Indicates whether the channel is required by the algorithm.
', 'ClarifyCheckStepMetadata$SkipCheck' => 'This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False
, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints
and BaselineUsedForDriftCheckStatistics
. If it is set to False
, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints
property.
Sets whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
', 'CreateModelInput$EnableNetworkIsolation' => 'Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
', 'CreateTrainingJobRequest$EnableNetworkIsolation' => 'Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
', 'CreateTrainingJobRequest$EnableInterContainerTrafficEncryption' => 'To encrypt all communications between ML compute instances in distributed training, choose True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see Protect Communications Between ML Compute Instances in a Distributed Training Job.
To train models using managed spot training, choose True
. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.
The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
', 'DescribeEndpointConfigOutput$EnableNetworkIsolation' => 'Indicates whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
', 'DescribeModelOutput$EnableNetworkIsolation' => 'If True
, no inbound or outbound network calls can be made to or from the model container.
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True
. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
To encrypt all communications between ML compute instances in distributed training, choose True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.
A Boolean indicating whether managed spot training is enabled (True
) or not (False
).
Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.
', 'HyperParameterSpecification$IsRequired' => 'Indicates whether this hyperparameter is required.
', 'HyperParameterTrainingJobDefinition$EnableNetworkIsolation' => 'Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
', 'HyperParameterTrainingJobDefinition$EnableInterContainerTrafficEncryption' => 'To encrypt all communications between ML compute instances in distributed training, choose True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
A Boolean indicating whether managed spot training is enabled (True
) or not (False
).
Toggle for excluding devices deployed in other stages.
', 'Model$EnableNetworkIsolation' => 'Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
', 'ModelDashboardIndicatorAction$Enabled' => 'Indicates whether the alert action is turned on.
', 'MonitoringCsvDatasetFormat$Header' => 'Indicates if the CSV data has a header.
', 'MonitoringJsonDatasetFormat$Line' => 'Indicates if the file should be read as a JSON object per line.
', 'MonitoringNetworkConfig$EnableInterContainerTrafficEncryption' => 'Whether to encrypt all communications between the instances used for the monitoring jobs. Choose True
to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for the monitoring job.
', 'NetworkConfig$EnableInterContainerTrafficEncryption' => 'Whether to encrypt all communications between distributed processing jobs. Choose True
to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
', 'OfflineStoreConfig$DisableGlueTableCreation' => 'Set to True
to disable the automatic creation of an Amazon Web Services Glue table when configuring an OfflineStore
. If set to False
, Feature Store will name the OfflineStore
Glue table following Athena\'s naming recommendations.
The default value is False
.
Turn OnlineStore
off by specifying False
for the EnableOnlineStore
flag. Turn OnlineStore
on by specifying True
for the EnableOnlineStore
flag.
The default value is False
.
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False
, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints
and BaselineUsedForDriftCheckStatistics
. If it is set to False
, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints
and BaselineUsedForDriftCheckStatistics
properties.
Setting this value to True
retrieves not only the entities of interest but also the Associations and lineage entities on the path. Set to False
to only return lineage entities that match your query.
If the TrainingJob
was created with network isolation, the value is set to true
. If network isolation is enabled, nodes can\'t communicate beyond the VPC they run in.
To encrypt all communications between ML compute instances in distributed training, choose True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
', 'TrainingSpecification$SupportsDistributedTraining' => 'Indicates whether the algorithm supports distributed training. If set to false, buyers can\'t request more than one instance during training.
', 'UpdateEndpointInput$RetainAllVariantProperties' => 'When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties
to true
. To use the variant properties specified in a new EndpointConfig
call when updating an endpoint, set RetainAllVariantProperties
to false
. The default is false
.
Specifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).
', ], ], 'BooleanOperator' => [ 'base' => NULL, 'refs' => [ 'SearchExpression$Operator' => 'A Boolean operator used to evaluate the search expression. If you want every conditional statement in all lists to be satisfied for the entire search expression to be true, specify And
. If only a single conditional statement needs to be true for the entire search expression to be true, specify Or
. The default value is And
.
The default branch for the Git repository.
', ], ], 'BucketName' => [ 'base' => NULL, 'refs' => [ 'PipelineDefinitionS3Location$Bucket' => 'Name of the S3 bucket.
', ], ], 'CacheHitResult' => [ 'base' => 'Details on the cache hit of a pipeline execution step.
', 'refs' => [ 'PipelineExecutionStep$CacheHitResult' => 'If this pipeline execution step was cached, details on the cache hit.
', ], ], 'CallbackStepMetadata' => [ 'base' => 'Metadata about a callback step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Callback' => 'The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.
', ], ], 'CallbackToken' => [ 'base' => NULL, 'refs' => [ 'CallbackStepMetadata$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', 'SendPipelineExecutionStepFailureRequest$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', 'SendPipelineExecutionStepSuccessRequest$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', ], ], 'CandidateArtifactLocations' => [ 'base' => 'The location of artifacts for an AutoML candidate job.
', 'refs' => [ 'CandidateProperties$CandidateArtifactLocations' => 'The Amazon S3 prefix to the artifacts generated for an AutoML candidate.
', ], ], 'CandidateDefinitionNotebookLocation' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobArtifacts$CandidateDefinitionNotebookLocation' => 'The URL of the notebook location.
', ], ], 'CandidateGenerationConfig' => [ 'base' => 'Stores the configuration information for how model candidates are generated using an AutoML job V2.
', 'refs' => [ 'TabularJobConfig$CandidateGenerationConfig' => 'The configuration information of how model candidates are generated.
', ], ], 'CandidateName' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$CandidateName' => 'The name of the candidate.
', 'ListCandidatesForAutoMLJobRequest$CandidateNameEquals' => 'List the candidates for the job and filter by candidate name.
', ], ], 'CandidateProperties' => [ 'base' => 'The properties of an AutoML candidate job.
', 'refs' => [ 'AutoMLCandidate$CandidateProperties' => 'The properties of an AutoML candidate job.
', ], ], 'CandidateSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobRequest$SortBy' => 'The parameter by which to sort the results. The default is Descending
.
The candidate\'s status.
', 'ListCandidatesForAutoMLJobRequest$StatusEquals' => 'List the candidates for the job and filter by status.
', ], ], 'CandidateStepArn' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepArn' => 'The ARN for the candidate\'s step.
', ], ], 'CandidateStepName' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepName' => 'The name for the candidate\'s step.
', ], ], 'CandidateStepType' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepType' => 'Whether the candidate is at the transform, training, or processing step.
', ], ], 'CandidateSteps' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$CandidateSteps' => 'Information about the candidate\'s steps.
', ], ], 'CanvasAppSettings' => [ 'base' => 'The SageMaker Canvas application settings.
', 'refs' => [ 'UserSettings$CanvasAppSettings' => 'The Canvas app settings.
', ], ], 'CapacitySize' => [ 'base' => 'Specifies the type and size of the endpoint capacity to activate for a blue/green deployment, a rolling deployment, or a rollback strategy. You can specify your batches as either instance count or the overall percentage or your fleet.
For a rollback strategy, if you don\'t specify the fields in this object, or if you set the Value
to 100%, then SageMaker uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant\'s total instance count.
', 'RollingUpdatePolicy$RollbackMaximumBatchSize' => 'Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.
', 'TrafficRoutingConfig$CanarySize' => 'Batch size for the first step to turn on traffic on the new endpoint fleet. Value
must be less than or equal to 50% of the variant\'s total instance count.
Batch size for each step to turn on traffic on the new endpoint fleet. Value
must be 10-50% of the variant\'s total instance count.
Specifies the endpoint capacity type.
INSTANCE_COUNT
: The endpoint activates based on the number of instances.
CAPACITY_PERCENT
: The endpoint activates based on the specified percentage of capacity.
Defines the capacity size, either as a number of instances or a capacity percentage.
', ], ], 'CapacityUnit' => [ 'base' => NULL, 'refs' => [ 'ThroughputConfig$ProvisionedReadCapacityUnits' => 'For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
', 'ThroughputConfig$ProvisionedWriteCapacityUnits' => 'For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
', 'ThroughputConfigDescription$ProvisionedReadCapacityUnits' => 'For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
', 'ThroughputConfigDescription$ProvisionedWriteCapacityUnits' => 'For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
', 'ThroughputConfigUpdate$ProvisionedReadCapacityUnits' => 'For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
', 'ThroughputConfigUpdate$ProvisionedWriteCapacityUnits' => 'For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
', ], ], 'CaptureContentTypeHeader' => [ 'base' => 'Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker will by default base64 encode when capturing the data.
', 'refs' => [ 'DataCaptureConfig$CaptureContentTypeHeader' => 'Configuration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.
', 'InferenceExperimentDataStorageConfig$ContentType' => NULL, ], ], 'CaptureMode' => [ 'base' => NULL, 'refs' => [ 'CaptureOption$CaptureMode' => 'Specify the boundary of data to capture.
', ], ], 'CaptureOption' => [ 'base' => 'Specifies data Model Monitor will capture.
', 'refs' => [ 'CaptureOptionList$member' => NULL, ], ], 'CaptureOptionList' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$CaptureOptions' => 'Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
', ], ], 'CaptureStatus' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfigSummary$CaptureStatus' => 'Whether data capture is currently functional.
', ], ], 'Catalog' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$Catalog' => 'The name of the Glue table catalog.
', ], ], 'CategoricalParameter' => [ 'base' => 'Environment parameters you want to benchmark your load test against.
', 'refs' => [ 'CategoricalParameters$member' => NULL, ], ], 'CategoricalParameterRange' => [ 'base' => 'A list of categorical hyperparameters to tune.
', 'refs' => [ 'CategoricalParameterRanges$member' => NULL, ], ], 'CategoricalParameterRangeSpecification' => [ 'base' => 'Defines the possible values for a categorical hyperparameter.
', 'refs' => [ 'ParameterRange$CategoricalParameterRangeSpecification' => 'A CategoricalParameterRangeSpecification
object that defines the possible values for a categorical hyperparameter.
The list of values you can pass.
', ], ], 'CategoricalParameterRanges' => [ 'base' => NULL, 'refs' => [ 'ParameterRanges$CategoricalParameterRanges' => 'The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.
', ], ], 'CategoricalParameters' => [ 'base' => NULL, 'refs' => [ 'EnvironmentParameterRanges$CategoricalParameterRanges' => 'Specified a list of parameters for each category.
', ], ], 'Cents' => [ 'base' => NULL, 'refs' => [ 'USD$Cents' => 'The fractional portion, in cents, of the amount.
', ], ], 'CertifyForMarketplace' => [ 'base' => NULL, 'refs' => [ 'CreateAlgorithmInput$CertifyForMarketplace' => 'Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.
', 'CreateModelPackageInput$CertifyForMarketplace' => 'Whether to certify the model package for listing on Amazon Web Services Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
', 'DescribeAlgorithmOutput$CertifyForMarketplace' => 'Whether the algorithm is certified to be listed in Amazon Web Services Marketplace.
', 'DescribeModelPackageOutput$CertifyForMarketplace' => 'Whether the model package is certified for listing on Amazon Web Services Marketplace.
', 'ModelPackage$CertifyForMarketplace' => 'Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.
', ], ], 'Channel' => [ 'base' => 'A channel is a named input source that training algorithms can consume.
', 'refs' => [ 'InputDataConfig$member' => NULL, ], ], 'ChannelName' => [ 'base' => NULL, 'refs' => [ 'Channel$ChannelName' => 'The name of the channel.
', 'ChannelSpecification$Name' => 'The name of the channel.
', ], ], 'ChannelSpecification' => [ 'base' => 'Defines a named input source, called a channel, to be used by an algorithm.
', 'refs' => [ 'ChannelSpecifications$member' => NULL, ], ], 'ChannelSpecifications' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$TrainingChannels' => 'A list of ChannelSpecification
objects, which specify the input sources to be used by the algorithm.
Contains information about the output location for managed spot training checkpoint data.
', 'refs' => [ 'CreateTrainingJobRequest$CheckpointConfig' => 'Contains information about the output location for managed spot training checkpoint data.
', 'DescribeTrainingJobResponse$CheckpointConfig' => NULL, 'HyperParameterTrainingJobDefinition$CheckpointConfig' => NULL, 'TrainingJob$CheckpointConfig' => NULL, ], ], 'Cidr' => [ 'base' => NULL, 'refs' => [ 'Cidrs$member' => NULL, ], ], 'Cidrs' => [ 'base' => NULL, 'refs' => [ 'SourceIpConfig$Cidrs' => 'A list of one to ten Classless Inter-Domain Routing (CIDR) values.
Maximum: Ten CIDR values
The following Length Constraints apply to individual CIDR values in the CIDR value list.
The container for the metadata for the ClarifyCheck step. For more information, see the topic on ClarifyCheck step in the Amazon SageMaker Developer Guide.
', 'refs' => [ 'PipelineExecutionStepMetadata$ClarifyCheck' => 'Container for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes:
The type of the check conducted,
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck
is set the same as CalculatedBaseline
.
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate
string \'{"myfeatures":$features}\'
will format a list of features [1,2,3]
into the record string \'{"myfeatures":[1,2,3]}\'
. Required only when the model container input is in JSON Lines format.
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See EnableExplanations
for additional information.
The configuration parameters for the SageMaker Clarify explainer.
', 'refs' => [ 'ExplainerConfig$ClarifyExplainerConfig' => 'A member of ExplainerConfig
that contains configuration parameters for the SageMaker Clarify explainer.
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint
output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes
must have at least one \'text\'
string (for example, [\'text\']
). If FeatureTypes
is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute
is the JMESPath expression \'myfeatures\'
, it extracts a list of features [1,2,3]
from request data \'{"myfeatures":[1,2,3]}\'
.
The inference configuration parameter for the model container.
', 'refs' => [ 'ClarifyExplainerConfig$InferenceConfig' => 'The inference configuration parameter for the model container.
', ], ], 'ClarifyLabelAttribute' => [ 'base' => NULL, 'refs' => [ 'ClarifyInferenceConfig$LabelAttribute' => 'A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is \'{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}\'
, then set LabelAttribute
to \'labels\'
to extract the list of label headers ["cat","dog","fish"]
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint
API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: \'"[\\\'cat\\\',\\\'dog\\\',\\\'fish\\\']","[0.1,0.6,0.3]"\'
, set LabelIndex
to 0
to select the label headers [\'cat\',\'dog\',\'fish\']
.
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6
MB.
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount
is 1
, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container\'s capacity at runtime.
The MIME type of the baseline data. Choose from \'text/csv\'
or \'application/jsonlines\'
. Defaults to \'text/csv\'
.
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is \'{"predicted_label":1,"probability":0.6}\'
, then set ProbabilityAttribute
to \'probability\'
.
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: \'1,0.6\'
, set ProbabilityIndex
to 1
to select the probability value 0.6
.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: \'"[\\\'cat\\\',\\\'dog\\\',\\\'fish\\\']","[0.1,0.6,0.3]"\'
, set ProbabilityIndex
to 1
to select the probability values [0.1,0.6,0.3]
.
The inline SHAP baseline data in string format. ShapBaseline
can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity
of the TextConfig
parameter. The size limit for ShapBasline
is 4 KB. Use the ShapBaselineUri
parameter if you want to provide more than 4 KB of baseline data.
The configuration for the SHAP baseline (also called the background or reference dataset) of the Kernal SHAP algorithm.
The number of records in the baseline data determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
ShapBaseline
and ShapBaselineUri
are mutually exclusive parameters. One or the either is required to configure a SHAP baseline.
The configuration for the SHAP baseline of the Kernal SHAP algorithm.
', ], ], 'ClarifyShapConfig' => [ 'base' => 'The configuration for SHAP analysis using SageMaker Clarify Explainer.
', 'refs' => [ 'ClarifyExplainerConfig$ShapConfig' => 'The configuration for SHAP analysis.
', ], ], 'ClarifyShapNumberOfSamples' => [ 'base' => NULL, 'refs' => [ 'ClarifyShapConfig$NumberOfSamples' => 'The number of samples to be used for analysis by the Kernal SHAP algorithm.
The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
', ], ], 'ClarifyShapUseLogit' => [ 'base' => NULL, 'refs' => [ 'ClarifyShapConfig$UseLogit' => 'A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
', ], ], 'ClarifyTextConfig' => [ 'base' => 'A parameter used to configure the SageMaker Clarify explainer to treat text features as text so that explanations are provided for individual units of text. Required only for natural language processing (NLP) explainability.
', 'refs' => [ 'ClarifyShapConfig$TextConfig' => 'A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
', ], ], 'ClarifyTextGranularity' => [ 'base' => NULL, 'refs' => [ 'ClarifyTextConfig$Granularity' => 'The unit of granularity for the analysis of text features. For example, if the unit is \'token\'
, then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
For a mix of multiple languages, use code \'xx\'
.
The client ID for your Amazon Cognito user pool.
', 'CognitoMemberDefinition$ClientId' => 'An identifier for an application client. You must create the app client ID using Amazon Cognito.
', 'OidcConfig$ClientId' => 'The OIDC IdP client ID used to configure your private workforce.
', 'OidcConfigForResponse$ClientId' => 'The OIDC IdP client ID used to configure your private workforce.
', ], ], 'ClientSecret' => [ 'base' => NULL, 'refs' => [ 'OidcConfig$ClientSecret' => 'The OIDC IdP client secret used to configure your private workforce.
', ], ], 'ClientToken' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ClientToken' => 'A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.
', 'CreateModelPackageInput$ClientToken' => 'A unique token that guarantees that the call to this API is idempotent.
', ], ], 'ClusterArn' => [ 'base' => NULL, 'refs' => [ 'ClusterSummary$ClusterArn' => 'The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
', 'CreateClusterResponse$ClusterArn' => 'The Amazon Resource Name (ARN) of the cluster.
', 'DeleteClusterResponse$ClusterArn' => 'The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster to delete.
', 'DescribeClusterResponse$ClusterArn' => 'The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
', 'UpdateClusterResponse$ClusterArn' => 'The Amazon Resource Name (ARN) of the updated SageMaker HyperPod cluster.
', ], ], 'ClusterInstanceCount' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$TargetCount' => 'The number of instances you specified to add to the instance group of a SageMaker HyperPod cluster.
', 'ClusterInstanceGroupSpecification$InstanceCount' => 'Specifies the number of instances to add to the instance group of a SageMaker HyperPod cluster.
', ], ], 'ClusterInstanceGroupDetails' => [ 'base' => 'Details of an instance group in a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterInstanceGroupDetailsList$member' => NULL, ], ], 'ClusterInstanceGroupDetailsList' => [ 'base' => NULL, 'refs' => [ 'DescribeClusterResponse$InstanceGroups' => 'The instance groups of the SageMaker HyperPod cluster.
', ], ], 'ClusterInstanceGroupName' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$InstanceGroupName' => 'The name of the instance group of a SageMaker HyperPod cluster.
', 'ClusterInstanceGroupSpecification$InstanceGroupName' => 'Specifies the name of the instance group.
', 'ClusterNodeDetails$InstanceGroupName' => 'The instance group name in which the instance is.
', 'ClusterNodeSummary$InstanceGroupName' => 'The name of the instance group in which the instance is.
', 'ListClusterNodesRequest$InstanceGroupNameContains' => 'A filter that returns the instance groups whose name contain a specified string.
', ], ], 'ClusterInstanceGroupSpecification' => [ 'base' => 'The specifications of an instance group that you need to define.
', 'refs' => [ 'ClusterInstanceGroupSpecifications$member' => NULL, ], ], 'ClusterInstanceGroupSpecifications' => [ 'base' => NULL, 'refs' => [ 'CreateClusterRequest$InstanceGroups' => 'The instance groups to be created in the SageMaker HyperPod cluster.
', 'UpdateClusterRequest$InstanceGroups' => 'Specify the instance groups to update.
', ], ], 'ClusterInstanceStatus' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceStatusDetails$Status' => 'The status of an instance in a SageMaker HyperPod cluster.
', ], ], 'ClusterInstanceStatusDetails' => [ 'base' => 'Details of an instance in a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterNodeDetails$InstanceStatus' => 'The status of the instance.
', 'ClusterNodeSummary$InstanceStatus' => 'The status of the instance.
', ], ], 'ClusterInstanceType' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$InstanceType' => 'The instance type of the instance group of a SageMaker HyperPod cluster.
', 'ClusterInstanceGroupSpecification$InstanceType' => 'Specifies the instance type of the instance group.
', 'ClusterNodeDetails$InstanceType' => 'The type of the instance.
', 'ClusterNodeSummary$InstanceType' => 'The type of the instance.
', ], ], 'ClusterLifeCycleConfig' => [ 'base' => 'The LifeCycle configuration for a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterInstanceGroupDetails$LifeCycleConfig' => 'Details of LifeCycle configuration for the instance group.
', 'ClusterInstanceGroupSpecification$LifeCycleConfig' => 'Specifies the LifeCycle configuration for the instance group.
', 'ClusterNodeDetails$LifeCycleConfig' => 'The LifeCycle configuration applied to the instance.
', ], ], 'ClusterLifeCycleConfigFileName' => [ 'base' => NULL, 'refs' => [ 'ClusterLifeCycleConfig$OnCreate' => 'The directory of the LifeCycle script under SourceS3Uri
. This LifeCycle script runs during cluster creation.
The name of the SageMaker HyperPod cluster.
', 'CreateClusterRequest$ClusterName' => 'The name for the new SageMaker HyperPod cluster.
', 'DescribeClusterResponse$ClusterName' => 'The name of the SageMaker HyperPod cluster.
', ], ], 'ClusterNameOrArn' => [ 'base' => NULL, 'refs' => [ 'DeleteClusterRequest$ClusterName' => 'The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster to delete.
', 'DescribeClusterNodeRequest$ClusterName' => 'The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which the instance is.
', 'DescribeClusterRequest$ClusterName' => 'The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
', 'ListClusterNodesRequest$ClusterName' => 'The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which you want to retrieve the list of nodes.
', 'UpdateClusterRequest$ClusterName' => 'Specify the name of the SageMaker HyperPod cluster you want to update.
', ], ], 'ClusterNodeDetails' => [ 'base' => 'Details of an instance (also called a node interchangeably) in a SageMaker HyperPod cluster.
', 'refs' => [ 'DescribeClusterNodeResponse$NodeDetails' => 'The details of the instance.
', ], ], 'ClusterNodeId' => [ 'base' => NULL, 'refs' => [ 'DescribeClusterNodeRequest$NodeId' => 'The ID of the instance.
', ], ], 'ClusterNodeSummaries' => [ 'base' => NULL, 'refs' => [ 'ListClusterNodesResponse$ClusterNodeSummaries' => 'The summaries of listed instances in a SageMaker HyperPod cluster
', ], ], 'ClusterNodeSummary' => [ 'base' => 'Lists a summary of the properties of an instance (also called a node interchangeably) of a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterNodeSummaries$member' => NULL, ], ], 'ClusterNonNegativeInstanceCount' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$CurrentCount' => 'The number of instances that are currently in the instance group of a SageMaker HyperPod cluster.
', ], ], 'ClusterSortBy' => [ 'base' => NULL, 'refs' => [ 'ListClusterNodesRequest$SortBy' => 'The field by which to sort results. The default value is CREATION_TIME
.
The field by which to sort results. The default value is CREATION_TIME
.
The status of the SageMaker HyperPod cluster.
', 'DescribeClusterResponse$ClusterStatus' => 'The status of the SageMaker HyperPod cluster.
', ], ], 'ClusterSummaries' => [ 'base' => NULL, 'refs' => [ 'ListClustersResponse$ClusterSummaries' => 'The summaries of listed SageMaker HyperPod clusters.
', ], ], 'ClusterSummary' => [ 'base' => 'Lists a summary of the properties of a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterSummaries$member' => NULL, ], ], 'ClusterThreadsPerCore' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$ThreadsPerCore' => 'The number you specified to TreadsPerCore
in CreateCluster
for enabling or disabling multithreading. For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
Specifies the value for Threads per core. For instance types that support multithreading, you can specify 1
for disabling multithreading and 2
for enabling multithreading. For instance types that doesn\'t support multithreading, specify 1
. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
The number of threads per CPU core you specified under CreateCluster
.
The Code Editor application settings.
For more information about Code Editor, see Get started with Code Editor in Amazon SageMaker.
', 'refs' => [ 'UserSettings$CodeEditorAppSettings' => 'The Code Editor application settings.
', ], ], 'CodeRepositories' => [ 'base' => NULL, 'refs' => [ 'JupyterLabAppSettings$CodeRepositories' => 'A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterLab application.
', 'JupyterServerAppSettings$CodeRepositories' => 'A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.
', 'SpaceJupyterLabAppSettings$CodeRepositories' => 'A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterLab application.
', ], ], 'CodeRepository' => [ 'base' => 'A Git repository that SageMaker automatically displays to users for cloning in the JupyterServer application.
', 'refs' => [ 'CodeRepositories$member' => NULL, ], ], 'CodeRepositoryArn' => [ 'base' => NULL, 'refs' => [ 'CodeRepositorySummary$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the Git repository.
', 'CreateCodeRepositoryOutput$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the new repository.
', 'DescribeCodeRepositoryOutput$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the Git repository.
', 'UpdateCodeRepositoryOutput$CodeRepositoryArn' => 'The ARN of the Git repository.
', ], ], 'CodeRepositoryContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$DefaultCodeRepositoryContains' => 'A string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.
', ], ], 'CodeRepositoryNameContains' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesInput$NameContains' => 'A string in the Git repositories name. This filter returns only repositories whose name contains the specified string.
', ], ], 'CodeRepositoryNameOrUrl' => [ 'base' => NULL, 'refs' => [ 'AdditionalCodeRepositoryNamesOrUrls$member' => NULL, 'CreateNotebookInstanceInput$DefaultCodeRepository' => 'A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'DescribeNotebookInstanceOutput$DefaultCodeRepository' => 'The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'ListNotebookInstancesInput$AdditionalCodeRepositoryEquals' => 'A filter that returns only notebook instances with associated with the specified git repository.
', 'NotebookInstanceSummary$DefaultCodeRepository' => 'The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'UpdateNotebookInstanceInput$DefaultCodeRepository' => 'The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', ], ], 'CodeRepositorySortBy' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesInput$SortBy' => 'The field to sort results by. The default is Name
.
The sort order for results. The default is Ascending
.
Specifies summary information about a Git repository.
', 'refs' => [ 'CodeRepositorySummaryList$member' => NULL, ], ], 'CodeRepositorySummaryList' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesOutput$CodeRepositorySummaryList' => 'Gets a list of summaries of the Git repositories. Each summary specifies the following values for the repository:
Name
Amazon Resource Name (ARN)
Creation time
Last modified time
Configuration information, including the URL location of the repository and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
', 'refs' => [ 'CreateWorkforceRequest$CognitoConfig' => 'Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use OidcConfig
if you specify values for CognitoConfig
.
The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
', ], ], 'CognitoMemberDefinition' => [ 'base' => 'Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
', 'refs' => [ 'MemberDefinition$CognitoMemberDefinition' => 'The Amazon Cognito user group that is part of the work team.
', ], ], 'CognitoUserGroup' => [ 'base' => NULL, 'refs' => [ 'CognitoMemberDefinition$UserGroup' => 'An identifier for a user group.
', ], ], 'CognitoUserPool' => [ 'base' => NULL, 'refs' => [ 'CognitoConfig$UserPool' => 'A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.
', 'CognitoMemberDefinition$UserPool' => 'An identifier for a user pool. The user pool must be in the same region as the service that you are calling.
', ], ], 'CollectionConfig' => [ 'base' => 'Configuration for your collection.
', 'refs' => [ 'FeatureDefinition$CollectionConfig' => 'Configuration for your collection.
', ], ], 'CollectionConfiguration' => [ 'base' => 'Configuration information for the Amazon SageMaker Debugger output tensor collections.
', 'refs' => [ 'CollectionConfigurations$member' => NULL, ], ], 'CollectionConfigurations' => [ 'base' => NULL, 'refs' => [ 'DebugHookConfig$CollectionConfigurations' => 'Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
The name of the tensor collection. The name must be unique relative to other rule configuration names.
', ], ], 'CollectionParameters' => [ 'base' => NULL, 'refs' => [ 'CollectionConfiguration$CollectionParameters' => 'Parameter values for the tensor collection. The allowed parameters are "name"
, "include_regex"
, "reduction_config"
, "save_config"
, "tensor_names"
, and "save_histogram"
.
A grouping of elements where each element within the collection must have the same feature type (String
, Integral
, or Fractional
).
List
: An ordered collection of elements.
Set
: An unordered collection of unique elements.
Vector
: A specialized list that represents a fixed-size array of elements. The vector dimension is determined by you. Must have elements with fractional feature types.
The Amazon Resource Name (ARN) of the model compilation job.
', 'CreateCompilationJobResponse$CompilationJobArn' => 'If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker returns the following data in JSON format:
CompilationJobArn
: The Amazon Resource Name (ARN) of the compiled job.
The Amazon Resource Name (ARN) of the model compilation job.
', ], ], 'CompilationJobStatus' => [ 'base' => NULL, 'refs' => [ 'CompilationJobSummary$CompilationJobStatus' => 'The status of the model compilation job.
', 'DescribeCompilationJobResponse$CompilationJobStatus' => 'The status of the model compilation job.
', 'ListCompilationJobsRequest$StatusEquals' => 'A filter that retrieves model compilation jobs with a specific CompilationJobStatus
status.
An array of CompilationJobSummary objects, each describing a model compilation job.
', ], ], 'CompilationJobSummary' => [ 'base' => 'A summary of a model compilation job.
', 'refs' => [ 'CompilationJobSummaries$member' => NULL, ], ], 'CompilerOptions' => [ 'base' => NULL, 'refs' => [ 'OutputConfig$CompilerOptions' => 'Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform
specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.
DTYPE
: Specifies the data type for the input. When compiling for ml_*
(except for ml_inf
) instances using PyTorch framework, provide the data type (dtype) of the model\'s input. "float32"
is used if "DTYPE"
is not specified. Options for data type are:
float32: Use either "float"
or "float32"
.
int64: Use either "int64"
or "long"
.
For example, {"dtype" : "float32"}
.
CPU
: Compilation for CPU supports the following compiler options.
mcpu
: CPU micro-architecture. For example, {\'mcpu\': \'skylake-avx512\'}
mattr
: CPU flags. For example, {\'mattr\': [\'+neon\', \'+vfpv4\']}
ARM
: Details of ARM CPU compilations.
NEON
: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.
For example, add {\'mattr\': [\'+neon\']}
to the compiler options if compiling for ARM 32-bit platform with the NEON support.
NVIDIA
: Compilation for NVIDIA GPU supports the following compiler options.
gpu_code
: Specifies the targeted architecture.
trt-ver
: Specifies the TensorRT versions in x.y.z. format.
cuda-ver
: Specifies the CUDA version in x.y format.
For example, {\'gpu-code\': \'sm_72\', \'trt-ver\': \'6.0.1\', \'cuda-ver\': \'10.1\'}
ANDROID
: Compilation for the Android OS supports the following compiler options:
ANDROID_PLATFORM
: Specifies the Android API levels. Available levels range from 21 to 29. For example, {\'ANDROID_PLATFORM\': 28}
.
mattr
: Add {\'mattr\': [\'+neon\']}
to compiler options if compiling for ARM 32-bit platform with NEON support.
INFERENTIA
: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, "CompilerOptions": "\\"--verbose 1 --num-neuroncores 2 -O2\\""
.
For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
CoreML
: Compilation for the CoreML OutputConfig TargetDevice
supports the following compiler options:
class_labels
: Specifies the classification labels file name inside input tar.gz file. For example, {"class_labels": "imagenet_labels_1000.txt"}
. Labels inside the txt file should be separated by newlines.
EIA
: Compilation for the Elastic Inference Accelerator supports the following compiler options:
precision_mode
: Specifies the precision of compiled artifacts. Supported values are "FP16"
and "FP32"
. Default is "FP32"
.
signature_def_key
: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow\'s default signature def key.
output_names
: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: signature_def_key
or output_names
.
For example: {"precision_mode": "FP32", "output_names": ["output:0"]}
A flag to stop a tuning job once AMT has detected that the job has converged.
', ], ], 'CompressionType' => [ 'base' => NULL, 'refs' => [ 'AdditionalS3DataSource$CompressionType' => 'The type of compression used for an additional data source used in inference or training. Specify None
if your additional data source is not compressed.
You can use Gzip
or None
. The default value is None
.
The allowed compression types depend on the input format and problem type. We allow the compression type Gzip
for S3Prefix
inputs on tabular data only. For all other inputs, the compression type should be None
. If no compression type is provided, we default to None
.
If training data is compressed, the compression type. The default value is None
. CompressionType
is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None
.
The allowed compression types, if data compression is used.
', ], ], 'ConditionOutcome' => [ 'base' => NULL, 'refs' => [ 'ConditionStepMetadata$Outcome' => 'The outcome of the Condition step evaluation.
', ], ], 'ConditionStepMetadata' => [ 'base' => 'Metadata for a Condition step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Condition' => 'The outcome of the condition evaluation that was run by this step execution.
', ], ], 'ConfigKey' => [ 'base' => NULL, 'refs' => [ 'CollectionParameters$key' => NULL, 'HookParameters$key' => NULL, 'ProfilingParameters$key' => NULL, 'RuleParameters$key' => NULL, ], ], 'ConfigValue' => [ 'base' => NULL, 'refs' => [ 'CollectionParameters$value' => NULL, 'HookParameters$value' => NULL, 'ProfilingParameters$value' => NULL, 'RuleParameters$value' => NULL, ], ], 'ConflictException' => [ 'base' => 'There was a conflict when you attempted to modify a SageMaker entity such as an Experiment
or Artifact
.
The arguments for a container used to run a processing job.
', ], ], 'ContainerConfig' => [ 'base' => 'The configuration used to run the application image container.
', 'refs' => [ 'JupyterLabAppImageConfig$ContainerConfig' => NULL, ], ], 'ContainerDefinition' => [ 'base' => 'Describes the container, as part of model definition.
', 'refs' => [ 'ContainerDefinitionList$member' => NULL, 'CreateModelInput$PrimaryContainer' => 'The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
', 'DescribeModelOutput$PrimaryContainer' => 'The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
', 'Model$PrimaryContainer' => NULL, ], ], 'ContainerDefinitionList' => [ 'base' => NULL, 'refs' => [ 'CreateModelInput$Containers' => 'Specifies the containers in the inference pipeline.
', 'DescribeModelOutput$Containers' => 'The containers in the inference pipeline.
', 'Model$Containers' => 'The containers in the inference pipeline.
', ], ], 'ContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'AppSpecification$ContainerEntrypoint' => 'The entrypoint for a container used to run a processing job.
', 'DataQualityAppSpecification$ContainerEntrypoint' => 'The entrypoint for a container used to run a monitoring job.
', 'ModelQualityAppSpecification$ContainerEntrypoint' => 'Specifies the entrypoint for a container that the monitoring job runs.
', 'MonitoringAppSpecification$ContainerEntrypoint' => 'Specifies the entrypoint for a container used to run the monitoring job.
', ], ], 'ContainerEntrypointString' => [ 'base' => NULL, 'refs' => [ 'ContainerEntrypoint$member' => NULL, ], ], 'ContainerHostname' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$ContainerHostname' => 'This parameter is ignored for models that contain only a PrimaryContainer
.
When a ContainerDefinition
is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don\'t specify a value for this parameter for a ContainerDefinition
that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition
in the pipeline. If you specify a value for the ContainerHostName
for any ContainerDefinition
that is part of an inference pipeline, you must specify a value for the ContainerHostName
parameter of every ContainerDefinition
in that pipeline.
The DNS host name for the Docker container.
', ], ], 'ContainerImage' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$Image' => 'The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see ContainerDefinition.
', 'ContainerDefinition$Image' => 'The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The image path you specified when you created the model.
', 'DeployedImage$ResolvedImage' => 'The specific digest path of the image hosted in this ProductionVariant
.
The Amazon Elastic Container Registry (Amazon ECR) path where the Docker image for the model is stored.
', 'ModelPackageContainerDefinition$Image' => 'The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The Amazon ECR registry path of the Docker image that contains the training algorithm.
', ], ], 'ContainerMode' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$Mode' => 'Whether the container hosts a single model or multiple models.
', ], ], 'ContentClassifier' => [ 'base' => NULL, 'refs' => [ 'ContentClassifiers$member' => NULL, ], ], 'ContentClassifiers' => [ 'base' => NULL, 'refs' => [ 'LabelingJobDataAttributes$ContentClassifiers' => 'Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.
', ], ], 'ContentColumn' => [ 'base' => NULL, 'refs' => [ 'TextClassificationJobConfig$ContentColumn' => 'The name of the column used to provide the sentences to be classified. It should not be the same as the target column.
', ], ], 'ContentDigest' => [ 'base' => NULL, 'refs' => [ 'FileSource$ContentDigest' => 'The digest of the file source.
', 'MetricsSource$ContentDigest' => 'The hash key used for the metrics source.
', ], ], 'ContentType' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$ContentType' => 'The content type of the data from the input source. You can use text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
The content type of the data from the input source. The following are the allowed content types for different problems:
For tabular problem types: text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
For image classification: image/png
, image/jpeg
, or image/*
. The default value is image/*
.
For text classification: text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
For time-series forecasting: text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
For text generation (LLMs fine-tuning): text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
The MIME type of the data.
', 'ContentTypes$member' => NULL, 'FileSource$ContentType' => 'The type of content stored in the file source.
', 'MetricsSource$ContentType' => 'The metric source content type.
', 'TransformInput$ContentType' => 'The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
', ], ], 'ContentTypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedContentTypes' => 'The supported MIME types for the input data.
', 'ChannelSpecification$SupportedContentTypes' => 'The supported MIME types for the data.
', 'InferenceSpecification$SupportedContentTypes' => 'The supported MIME types for the input data.
', ], ], 'ContextArn' => [ 'base' => NULL, 'refs' => [ 'ContextSummary$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'CreateContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'DeleteContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'DescribeContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'UpdateContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', ], ], 'ContextName' => [ 'base' => NULL, 'refs' => [ 'ContextSummary$ContextName' => 'The name of the context.
', 'CreateContextRequest$ContextName' => 'The name of the context. Must be unique to your account in an Amazon Web Services Region.
', 'DeleteContextRequest$ContextName' => 'The name of the context to delete.
', 'DescribeContextResponse$ContextName' => 'The name of the context.
', 'UpdateContextRequest$ContextName' => 'The name of the context to update.
', ], ], 'ContextNameOrArn' => [ 'base' => NULL, 'refs' => [ 'DescribeContextRequest$ContextName' => 'The name of the context to describe.
', ], ], 'ContextSource' => [ 'base' => 'A structure describing the source of a context.
', 'refs' => [ 'ContextSummary$Source' => 'The source of the context.
', 'CreateContextRequest$Source' => 'The source type, ID, and URI.
', 'DescribeContextResponse$Source' => 'The source of the context.
', ], ], 'ContextSummaries' => [ 'base' => NULL, 'refs' => [ 'ListContextsResponse$ContextSummaries' => 'A list of contexts and their properties.
', ], ], 'ContextSummary' => [ 'base' => 'Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
', 'refs' => [ 'ContextSummaries$member' => NULL, ], ], 'ContinuousParameterRange' => [ 'base' => 'A list of continuous hyperparameters to tune.
', 'refs' => [ 'ContinuousParameterRanges$member' => NULL, ], ], 'ContinuousParameterRangeSpecification' => [ 'base' => 'Defines the possible values for a continuous hyperparameter.
', 'refs' => [ 'ParameterRange$ContinuousParameterRangeSpecification' => 'A ContinuousParameterRangeSpecification
object that defines the possible values for a continuous hyperparameter.
The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.
', ], ], 'ConvergenceDetected' => [ 'base' => 'A flag to indicating that automatic model tuning (AMT) has detected model convergence, defined as a lack of significant improvement (1% or less) against an objective metric.
', 'refs' => [ 'TuningJobCompletionCriteria$ConvergenceDetected' => 'A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.
', ], ], 'CountryCode' => [ 'base' => NULL, 'refs' => [ 'HolidayConfigAttributes$CountryCode' => 'The country code for the holiday calendar.
For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your choice.
', ], ], 'CreateActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAlgorithmInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateAlgorithmOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobV2Request' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobV2Response' => [ 'base' => NULL, 'refs' => [], ], 'CreateClusterRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateClusterResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateCompilationJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateDataQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDataQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentPlanRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentPlanResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFlowDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFlowDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHumanTaskUiRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHumanTaskUiResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceComponentInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceComponentOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceRecommendationsJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateLabelingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelBiasJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelBiasJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardExportJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardExportJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelExplainabilityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelExplainabilityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageGroupInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageGroupOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreatePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreatePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedDomainUrlRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedDomainUrlResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedNotebookInstanceUrlInput' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedNotebookInstanceUrlOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateProcessingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateStudioLifecycleConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateStudioLifecycleConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTransformJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreationTime' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$CreationTime' => 'A timestamp that shows when the algorithm was created.
', 'AppDetails$CreationTime' => 'The creation time.
', 'BatchDescribeModelPackageSummary$CreationTime' => 'The creation time of the mortgage package summary.
', 'CodeRepositorySummary$CreationTime' => 'The date and time that the Git repository was created.
', 'CompilationJobSummary$CreationTime' => 'The time when the model compilation job was created.
', 'DescribeAlgorithmOutput$CreationTime' => 'A timestamp specifying when the algorithm was created.
', 'DescribeCodeRepositoryOutput$CreationTime' => 'The date and time that the repository was created.
', 'DescribeCompilationJobResponse$CreationTime' => 'The time that the model compilation job was created.
', 'DescribeDomainResponse$CreationTime' => 'The creation time.
', 'DescribeFeatureGroupResponse$CreationTime' => 'A timestamp indicating when SageMaker created the FeatureGroup
.
A timestamp indicating when the feature was created.
', 'DescribeInferenceRecommendationsJobResponse$CreationTime' => 'A timestamp that shows when the job was created.
', 'DescribeModelPackageGroupOutput$CreationTime' => 'The time that the model group was created.
', 'DescribeModelPackageOutput$CreationTime' => 'A timestamp specifying when the model package was created.
', 'DescribeNotebookInstanceLifecycleConfigOutput$CreationTime' => 'A timestamp that tells when the lifecycle configuration was created.
', 'DescribeNotebookInstanceOutput$CreationTime' => 'A timestamp. Use this parameter to return the time when the notebook instance was created
', 'DescribeSpaceResponse$CreationTime' => 'The creation time.
', 'DescribeUserProfileResponse$CreationTime' => 'The creation time.
', 'DomainDetails$CreationTime' => 'The creation time.
', 'FeatureGroup$CreationTime' => 'The time a FeatureGroup
was created.
A timestamp indicating when the feature was created.
', 'InferenceRecommendationsJob$CreationTime' => 'A timestamp that shows when the job was created.
', 'ListAlgorithmsInput$CreationTimeAfter' => 'A filter that returns only algorithms created after the specified time (timestamp).
', 'ListAlgorithmsInput$CreationTimeBefore' => 'A filter that returns only algorithms created before the specified time (timestamp).
', 'ListCodeRepositoriesInput$CreationTimeAfter' => 'A filter that returns only Git repositories that were created after the specified time.
', 'ListCodeRepositoriesInput$CreationTimeBefore' => 'A filter that returns only Git repositories that were created before the specified time.
', 'ListCompilationJobsRequest$CreationTimeAfter' => 'A filter that returns the model compilation jobs that were created after a specified time.
', 'ListCompilationJobsRequest$CreationTimeBefore' => 'A filter that returns the model compilation jobs that were created before a specified time.
', 'ListFeatureGroupsRequest$CreationTimeAfter' => 'Use this parameter to search for FeatureGroups
s created after a specific date and time.
Use this parameter to search for FeatureGroups
s created before a specific date and time.
A filter that returns only jobs created after the specified time (timestamp).
', 'ListInferenceRecommendationsJobsRequest$CreationTimeBefore' => 'A filter that returns only jobs created before the specified time (timestamp).
', 'ListModelPackageGroupsInput$CreationTimeAfter' => 'A filter that returns only model groups created after the specified time.
', 'ListModelPackageGroupsInput$CreationTimeBefore' => 'A filter that returns only model groups created before the specified time.
', 'ListModelPackagesInput$CreationTimeAfter' => 'A filter that returns only model packages created after the specified time (timestamp).
', 'ListModelPackagesInput$CreationTimeBefore' => 'A filter that returns only model packages created before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$CreationTimeBefore' => 'A filter that returns only lifecycle configurations that were created before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$CreationTimeAfter' => 'A filter that returns only lifecycle configurations that were created after the specified time (timestamp).
', 'ListNotebookInstancesInput$CreationTimeBefore' => 'A filter that returns only notebook instances that were created before the specified time (timestamp).
', 'ListNotebookInstancesInput$CreationTimeAfter' => 'A filter that returns only notebook instances that were created after the specified time (timestamp).
', 'ModelPackage$CreationTime' => 'The time that the model package was created.
', 'ModelPackageGroup$CreationTime' => 'The time that the model group was created.
', 'ModelPackageGroupSummary$CreationTime' => 'The time that the model group was created.
', 'ModelPackageSummary$CreationTime' => 'A timestamp that shows when the model package was created.
', 'NotebookInstanceLifecycleConfigSummary$CreationTime' => 'A timestamp that tells when the lifecycle configuration was created.
', 'NotebookInstanceSummary$CreationTime' => 'A timestamp that shows when the notebook instance was created.
', 'SpaceDetails$CreationTime' => 'The creation time.
', 'UserProfileDetails$CreationTime' => 'The creation time.
', ], ], 'CrossAccountFilterOption' => [ 'base' => NULL, 'refs' => [ 'SearchRequest$CrossAccountFilterOption' => ' A cross account filter option. When the value is "CrossAccount"
the search results will only include resources made discoverable to you from other accounts. When the value is "SameAccount"
or null
the search results will only include resources from your account. Default is null
. For more information on searching for resources made discoverable to your account, see Search discoverable resources in the SageMaker Developer Guide. The maximum number of ResourceCatalog
s viewable is 1000.
The list of all content type headers that Amazon SageMaker will treat as CSV and capture accordingly.
', ], ], 'CustomFileSystem' => [ 'base' => 'A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
', 'refs' => [ 'CustomFileSystems$member' => NULL, ], ], 'CustomFileSystemConfig' => [ 'base' => 'The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
', 'refs' => [ 'CustomFileSystemConfigs$member' => NULL, ], ], 'CustomFileSystemConfigs' => [ 'base' => NULL, 'refs' => [ 'UserSettings$CustomFileSystemConfigs' => 'The settings for assigning a custom file system to a user profile. Permitted users can access this file system in Amazon SageMaker Studio.
', ], ], 'CustomFileSystems' => [ 'base' => NULL, 'refs' => [ 'SpaceSettings$CustomFileSystems' => 'A file system, created by you, that you assign to a space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
', ], ], 'CustomImage' => [ 'base' => 'A custom SageMaker image. For more information, see Bring your own SageMaker image.
', 'refs' => [ 'CustomImages$member' => NULL, ], ], 'CustomImageContainerArguments' => [ 'base' => NULL, 'refs' => [ 'ContainerConfig$ContainerArguments' => 'The arguments for the container when you\'re running the application.
', ], ], 'CustomImageContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'ContainerConfig$ContainerEntrypoint' => 'The entrypoint used to run the application in the container.
', ], ], 'CustomImageContainerEnvironmentVariables' => [ 'base' => NULL, 'refs' => [ 'ContainerConfig$ContainerEnvironmentVariables' => 'The environment variables to set in the container
', ], ], 'CustomImages' => [ 'base' => NULL, 'refs' => [ 'JupyterLabAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a JupyterLab app.
', 'KernelGatewayAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a KernelGateway app.
', 'RSessionAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a RSession app.
', ], ], 'CustomPosixUserConfig' => [ 'base' => 'Details about the POSIX identity that is used for file system operations.
', 'refs' => [ 'UserSettings$CustomPosixUserConfig' => 'Details about the POSIX identity that is used for file system operations.
', ], ], 'CustomerMetadataKey' => [ 'base' => NULL, 'refs' => [ 'CustomerMetadataKeyList$member' => NULL, 'CustomerMetadataMap$key' => NULL, ], ], 'CustomerMetadataKeyList' => [ 'base' => NULL, 'refs' => [ 'UpdateModelPackageInput$CustomerMetadataPropertiesToRemove' => 'The metadata properties associated with the model package versions to remove.
', ], ], 'CustomerMetadataMap' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', 'DescribeModelPackageOutput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', 'ModelPackage$CustomerMetadataProperties' => 'The metadata properties for the model package.
', 'UpdateModelPackageInput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', ], ], 'CustomerMetadataValue' => [ 'base' => NULL, 'refs' => [ 'CustomerMetadataMap$value' => NULL, ], ], 'CustomizedMetricSpecification' => [ 'base' => 'A customized metric.
', 'refs' => [ 'MetricSpecification$Customized' => 'Information about a customized metric.
', ], ], 'DataCaptureConfig' => [ 'base' => 'Configuration to control how SageMaker captures inference data.
', 'refs' => [ 'CreateEndpointConfigInput$DataCaptureConfig' => NULL, 'DescribeEndpointConfigOutput$DataCaptureConfig' => NULL, ], ], 'DataCaptureConfigSummary' => [ 'base' => 'The currently active data capture configuration used by your Endpoint.
', 'refs' => [ 'DescribeEndpointOutput$DataCaptureConfig' => NULL, 'Endpoint$DataCaptureConfig' => NULL, ], ], 'DataCatalogConfig' => [ 'base' => 'The meta data of the Glue table which serves as data catalog for the OfflineStore
.
The meta data of the Glue table that is autogenerated when an OfflineStore
is created.
Whether the generated dataset is FullyReplicated
or ShardedByS3Key
(default).
The URL of the notebook location.
', ], ], 'DataInputConfig' => [ 'base' => NULL, 'refs' => [ 'DerivedInformation$DerivedDataInputConfig' => 'The data input configuration that SageMaker Neo automatically derived for the model. When SageMaker Neo derives this information, you don\'t need to specify the data input configuration when you create a compilation job.
', 'InputConfig$DataInputConfig' => 'Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are Framework
specific.
TensorFlow
: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"input":[1,1024,1024,3]}
If using the CLI, {\\"input\\":[1,1024,1024,3]}
Examples for two inputs:
If using the console, {"data1": [1,28,28,1], "data2":[1,28,28,1]}
If using the CLI, {\\"data1\\": [1,28,28,1], \\"data2\\":[1,28,28,1]}
KERAS
: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig
should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"input_1":[1,3,224,224]}
If using the CLI, {\\"input_1\\":[1,3,224,224]}
Examples for two inputs:
If using the console, {"input_1": [1,3,224,224], "input_2":[1,3,224,224]}
If using the CLI, {\\"input_1\\": [1,3,224,224], \\"input_2\\":[1,3,224,224]}
MXNET/ONNX/DARKNET
: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"data":[1,3,1024,1024]}
If using the CLI, {\\"data\\":[1,3,1024,1024]}
Examples for two inputs:
If using the console, {"var1": [1,1,28,28], "var2":[1,1,28,28]}
If using the CLI, {\\"var1\\": [1,1,28,28], \\"var2\\":[1,1,28,28]}
PyTorch
: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.
Examples for one input in dictionary format:
If using the console, {"input0":[1,3,224,224]}
If using the CLI, {\\"input0\\":[1,3,224,224]}
Example for one input in list format: [[1,3,224,224]]
Examples for two inputs in dictionary format:
If using the console, {"input0":[1,3,224,224], "input1":[1,3,224,224]}
If using the CLI, {\\"input0\\":[1,3,224,224], \\"input1\\":[1,3,224,224]}
Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]
XGBOOST
: input data name and shape are not needed.
DataInputConfig
supports the following parameters for CoreML
TargetDevice
(ML Model format):
shape
: Input shape, for example {"input_1": {"shape": [1,224,224,3]}}
. In addition to static input shapes, CoreML converter supports Flexible input shapes:
Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: {"input_1": {"shape": ["1..10", 224, 224, 3]}}
Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: {"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]}}
default_shape
: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example {"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]}}
type
: Input type. Allowed values: Image
and Tensor
. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias
and scale
.
bias
: If the input type is an Image, you need to provide the bias vector.
scale
: If the input type is an Image, you need to provide a scale factor.
CoreML ClassifierConfig
parameters can be specified using OutputConfig CompilerOptions
. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:
Tensor type input:
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]}}
Tensor type input without input name (PyTorch):
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]}]
Image type input:
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}}
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
Image type input without input name (PyTorch):
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}]
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
Depending on the model format, DataInputConfig
requires the following parameters for ml_eia2
OutputConfig:TargetDevice.
For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key
and the input model shapes for DataInputConfig
. Specify the signature_def_key
in OutputConfig:CompilerOptions
if the model does not use TensorFlow\'s default signature def key. For example:
"DataInputConfig": {"inputs": [1, 224, 224, 3]}
"CompilerOptions": {"signature_def_key": "serving_custom"}
For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig
and the output tensor names for output_names
in OutputConfig:CompilerOptions
. For example:
"DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]}
"CompilerOptions": {"output_names": ["output_tensor:0"]}
The input configuration object for the model.
', ], ], 'DataProcessing' => [ 'base' => 'The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
', 'refs' => [ 'CreateTransformJobRequest$DataProcessing' => 'The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
', 'DescribeTransformJobResponse$DataProcessing' => NULL, 'TransformJob$DataProcessing' => NULL, ], ], 'DataQualityAppSpecification' => [ 'base' => 'Information about the container that a data quality monitoring job runs.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityAppSpecification' => 'Specifies the container that runs the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityAppSpecification' => 'Information about the container that runs the data quality monitoring job.
', ], ], 'DataQualityBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityBaselineConfig' => 'Configures the constraints and baselines for the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityBaselineConfig' => 'The constraints and baselines for the data quality monitoring job definition.
', ], ], 'DataQualityJobInput' => [ 'base' => 'The input for the data quality monitoring job. Currently endpoints are supported for input.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityJobInput' => 'A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityJobInput' => 'The list of inputs for the data quality monitoring job. Currently endpoints are supported.
', ], ], 'DataSource' => [ 'base' => 'Describes the location of the channel data.
', 'refs' => [ 'Channel$DataSource' => 'The location of the channel data.
', ], ], 'DataSourceName' => [ 'base' => NULL, 'refs' => [ 'IdentityProviderOAuthSetting$DataSourceName' => 'The name of the data source that you\'re connecting to. Canvas currently supports OAuth for Snowflake and Salesforce Data Cloud.
', ], ], 'Database' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$Database' => 'The name of the Glue table database.
', ], ], 'DatasetDefinition' => [ 'base' => 'Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition
or RedshiftDatasetDefinition
types.
Configuration for a Dataset Definition input.
', ], ], 'DebugHookConfig' => [ 'base' => 'Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
', 'DescribeTrainingJobResponse$DebugRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
', 'TrainingJob$DebugRuleConfigurations' => 'Information about the debug rule configuration.
', ], ], 'DebugRuleEvaluationStatus' => [ 'base' => 'Information about the status of the rule evaluation.
', 'refs' => [ 'DebugRuleEvaluationStatuses$member' => NULL, ], ], 'DebugRuleEvaluationStatuses' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$DebugRuleEvaluationStatuses' => 'Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
', 'TrainingJob$DebugRuleEvaluationStatuses' => 'Information about the evaluation status of the rules for the training job.
', ], ], 'DefaultEbsStorageSettings' => [ 'base' => 'A collection of default EBS storage settings that applies to private spaces created within a domain or user profile.
', 'refs' => [ 'DefaultSpaceStorageSettings$DefaultEbsStorageSettings' => 'The default EBS storage settings for a private space.
', ], ], 'DefaultGid' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$DefaultGid' => 'The default POSIX group ID (GID). If not specified, defaults to 100
.
A collection of settings that apply to spaces created in the Domain.
', 'refs' => [ 'CreateDomainRequest$DefaultSpaceSettings' => 'The default settings used to create a space.
', 'DescribeDomainResponse$DefaultSpaceSettings' => 'The default settings used to create a space.
', 'UpdateDomainRequest$DefaultSpaceSettings' => 'The default settings used to create a space within the Domain.
', ], ], 'DefaultSpaceStorageSettings' => [ 'base' => 'The default storage settings for a private space.
', 'refs' => [ 'UserSettings$SpaceStorageSettings' => 'The storage settings for a private space.
', ], ], 'DefaultUid' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$DefaultUid' => 'The default POSIX user ID (UID). If not specified, defaults to 1000
.
The hub content dependency copy path.
', ], ], 'DependencyOriginPath' => [ 'base' => NULL, 'refs' => [ 'HubContentDependency$DependencyOriginPath' => 'The hub content dependency origin path.
', ], ], 'DeployedImage' => [ 'base' => 'Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag]
form to specify the image path of the primary container when you created the model hosted in this ProductionVariant
, the path resolves to a path of the form registry/repository[@digest]
. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
An array of DeployedImage
objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant
.
An array of DeployedImage
objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant
.
The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
', 'refs' => [ 'CreateEndpointInput$DeploymentConfig' => NULL, 'DescribeEndpointOutput$LastDeploymentConfig' => 'The most recent deployment configuration for the endpoint.
', 'UpdateEndpointInput$DeploymentConfig' => 'The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
', ], ], 'DeploymentRecommendation' => [ 'base' => 'A set of recommended deployment configurations for the model. To get more advanced recommendations, see CreateInferenceRecommendationsJob to create an inference recommendation job.
', 'refs' => [ 'DescribeModelOutput$DeploymentRecommendation' => 'A set of recommended deployment configurations for the model.
', 'Model$DeploymentRecommendation' => 'A set of recommended deployment configurations for the model.
', ], ], 'DeploymentStage' => [ 'base' => 'Contains information about a stage in an edge deployment plan.
', 'refs' => [ 'DeploymentStages$member' => NULL, ], ], 'DeploymentStageMaxResults' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgeDeploymentPlanRequest$MaxResults' => 'The maximum number of results to select (50 by default).
', ], ], 'DeploymentStageStatusSummaries' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgeDeploymentPlanResponse$Stages' => 'List of stages in the edge deployment plan.
', ], ], 'DeploymentStageStatusSummary' => [ 'base' => 'Contains information summarizing the deployment stage results.
', 'refs' => [ 'DeploymentStageStatusSummaries$member' => NULL, ], ], 'DeploymentStages' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanRequest$Stages' => 'List of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.
', 'CreateEdgeDeploymentStageRequest$Stages' => 'List of stages to be added to the edge deployment plan.
', ], ], 'DeregisterDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'DerivedInformation' => [ 'base' => 'Information that SageMaker Neo automatically derived about the model.
', 'refs' => [ 'DescribeCompilationJobResponse$DerivedInformation' => 'Information that SageMaker Neo automatically derived about the model.
', ], ], 'DescribeActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAlgorithmInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAlgorithmOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobV2Request' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobV2Response' => [ 'base' => NULL, 'refs' => [], ], 'DescribeClusterNodeRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeClusterNodeResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeClusterRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeClusterResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCompilationJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDataQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDataQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceFleetResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgeDeploymentPlanRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgeDeploymentPlanResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgePackagingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureMetadataResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFlowDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFlowDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubContentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubContentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHumanTaskUiRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHumanTaskUiResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceComponentInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceComponentOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceRecommendationsJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLabelingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLineageGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLineageGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelBiasJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelBiasJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardExportJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardExportJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelExplainabilityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelExplainabilityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageGroupInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageGroupOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineDefinitionForExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineDefinitionForExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProcessingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStudioLifecycleConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStudioLifecycleConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSubscribedWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSubscribedWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTransformJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'Description' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupRequest$Description' => 'A free-form description of a FeatureGroup
.
A free form description of the feature group.
', 'FeatureGroup$Description' => 'A free form description of a FeatureGroup
.
Specifies weight and capacity values for a production variant.
', 'refs' => [ 'DesiredWeightAndCapacityList$member' => NULL, ], ], 'DesiredWeightAndCapacityList' => [ 'base' => NULL, 'refs' => [ 'UpdateEndpointWeightsAndCapacitiesInput$DesiredWeightsAndCapacities' => 'An object that provides new capacity and weight values for a variant.
', ], ], 'DestinationS3Uri' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceOutputConfig$S3OutputPath' => 'The Amazon S3 location to upload inference responses to.
', 'AsyncInferenceOutputConfig$S3FailurePath' => 'The Amazon S3 location to upload failure inference responses to.
', 'BatchTransformInput$DataCapturedDestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'DataCaptureConfig$DestinationS3Uri' => 'The Amazon S3 location used to capture the data.
', 'DataCaptureConfigSummary$DestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'InferenceExperimentDataStorageConfig$Destination' => 'The Amazon S3 bucket where the inference request and response data is stored.
', 'ProductionVariantCoreDumpConfig$DestinationS3Uri' => 'The Amazon S3 bucket to send the core dump to.
', ], ], 'DetailedAlgorithmStatus' => [ 'base' => NULL, 'refs' => [ 'AlgorithmStatusItem$Status' => 'The current status.
', ], ], 'DetailedModelPackageStatus' => [ 'base' => NULL, 'refs' => [ 'ModelPackageStatusItem$Status' => 'The current status.
', ], ], 'Device' => [ 'base' => 'Information of a particular device.
', 'refs' => [ 'Devices$member' => NULL, ], ], 'DeviceArn' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$DeviceArn' => 'The Amazon Resource Name (ARN) of the device.
', 'DeviceDeploymentSummary$DeviceArn' => 'The ARN of the device.
', 'DeviceSummary$DeviceArn' => 'Amazon Resource Name (ARN) of the device.
', ], ], 'DeviceDeploymentStatus' => [ 'base' => NULL, 'refs' => [ 'DeviceDeploymentSummary$DeviceDeploymentStatus' => 'The deployment status of the device.
', ], ], 'DeviceDeploymentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListStageDevicesResponse$DeviceDeploymentSummaries' => 'List of summaries of devices allocated to the stage.
', ], ], 'DeviceDeploymentSummary' => [ 'base' => 'Contains information summarizing device details and deployment status.
', 'refs' => [ 'DeviceDeploymentSummaries$member' => NULL, ], ], 'DeviceDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$Description' => 'A description of the device.
', 'Device$Description' => 'Description of the device.
', 'DeviceDeploymentSummary$Description' => 'The description of the device.
', 'DeviceSummary$Description' => 'A description of the device.
', ], ], 'DeviceFleetArn' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceFleetResponse$DeviceFleetArn' => 'The The Amazon Resource Name (ARN) of the fleet.
', 'DeviceFleetSummary$DeviceFleetArn' => 'Amazon Resource Name (ARN) of the device fleet.
', 'GetDeviceFleetReportResponse$DeviceFleetArn' => 'The Amazon Resource Name (ARN) of the device.
', ], ], 'DeviceFleetDescription' => [ 'base' => NULL, 'refs' => [ 'CreateDeviceFleetRequest$Description' => 'A description of the fleet.
', 'DescribeDeviceFleetResponse$Description' => 'A description of the fleet.
', 'GetDeviceFleetReportResponse$Description' => 'Description of the fleet.
', 'UpdateDeviceFleetRequest$Description' => 'Description of the fleet.
', ], ], 'DeviceFleetSummaries' => [ 'base' => NULL, 'refs' => [ 'ListDeviceFleetsResponse$DeviceFleetSummaries' => 'Summary of the device fleet.
', ], ], 'DeviceFleetSummary' => [ 'base' => 'Summary of the device fleet.
', 'refs' => [ 'DeviceFleetSummaries$member' => NULL, ], ], 'DeviceName' => [ 'base' => NULL, 'refs' => [ 'Device$DeviceName' => 'The name of the device.
', 'DeviceDeploymentSummary$DeviceName' => 'The name of the device.
', 'DeviceNames$member' => NULL, 'DeviceSelectionConfig$DeviceNameContains' => 'A filter to select devices with names containing this name.
', ], ], 'DeviceNames' => [ 'base' => NULL, 'refs' => [ 'DeregisterDevicesRequest$DeviceNames' => 'The unique IDs of the devices.
', 'DeviceSelectionConfig$DeviceNames' => 'List of devices chosen to deploy.
', ], ], 'DeviceSelectionConfig' => [ 'base' => 'Contains information about the configurations of selected devices.
', 'refs' => [ 'DeploymentStage$DeviceSelectionConfig' => 'Configuration of the devices in the stage.
', 'DeploymentStageStatusSummary$DeviceSelectionConfig' => 'Configuration of the devices in the stage.
', ], ], 'DeviceStats' => [ 'base' => 'Status of devices.
', 'refs' => [ 'GetDeviceFleetReportResponse$DeviceStats' => 'Status of devices.
', ], ], 'DeviceSubsetType' => [ 'base' => NULL, 'refs' => [ 'DeviceSelectionConfig$DeviceSubsetType' => 'Type of device subsets to deploy to the current stage.
', ], ], 'DeviceSummaries' => [ 'base' => NULL, 'refs' => [ 'ListDevicesResponse$DeviceSummaries' => 'Summary of devices.
', ], ], 'DeviceSummary' => [ 'base' => 'Summary of the device.
', 'refs' => [ 'DeviceSummaries$member' => NULL, ], ], 'Devices' => [ 'base' => NULL, 'refs' => [ 'RegisterDevicesRequest$Devices' => 'A list of devices to register with SageMaker Edge Manager.
', 'UpdateDevicesRequest$Devices' => 'List of devices to register with Edge Manager agent.
', ], ], 'Dimension' => [ 'base' => NULL, 'refs' => [ 'VectorConfig$Dimension' => 'The number of elements in your vector.
', ], ], 'DirectDeploySettings' => [ 'base' => 'The model deployment settings for the SageMaker Canvas application.
In order to enable model deployment for Canvas, the SageMaker Domain\'s or user profile\'s Amazon Web Services IAM execution role must have the AmazonSageMakerCanvasDirectDeployAccess
policy attached. You can also turn on model deployment permissions through the SageMaker Domain\'s or user profile\'s settings in the SageMaker console.
The model deployment settings for the SageMaker Canvas application.
', ], ], 'DirectInternetAccess' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$DirectInternetAccess' => 'Sets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled
this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled
only if you set a value for the SubnetId
parameter.
Describes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.
For more information, see Notebook Instances Are Internet-Enabled by Default.
', ], ], 'Direction' => [ 'base' => NULL, 'refs' => [ 'QueryLineageRequest$Direction' => 'Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.
', ], ], 'DirectoryPath' => [ 'base' => NULL, 'refs' => [ 'CheckpointConfig$LocalPath' => '(Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/
.
Path to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/
.
Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/
.
The full path to the directory to associate with the channel.
', 'ProfilerRuleConfiguration$LocalPath' => 'Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/
.
Path to local storage location for tensorBoard output. Defaults to /opt/ml/output/tensorboard
.
Configuration to turn off Amazon SageMaker Debugger\'s system monitoring and profiling functionality. To turn it off, set to True
.
To turn off Amazon SageMaker Debugger monitoring and profiling while a training job is in progress, set to True
.
A list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateDefaultCodeRepository' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateDefaultCodeRepository' => 'The name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateNotebookInstanceAcceleratorTypes' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateAcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types to remove from this notebook instance. This operation is idempotent. If you specify an accelerator type that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateNotebookInstanceLifecycleConfig' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateLifecycleConfig' => 'Set to true
to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.
A collection of settings that configure the domain\'s Docker interaction.
', 'refs' => [ 'DomainSettings$DockerSettings' => 'A collection of settings that configure the domain\'s Docker interaction.
', 'DomainSettingsForUpdate$DockerSettings' => 'A collection of settings that configure the domain\'s Docker interaction.
', ], ], 'DocumentSchemaVersion' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$DocumentSchemaVersion' => 'The document schema version for the hub content.
', 'HubContentInfo$DocumentSchemaVersion' => 'The version of the hub content document schema.
', 'ImportHubContentRequest$DocumentSchemaVersion' => 'The version of the hub content schema to import.
', 'ListHubContentVersionsRequest$MaxSchemaVersion' => 'The upper bound of the hub content schema version.
', 'ListHubContentsRequest$MaxSchemaVersion' => 'The upper bound of the hub content schema verion.
', ], ], 'Dollars' => [ 'base' => NULL, 'refs' => [ 'USD$Dollars' => 'The whole number of dollars in the amount.
', ], ], 'DomainArn' => [ 'base' => NULL, 'refs' => [ 'CreateDomainResponse$DomainArn' => 'The Amazon Resource Name (ARN) of the created domain.
', 'DescribeDomainResponse$DomainArn' => 'The domain\'s Amazon Resource Name (ARN).
', 'DomainDetails$DomainArn' => 'The domain\'s Amazon Resource Name (ARN).
', 'UpdateDomainResponse$DomainArn' => 'The Amazon Resource Name (ARN) of the domain.
', ], ], 'DomainDetails' => [ 'base' => 'The domain\'s details.
', 'refs' => [ 'DomainList$member' => NULL, ], ], 'DomainId' => [ 'base' => NULL, 'refs' => [ 'AppDetails$DomainId' => 'The domain ID.
', 'CreateAppRequest$DomainId' => 'The domain ID.
', 'CreatePresignedDomainUrlRequest$DomainId' => 'The domain ID.
', 'CreateSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'CreateUserProfileRequest$DomainId' => 'The ID of the associated Domain.
', 'DeleteAppRequest$DomainId' => 'The domain ID.
', 'DeleteDomainRequest$DomainId' => 'The domain ID.
', 'DeleteSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'DeleteUserProfileRequest$DomainId' => 'The domain ID.
', 'DescribeAppRequest$DomainId' => 'The domain ID.
', 'DescribeAppResponse$DomainId' => 'The domain ID.
', 'DescribeDomainRequest$DomainId' => 'The domain ID.
', 'DescribeDomainResponse$DomainId' => 'The domain ID.
', 'DescribeSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'DescribeSpaceResponse$DomainId' => 'The ID of the associated Domain.
', 'DescribeUserProfileRequest$DomainId' => 'The domain ID.
', 'DescribeUserProfileResponse$DomainId' => 'The ID of the domain that contains the profile.
', 'DomainDetails$DomainId' => 'The domain ID.
', 'ListAppsRequest$DomainIdEquals' => 'A parameter to search for the domain ID.
', 'ListSpacesRequest$DomainIdEquals' => 'A parameter to search for the Domain ID.
', 'ListUserProfilesRequest$DomainIdEquals' => 'A parameter by which to filter the results.
', 'SpaceDetails$DomainId' => 'The ID of the associated Domain.
', 'UpdateDomainRequest$DomainId' => 'The ID of the domain to be updated.
', 'UpdateSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'UpdateUserProfileRequest$DomainId' => 'The domain ID.
', 'UserProfileDetails$DomainId' => 'The domain ID.
', ], ], 'DomainList' => [ 'base' => NULL, 'refs' => [ 'ListDomainsResponse$Domains' => 'The list of domains.
', ], ], 'DomainName' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$DomainName' => 'A name for the domain.
', 'DescribeDomainResponse$DomainName' => 'The domain name.
', 'DomainDetails$DomainName' => 'The domain name.
', ], ], 'DomainSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'DomainSettings$SecurityGroupIds' => 'The security groups for the Amazon Virtual Private Cloud that the Domain
uses for communication between Domain-level apps and user apps.
The security groups for the Amazon Virtual Private Cloud that the Domain
uses for communication between Domain-level apps and user apps.
A collection of settings that apply to the SageMaker Domain
. These settings are specified through the CreateDomain
API call.
A collection of Domain
settings.
A collection of Domain
settings.
A collection of Domain
configuration settings to update.
A collection of DomainSettings
configuration values to update.
The status.
', 'DomainDetails$Status' => 'The status.
', ], ], 'Double' => [ 'base' => NULL, 'refs' => [ 'TargetTrackingScalingPolicyConfiguration$TargetValue' => 'The recommended target value to specify for the metric when creating a scaling policy.
', ], ], 'DoubleParameterValue' => [ 'base' => NULL, 'refs' => [ 'TrialComponentParameterValue$NumberValue' => 'The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can\'t specify the StringValue
parameter.
Represents the drift check baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'CreateModelPackageInput$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
', 'DescribeModelPackageOutput$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
', 'ModelPackage$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckBias' => [ 'base' => 'Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$Bias' => 'Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckExplainability' => [ 'base' => 'Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$Explainability' => 'Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckModelDataQuality' => [ 'base' => 'Represents the drift check data quality baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$ModelDataQuality' => 'Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckModelQuality' => [ 'base' => 'Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$ModelQuality' => 'Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
', ], ], 'DynamicScalingConfiguration' => [ 'base' => 'An object with the recommended values for you to specify when creating an autoscaling policy.
', 'refs' => [ 'GetScalingConfigurationRecommendationResponse$DynamicScalingConfiguration' => 'An object with the recommended values for you to specify when creating an autoscaling policy.
', ], ], 'EFSFileSystem' => [ 'base' => 'A file system, created by you in Amazon EFS, that you assign to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
', 'refs' => [ 'CustomFileSystem$EFSFileSystem' => 'A custom file system in Amazon EFS.
', ], ], 'EFSFileSystemConfig' => [ 'base' => 'The settings for assigning a custom Amazon EFS file system to a user profile or space for an Amazon SageMaker Domain.
', 'refs' => [ 'CustomFileSystemConfig$EFSFileSystemConfig' => 'The settings for a custom Amazon EFS file system.
', ], ], 'EMRStepMetadata' => [ 'base' => 'The configurations and outcomes of an Amazon EMR step execution.
', 'refs' => [ 'PipelineExecutionStepMetadata$EMR' => 'The configurations and outcomes of an Amazon EMR step execution.
', ], ], 'EbsStorageSettings' => [ 'base' => 'A collection of EBS storage settings that applies to private spaces.
', 'refs' => [ 'SpaceStorageSettings$EbsStorageSettings' => 'A collection of EBS storage settings for a private space.
', ], ], 'Edge' => [ 'base' => 'A directed edge connecting two lineage entities.
', 'refs' => [ 'Edges$member' => NULL, ], ], 'EdgeDeploymentConfig' => [ 'base' => 'Contains information about the configuration of a deployment.
', 'refs' => [ 'DeploymentStage$DeploymentConfig' => 'Configuration of the deployment details.
', 'DeploymentStageStatusSummary$DeploymentConfig' => 'Configuration of the deployment details.
', ], ], 'EdgeDeploymentModelConfig' => [ 'base' => 'Contains information about the configuration of a model in a deployment.
', 'refs' => [ 'EdgeDeploymentModelConfigs$member' => NULL, ], ], 'EdgeDeploymentModelConfigs' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanRequest$ModelConfigs' => 'List of models associated with the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$ModelConfigs' => 'List of models associated with the edge deployment plan.
', ], ], 'EdgeDeploymentPlanArn' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanResponse$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPlanArn' => 'The ARN of edge deployment plan.
', 'DeviceDeploymentSummary$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', ], ], 'EdgeDeploymentPlanSummaries' => [ 'base' => NULL, 'refs' => [ 'ListEdgeDeploymentPlansResponse$EdgeDeploymentPlanSummaries' => 'List of summaries of edge deployment plans.
', ], ], 'EdgeDeploymentPlanSummary' => [ 'base' => 'Contains information summarizing an edge deployment plan.
', 'refs' => [ 'EdgeDeploymentPlanSummaries$member' => NULL, ], ], 'EdgeDeploymentStatus' => [ 'base' => 'Contains information summarizing the deployment stage results.
', 'refs' => [ 'DeploymentStageStatusSummary$DeploymentStatus' => 'General status of the current state.
', ], ], 'EdgeModel' => [ 'base' => 'The model on the edge device.
', 'refs' => [ 'EdgeModels$member' => NULL, ], ], 'EdgeModelStat' => [ 'base' => 'Status of edge devices with this model.
', 'refs' => [ 'EdgeModelStats$member' => NULL, ], ], 'EdgeModelStats' => [ 'base' => NULL, 'refs' => [ 'GetDeviceFleetReportResponse$ModelStats' => 'Status of model on device.
', ], ], 'EdgeModelSummaries' => [ 'base' => NULL, 'refs' => [ 'DeviceSummary$Models' => 'Models on the device.
', ], ], 'EdgeModelSummary' => [ 'base' => 'Summary of model on edge device.
', 'refs' => [ 'EdgeModelSummaries$member' => NULL, ], ], 'EdgeModels' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$Models' => 'Models on the device.
', ], ], 'EdgeOutputConfig' => [ 'base' => 'The output configuration.
', 'refs' => [ 'CreateDeviceFleetRequest$OutputConfig' => 'The output configuration for storing sample data collected by the fleet.
', 'CreateEdgePackagingJobRequest$OutputConfig' => 'Provides information about the output location for the packaged model.
', 'DescribeDeviceFleetResponse$OutputConfig' => 'The output configuration for storing sampled data.
', 'DescribeEdgePackagingJobResponse$OutputConfig' => 'The output configuration for the edge packaging job.
', 'GetDeviceFleetReportResponse$OutputConfig' => 'The output configuration for storing sample data collected by the fleet.
', 'UpdateDeviceFleetRequest$OutputConfig' => 'Output configuration for storing sample data collected by the fleet.
', ], ], 'EdgePackagingJobArn' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgePackagingJobResponse$EdgePackagingJobArn' => 'The Amazon Resource Name (ARN) of the edge packaging job.
', 'EdgePackagingJobSummary$EdgePackagingJobArn' => 'The Amazon Resource Name (ARN) of the edge packaging job.
', ], ], 'EdgePackagingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgePackagingJobResponse$EdgePackagingJobStatus' => 'The current status of the packaging job.
', 'EdgePackagingJobSummary$EdgePackagingJobStatus' => 'The status of the edge packaging job.
', 'ListEdgePackagingJobsRequest$StatusEquals' => 'The job status to filter for.
', ], ], 'EdgePackagingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListEdgePackagingJobsResponse$EdgePackagingJobSummaries' => 'Summaries of edge packaging jobs.
', ], ], 'EdgePackagingJobSummary' => [ 'base' => 'Summary of edge packaging job.
', 'refs' => [ 'EdgePackagingJobSummaries$member' => NULL, ], ], 'EdgePresetDeploymentArtifact' => [ 'base' => NULL, 'refs' => [ 'EdgePresetDeploymentOutput$Artifact' => 'The Amazon Resource Name (ARN) of the generated deployable resource.
', ], ], 'EdgePresetDeploymentOutput' => [ 'base' => 'The output of a SageMaker Edge Manager deployable resource.
', 'refs' => [ 'DescribeEdgePackagingJobResponse$PresetDeploymentOutput' => 'The output of a SageMaker Edge Manager deployable resource.
', ], ], 'EdgePresetDeploymentStatus' => [ 'base' => NULL, 'refs' => [ 'EdgePresetDeploymentOutput$Status' => 'The status of the deployable resource.
', ], ], 'EdgePresetDeploymentType' => [ 'base' => NULL, 'refs' => [ 'EdgeOutputConfig$PresetDeploymentType' => 'The deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
', 'EdgePresetDeploymentOutput$Type' => 'The deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
', ], ], 'EdgeVersion' => [ 'base' => NULL, 'refs' => [ 'AgentVersion$Version' => 'Version of the agent.
', 'CreateEdgePackagingJobRequest$ModelVersion' => 'The version of the model.
', 'DescribeDeviceResponse$AgentVersion' => 'Edge Manager agent version.
', 'DescribeEdgePackagingJobResponse$ModelVersion' => 'The version of the model.
', 'DeviceSummary$AgentVersion' => 'Edge Manager agent version.
', 'EdgeModel$ModelVersion' => 'The model version.
', 'EdgeModelStat$ModelVersion' => 'The model version.
', 'EdgeModelSummary$ModelVersion' => 'The version model.
', 'EdgePackagingJobSummary$ModelVersion' => 'The version of the model.
', ], ], 'Edges' => [ 'base' => NULL, 'refs' => [ 'QueryLineageResponse$Edges' => 'A list of edges that connect vertices in the response.
', ], ], 'EfsUid' => [ 'base' => NULL, 'refs' => [ 'DescribeSpaceResponse$HomeEfsFileSystemUid' => 'The ID of the space\'s profile in the Amazon Elastic File System volume.
', 'DescribeUserProfileResponse$HomeEfsFileSystemUid' => 'The ID of the user\'s profile in the Amazon Elastic File System (EFS) volume.
', ], ], 'EnableCapture' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$EnableCapture' => 'Whether data capture should be enabled or disabled (defaults to enabled).
', 'DataCaptureConfigSummary$EnableCapture' => 'Whether data capture is enabled or disabled.
', ], ], 'EnableInfraCheck' => [ 'base' => NULL, 'refs' => [ 'InfraCheckConfig$EnableInfraCheck' => 'Enables an infrastructure health check.
', ], ], 'EnableIotRoleAlias' => [ 'base' => NULL, 'refs' => [ 'CreateDeviceFleetRequest$EnableIotRoleAlias' => 'Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
', 'UpdateDeviceFleetRequest$EnableIotRoleAlias' => 'Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
', ], ], 'EnableRemoteDebug' => [ 'base' => NULL, 'refs' => [ 'RemoteDebugConfig$EnableRemoteDebug' => 'If set to True, enables remote debugging.
', 'RemoteDebugConfigForUpdate$EnableRemoteDebug' => 'If set to True, enables remote debugging.
', ], ], 'EnableSagemakerServicecatalogPortfolioInput' => [ 'base' => NULL, 'refs' => [], ], 'EnableSagemakerServicecatalogPortfolioOutput' => [ 'base' => NULL, 'refs' => [], ], 'Endpoint' => [ 'base' => 'A hosted endpoint for real-time inference.
', 'refs' => [ 'SearchRecord$Endpoint' => NULL, ], ], 'EndpointArn' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'DescribeEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'DescribeInferenceComponentOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint that hosts the inference component.
', 'Endpoint$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'EndpointSummary$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'InferenceComponentSummary$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint that hosts the inference component.
', 'ModelDashboardEndpoint$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'UpdateEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'UpdateEndpointWeightsAndCapacitiesOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the updated endpoint.
', ], ], 'EndpointConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigOutput$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', 'DescribeEndpointConfigOutput$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', 'EndpointConfigSummary$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', ], ], 'EndpointConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
', 'CreateEndpointInput$EndpointConfigName' => 'The name of an endpoint configuration. For more information, see CreateEndpointConfig.
', 'DeleteEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration that you want to delete.
', 'DescribeEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration.
', 'DescribeEndpointConfigOutput$EndpointConfigName' => 'Name of the SageMaker endpoint configuration.
', 'DescribeEndpointOutput$EndpointConfigName' => 'The name of the endpoint configuration associated with this endpoint.
', 'Endpoint$EndpointConfigName' => 'The endpoint configuration associated with the endpoint.
', 'EndpointConfigSummary$EndpointConfigName' => 'The name of the endpoint configuration.
', 'EndpointMetadata$EndpointConfigName' => 'The name of the endpoint configuration.
', 'PendingDeploymentSummary$EndpointConfigName' => 'The name of the endpoint configuration used in the deployment.
', 'UpdateEndpointInput$EndpointConfigName' => 'The name of the new endpoint configuration.
', ], ], 'EndpointConfigNameContains' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$NameContains' => 'A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.
', ], ], 'EndpointConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$SortBy' => 'The field to sort results by. The default is CreationTime
.
Provides summary information for an endpoint configuration.
', 'refs' => [ 'EndpointConfigSummaryList$member' => NULL, ], ], 'EndpointConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsOutput$EndpointConfigs' => 'An array of endpoint configurations.
', ], ], 'EndpointInfo' => [ 'base' => 'Details about a customer endpoint that was compared in an Inference Recommender job.
', 'refs' => [ 'EndpointPerformance$EndpointInfo' => NULL, 'Endpoints$member' => NULL, ], ], 'EndpointInput' => [ 'base' => 'Input object for the endpoint
', 'refs' => [ 'DataQualityJobInput$EndpointInput' => NULL, 'ModelBiasJobInput$EndpointInput' => NULL, 'ModelExplainabilityJobInput$EndpointInput' => NULL, 'ModelQualityJobInput$EndpointInput' => NULL, 'MonitoringInput$EndpointInput' => 'The endpoint for a monitoring job.
', ], ], 'EndpointInputConfiguration' => [ 'base' => 'The endpoint configuration for the load test.
', 'refs' => [ 'EndpointInputConfigurations$member' => NULL, ], ], 'EndpointInputConfigurations' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$EndpointConfigurations' => 'Specifies the endpoint configuration to use for a job.
', ], ], 'EndpointMetadata' => [ 'base' => 'The metadata of the endpoint.
', 'refs' => [ 'DescribeInferenceExperimentResponse$EndpointMetadata' => 'The metadata of the endpoint on which the inference experiment ran.
', ], ], 'EndpointName' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointInput$EndpointName' => 'The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint
, but the case is preserved and must be matched in InvokeEndpoint.
The name of an existing endpoint where you host the inference component.
', 'CreateInferenceExperimentRequest$EndpointName' => 'The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.
', 'DeleteEndpointInput$EndpointName' => 'The name of the endpoint that you want to delete.
', 'DescribeEndpointInput$EndpointName' => 'The name of the endpoint.
', 'DescribeEndpointOutput$EndpointName' => 'Name of the endpoint.
', 'DescribeInferenceComponentOutput$EndpointName' => 'The name of the endpoint that hosts the inference component.
', 'DescribeMonitoringScheduleResponse$EndpointName' => 'The name of the endpoint for the monitoring job.
', 'Endpoint$EndpointName' => 'The name of the endpoint.
', 'EndpointInfo$EndpointName' => 'The name of a customer\'s endpoint.
', 'EndpointInput$EndpointName' => 'An endpoint in customer\'s account which has enabled DataCaptureConfig
enabled.
The name of the endpoint.
', 'EndpointSummary$EndpointName' => 'The name of the endpoint.
', 'GetScalingConfigurationRecommendationRequest$EndpointName' => 'The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName
field.
Specify either this field or the RecommendationId
field.
The name of an endpoint benchmarked during a previously completed Inference Recommender job.
', 'InferenceComponentSummary$EndpointName' => 'The name of the endpoint that hosts the inference component.
', 'ListDataQualityJobDefinitionsRequest$EndpointName' => 'A filter that lists the data quality job definitions associated with the specified endpoint.
', 'ListInferenceComponentsInput$EndpointNameEquals' => 'An endpoint name to filter the listed inference components. The response includes only those inference components that are hosted at the specified endpoint.
', 'ListModelBiasJobDefinitionsRequest$EndpointName' => 'Name of the endpoint to monitor for model bias.
', 'ListModelExplainabilityJobDefinitionsRequest$EndpointName' => 'Name of the endpoint to monitor for model explainability.
', 'ListModelQualityJobDefinitionsRequest$EndpointName' => 'A filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.
', 'ListMonitoringExecutionsRequest$EndpointName' => 'Name of a specific endpoint to fetch jobs for.
', 'ListMonitoringSchedulesRequest$EndpointName' => 'Name of a specific endpoint to fetch schedules for.
', 'ModelDashboardEndpoint$EndpointName' => 'The endpoint name.
', 'ModelDashboardMonitoringSchedule$EndpointName' => 'The endpoint which is monitored.
', 'ModelDeployConfig$EndpointName' => 'Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically.
Specify the EndpointName
if and only if you set AutoGenerateEndpointName
to False
; otherwise a 400 error is thrown.
The name of the endpoint to which the model has been deployed.
If model deployment fails, this field is omitted from the response.
The name of the endpoint used to run the monitoring job.
', 'MonitoringJobDefinitionSummary$EndpointName' => 'The name of the endpoint that the job monitors.
', 'MonitoringSchedule$EndpointName' => 'The endpoint that hosts the model being monitored.
', 'MonitoringScheduleSummary$EndpointName' => 'The name of the endpoint using the monitoring schedule.
', 'UpdateEndpointInput$EndpointName' => 'The name of the endpoint whose configuration you want to update.
', 'UpdateEndpointWeightsAndCapacitiesInput$EndpointName' => 'The name of an existing SageMaker endpoint.
', ], ], 'EndpointNameContains' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsInput$NameContains' => 'A string in endpoint names. This filter returns only endpoints whose name contains the specified string.
', ], ], 'EndpointOutputConfiguration' => [ 'base' => 'The endpoint configuration made by Inference Recommender during a recommendation job.
', 'refs' => [ 'InferenceRecommendation$EndpointConfiguration' => 'Defines the endpoint configuration parameters.
', 'RecommendationJobInferenceBenchmark$EndpointConfiguration' => NULL, ], ], 'EndpointPerformance' => [ 'base' => 'The performance results from running an Inference Recommender job on an existing endpoint.
', 'refs' => [ 'EndpointPerformances$member' => NULL, ], ], 'EndpointPerformances' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$EndpointPerformances' => 'The performance results from running an Inference Recommender job on an existing endpoint.
', ], ], 'EndpointSortKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsInput$SortBy' => 'Sorts the list of results. The default is CreationTime
.
The status of the endpoint.
OutOfService
: Endpoint is not available to take incoming requests.
Creating
: CreateEndpoint is executing.
Updating
: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating
: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack
: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService
status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService
: Endpoint is available to process incoming requests.
Deleting
: DeleteEndpoint is executing.
Failed
: Endpoint could not be created, updated, or re-scaled. Use the FailureReason
value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
UpdateRollbackFailed
: Both the rolling deployment and auto-rollback failed. Your endpoint is in service with a mix of the old and new endpoint configurations. For information about how to remedy this issue and restore the endpoint\'s status to InService
, see Rolling Deployments.
The status of the endpoint.
', 'EndpointMetadata$EndpointStatus' => 'The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary.
', 'EndpointSummary$EndpointStatus' => 'The status of the endpoint.
OutOfService
: Endpoint is not available to take incoming requests.
Creating
: CreateEndpoint is executing.
Updating
: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating
: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack
: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService
status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService
: Endpoint is available to process incoming requests.
Deleting
: DeleteEndpoint is executing.
Failed
: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason
for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
To get a list of endpoints with a specified status, use the StatusEquals
filter with a call to ListEndpoints.
A filter that returns only endpoints with the specified status.
', 'ModelDashboardEndpoint$EndpointStatus' => 'The endpoint status.
', ], ], 'EndpointSummary' => [ 'base' => 'Provides summary information for an endpoint.
', 'refs' => [ 'EndpointSummaryList$member' => NULL, ], ], 'EndpointSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsOutput$Endpoints' => 'An array or endpoint objects.
', ], ], 'Endpoints' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$Endpoints' => 'Existing customer endpoints on which to run an Inference Recommender job.
', ], ], 'EntityDescription' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Description' => 'A description of the additional Inference specification
', 'AlgorithmSummary$AlgorithmDescription' => 'A brief description of the algorithm.
', 'BatchDescribeModelPackageSummary$ModelPackageDescription' => 'The description of the model package.
', 'ChannelSpecification$Description' => 'A brief description of the channel.
', 'CreateAlgorithmInput$AlgorithmDescription' => 'A description of the algorithm.
', 'CreateModelPackageGroupInput$ModelPackageGroupDescription' => 'A description for the model group.
', 'CreateModelPackageInput$ModelPackageDescription' => 'A description of the model package.
', 'CreateProjectInput$ProjectDescription' => 'A description for the project.
', 'DescribeAlgorithmOutput$AlgorithmDescription' => 'A brief summary about the algorithm.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupDescription' => 'A description of the model group.
', 'DescribeModelPackageOutput$ModelPackageDescription' => 'A brief summary of the model package.
', 'DescribeProjectOutput$ProjectDescription' => 'The description of the project.
', 'HyperParameterSpecification$Description' => 'A brief description of the hyperparameter.
', 'ModelPackage$ModelPackageDescription' => 'The description of the model package.
', 'ModelPackageGroup$ModelPackageGroupDescription' => 'The description for the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupDescription' => 'A description of the model group.
', 'ModelPackageSummary$ModelPackageDescription' => 'A brief description of the model package.
', 'Project$ProjectDescription' => 'The description of the project.
', 'ProjectSummary$ProjectDescription' => 'The description of the project.
', 'UpdateProjectInput$ProjectDescription' => 'The description for the project.
', ], ], 'EntityName' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Name' => 'A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
', 'AlgorithmStatusItem$Name' => 'The name of the algorithm for which the overall status is being reported.
', 'AlgorithmSummary$AlgorithmName' => 'The name of the algorithm that is described by the summary.
', 'AlgorithmValidationProfile$ProfileName' => 'The name of the profile for the algorithm. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'BatchDescribeModelPackageSummary$ModelPackageGroupName' => 'The group name for the model package
', 'CodeRepositorySummary$CodeRepositoryName' => 'The name of the Git repository.
', 'CompilationJobSummary$CompilationJobName' => 'The name of the model compilation job that you want a summary for.
', 'CreateAlgorithmInput$AlgorithmName' => 'The name of the algorithm.
', 'CreateCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'CreateCompilationJobRequest$CompilationJobName' => 'A name for the model compilation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.
', 'CreateDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet that the device belongs to.
', 'CreateEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'CreateEdgeDeploymentPlanRequest$DeviceFleetName' => 'The device fleet used for this edge deployment plan.
', 'CreateEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'CreateEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'CreateEdgePackagingJobRequest$CompilationJobName' => 'The name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.
', 'CreateEdgePackagingJobRequest$ModelName' => 'The name of the model.
', 'CreateModelCardExportJobRequest$ModelCardExportJobName' => 'The name of the model card export job.
', 'CreateModelCardRequest$ModelCardName' => 'The unique name of the model card.
', 'CreateModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group.
', 'CreateModelPackageInput$ModelPackageName' => 'The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
', 'DeleteAlgorithmInput$AlgorithmName' => 'The name of the algorithm to delete.
', 'DeleteCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to delete.
', 'DeleteCompilationJobRequest$CompilationJobName' => 'The name of the compilation job to delete.
', 'DeleteDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet to delete.
', 'DeleteEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to delete.
', 'DeleteEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan from which the stage will be deleted.
', 'DeleteEdgeDeploymentStageRequest$StageName' => 'The name of the stage.
', 'DeleteModelCardRequest$ModelCardName' => 'The name of the model card to delete.
', 'DeleteModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group for which to delete the policy.
', 'DeploymentStage$StageName' => 'The name of the stage.
', 'DeploymentStageStatusSummary$StageName' => 'The name of the stage.
', 'DeregisterDevicesRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', 'DescribeAlgorithmOutput$AlgorithmName' => 'The name of the algorithm being described.
', 'DescribeCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to describe.
', 'DescribeCodeRepositoryOutput$CodeRepositoryName' => 'The name of the Git repository.
', 'DescribeCompilationJobRequest$CompilationJobName' => 'The name of the model compilation job that you want information about.
', 'DescribeCompilationJobResponse$CompilationJobName' => 'The name of the model compilation job.
', 'DescribeDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet.
', 'DescribeDeviceFleetResponse$DeviceFleetName' => 'The name of the fleet.
', 'DescribeDeviceRequest$DeviceName' => 'The unique ID of the device.
', 'DescribeDeviceRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', 'DescribeDeviceResponse$DeviceName' => 'The unique identifier of the device.
', 'DescribeDeviceResponse$DeviceFleetName' => 'The name of the fleet the device belongs to.
', 'DescribeEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the deployment plan to describe.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$DeviceFleetName' => 'The device fleet used for this edge deployment plan.
', 'DescribeEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'DescribeEdgePackagingJobResponse$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'DescribeEdgePackagingJobResponse$CompilationJobName' => 'The name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged.
', 'DescribeEdgePackagingJobResponse$ModelName' => 'The name of the model.
', 'DescribeModelCardExportJobResponse$ModelCardExportJobName' => 'The name of the model card export job to describe.
', 'DescribeModelCardExportJobResponse$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card that the model export job exports.
', 'DescribeModelCardResponse$ModelCardName' => 'The name of the model card.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupName' => 'The name of the model group.
', 'DescribeModelPackageOutput$ModelPackageName' => 'The name of the model package being described.
', 'DescribeModelPackageOutput$ModelPackageGroupName' => 'If the model is a versioned model, the name of the model group that the versioned model belongs to.
', 'DeviceDeploymentSummary$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'DeviceDeploymentSummary$StageName' => 'The name of the stage in the edge deployment plan.
', 'DeviceDeploymentSummary$DeployedStageName' => 'The name of the deployed stage.
', 'DeviceDeploymentSummary$DeviceFleetName' => 'The name of the fleet to which the device belongs to.
', 'DeviceFleetSummary$DeviceFleetName' => 'Name of the device fleet.
', 'DeviceSummary$DeviceName' => 'The unique identifier of the device.
', 'DeviceSummary$DeviceFleetName' => 'The name of the fleet the device belongs to.
', 'EdgeDeploymentModelConfig$ModelHandle' => 'The name the device application uses to reference this model.
', 'EdgeDeploymentModelConfig$EdgePackagingJobName' => 'The edge packaging job associated with this deployment.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'EdgeDeploymentPlanSummary$DeviceFleetName' => 'The name of the device fleet used for the deployment.
', 'EdgeModel$ModelName' => 'The name of the model.
', 'EdgeModelStat$ModelName' => 'The name of the model.
', 'EdgeModelSummary$ModelName' => 'The name of the model.
', 'EdgePackagingJobSummary$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'EdgePackagingJobSummary$CompilationJobName' => 'The name of the SageMaker Neo compilation job.
', 'EdgePackagingJobSummary$ModelName' => 'The name of the model.
', 'GetDeviceFleetReportRequest$DeviceFleetName' => 'The name of the fleet.
', 'GetDeviceFleetReportResponse$DeviceFleetName' => 'The name of the fleet.
', 'GetModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group for which to get the resource policy.
', 'ListDevicesRequest$ModelName' => 'A filter that searches devices that contains this name in any of their models.
', 'ListDevicesRequest$DeviceFleetName' => 'Filter for fleets containing this name in their device fleet name.
', 'ListModelCardExportJobsRequest$ModelCardName' => 'List export jobs for the model card with the specified name.
', 'ListModelCardExportJobsRequest$ModelCardExportJobNameContains' => 'Only list model card export jobs with names that contain the specified string.
', 'ListModelCardsRequest$NameContains' => 'Only list model cards with names that contain the specified string.
', 'ListStageDevicesRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'ListStageDevicesRequest$StageName' => 'The name of the stage in the deployment.
', 'ModelCard$ModelCardName' => 'The unique name of the model card.
', 'ModelCardExportJobSummary$ModelCardExportJobName' => 'The name of the model card export job.
', 'ModelCardExportJobSummary$ModelCardName' => 'The name of the model card that the export job exports.
', 'ModelCardSummary$ModelCardName' => 'The name of the model card.
', 'ModelCardVersionSummary$ModelCardName' => 'The name of the model card.
', 'ModelDashboardModelCard$ModelCardName' => 'The name of a model card.
', 'ModelPackage$ModelPackageName' => 'The name of the model.
', 'ModelPackage$ModelPackageGroupName' => 'The model group to which the model belongs.
', 'ModelPackageGroup$ModelPackageGroupName' => 'The name of the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupName' => 'The name of the model group.
', 'ModelPackageStatusItem$Name' => 'The name of the model package for which the overall status is being reported.
', 'ModelPackageSummary$ModelPackageName' => 'The name of the model package.
', 'ModelPackageSummary$ModelPackageGroupName' => 'If the model package is a versioned model, the model group that the versioned model belongs to.
', 'ModelPackageValidationProfile$ProfileName' => 'The name of the profile for the model package.
', 'PutModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group to add a resource policy to.
', 'RegisterDevicesRequest$DeviceFleetName' => 'The name of the fleet.
', 'StartEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to start.
', 'StartEdgeDeploymentStageRequest$StageName' => 'The name of the stage to start.
', 'StopCompilationJobRequest$CompilationJobName' => 'The name of the model compilation job to stop.
', 'StopEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to stop.
', 'StopEdgeDeploymentStageRequest$StageName' => 'The name of the stage to stop.
', 'StopEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'UpdateCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to update.
', 'UpdateDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet.
', 'UpdateDevicesRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', ], ], 'EnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'EnvironmentMap$key' => NULL, ], ], 'EnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$Environment' => 'The environment variables to set in the container. For more information, see ContainerDefinition.
', 'ContainerDefinition$Environment' => 'The environment variables to set in the Docker container. Each key and value in the Environment
string to string map can have length of up to 1024. We support up to 16 entries in the map.
The environment variables to set in the Docker container. Each key and value in the Environment string-to-string map can have length of up to 1024. We support up to 16 entries in the map.
', 'InferenceComponentContainerSpecificationSummary$Environment' => 'The environment variables to set in the Docker container.
', 'ModelPackageContainerDefinition$Environment' => 'The environment variables to set in the Docker container. Each key and value in the Environment
string to string map can have length of up to 1024. We support up to 16 entries in the map.
The recommended environment variables to set in the model container for Real-Time Inference.
', ], ], 'EnvironmentParameter' => [ 'base' => 'A list of environment parameters suggested by the Amazon SageMaker Inference Recommender.
', 'refs' => [ 'EnvironmentParameters$member' => NULL, ], ], 'EnvironmentParameterRanges' => [ 'base' => 'Specifies the range of environment parameters
', 'refs' => [ 'EndpointInputConfiguration$EnvironmentParameterRanges' => 'The parameter you want to benchmark against.
', ], ], 'EnvironmentParameters' => [ 'base' => NULL, 'refs' => [ 'ModelConfiguration$EnvironmentParameters' => 'Defines the environment parameters that includes key, value types, and values.
', ], ], 'EnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'EnvironmentMap$value' => NULL, ], ], 'ExcludeFeaturesAttribute' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$ExcludeFeaturesAttribute' => 'The attributes of the input data to exclude from the analysis.
', 'EndpointInput$ExcludeFeaturesAttribute' => 'The attributes of the input data to exclude from the analysis.
', ], ], 'ExecutionRoleIdentityConfig' => [ 'base' => NULL, 'refs' => [ 'DomainSettings$ExecutionRoleIdentityConfig' => 'The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key.
', 'DomainSettingsForUpdate$ExecutionRoleIdentityConfig' => 'The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the InService
or Pending
state.
A filter that retrieves only jobs with a specific status.
', 'MonitoringExecutionSummary$MonitoringExecutionStatus' => 'The status of the monitoring job.
', ], ], 'ExitMessage' => [ 'base' => NULL, 'refs' => [ 'DescribeProcessingJobResponse$ExitMessage' => 'An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', 'ProcessingJob$ExitMessage' => 'A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', 'ProcessingJobSummary$ExitMessage' => 'An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', ], ], 'Experiment' => [ 'base' => 'The properties of an experiment as returned by the Search API.
', 'refs' => [ 'SearchRecord$Experiment' => 'The properties of an experiment.
', ], ], 'ExperimentArn' => [ 'base' => NULL, 'refs' => [ 'CreateExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'DeleteExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment that is being deleted.
', 'DescribeExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'Experiment$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'ExperimentSummary$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'UpdateExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', ], ], 'ExperimentConfig' => [ 'base' => 'Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
', 'refs' => [ 'CreateProcessingJobRequest$ExperimentConfig' => NULL, 'CreateTrainingJobRequest$ExperimentConfig' => NULL, 'CreateTransformJobRequest$ExperimentConfig' => NULL, 'DescribeProcessingJobResponse$ExperimentConfig' => 'The configuration information used to create an experiment.
', 'DescribeTrainingJobResponse$ExperimentConfig' => NULL, 'DescribeTransformJobResponse$ExperimentConfig' => NULL, 'ProcessingJob$ExperimentConfig' => NULL, 'TrainingJob$ExperimentConfig' => NULL, 'TransformJob$ExperimentConfig' => NULL, ], ], 'ExperimentDescription' => [ 'base' => NULL, 'refs' => [ 'CreateActionRequest$Description' => 'The description of the action.
', 'CreateContextRequest$Description' => 'The description of the context.
', 'CreateExperimentRequest$Description' => 'The description of the experiment.
', 'DescribeActionResponse$Description' => 'The description of the action.
', 'DescribeContextResponse$Description' => 'The description of the context.
', 'DescribeExperimentResponse$Description' => 'The description of the experiment.
', 'DescribeLineageGroupResponse$Description' => 'The description of the lineage group.
', 'Experiment$Description' => 'The description of the experiment.
', 'UpdateActionRequest$Description' => 'The new description for the action.
', 'UpdateContextRequest$Description' => 'The new description for the context.
', 'UpdateExperimentRequest$Description' => 'The description of the experiment.
', ], ], 'ExperimentEntityName' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$ActionName' => 'The name of the action.
', 'ArtifactSummary$ArtifactName' => 'The name of the artifact.
', 'AssociateTrialComponentRequest$TrialComponentName' => 'The name of the component to associated with the trial.
', 'AssociateTrialComponentRequest$TrialName' => 'The name of the trial to associate with.
', 'AssociationSummary$SourceName' => 'The name of the source.
', 'AssociationSummary$DestinationName' => 'The name of the destination.
', 'CreateActionRequest$ActionName' => 'The name of the action. Must be unique to your account in an Amazon Web Services Region.
', 'CreateArtifactRequest$ArtifactName' => 'The name of the artifact. Must be unique to your account in an Amazon Web Services Region.
', 'CreateExperimentRequest$ExperimentName' => 'The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateExperimentRequest$DisplayName' => 'The name of the experiment as displayed. The name doesn\'t need to be unique. If you don\'t specify DisplayName
, the value in ExperimentName
is displayed.
The name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateTrialComponentRequest$DisplayName' => 'The name of the component as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateTrialRequest$DisplayName' => 'The name of the trial as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the experiment to associate the trial with.
', 'DeleteActionRequest$ActionName' => 'The name of the action to delete.
', 'DeleteExperimentRequest$ExperimentName' => 'The name of the experiment to delete.
', 'DeleteTrialComponentRequest$TrialComponentName' => 'The name of the component to delete.
', 'DeleteTrialRequest$TrialName' => 'The name of the trial to delete.
', 'DescribeExperimentRequest$ExperimentName' => 'The name of the experiment to describe.
', 'DescribeExperimentResponse$ExperimentName' => 'The name of the experiment.
', 'DescribeExperimentResponse$DisplayName' => 'The name of the experiment as displayed. If DisplayName
isn\'t specified, ExperimentName
is displayed.
The name of the lineage group.
', 'DescribeLineageGroupResponse$LineageGroupName' => 'The name of the lineage group.
', 'DescribeLineageGroupResponse$DisplayName' => 'The display name of the lineage group.
', 'DescribeTrialComponentResponse$TrialComponentName' => 'The name of the trial component.
', 'DescribeTrialComponentResponse$DisplayName' => 'The name of the component as displayed. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the trial to describe.
', 'DescribeTrialResponse$TrialName' => 'The name of the trial.
', 'DescribeTrialResponse$DisplayName' => 'The name of the trial as displayed. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the experiment the trial is part of.
', 'DisassociateTrialComponentRequest$TrialComponentName' => 'The name of the component to disassociate from the trial.
', 'DisassociateTrialComponentRequest$TrialName' => 'The name of the trial to disassociate from.
', 'Experiment$ExperimentName' => 'The name of the experiment.
', 'Experiment$DisplayName' => 'The name of the experiment as displayed. If DisplayName
isn\'t specified, ExperimentName
is displayed.
The name of an existing experiment to associate with the trial component.
', 'ExperimentConfig$TrialName' => 'The name of an existing trial to associate the trial component with. If not specified, a new trial is created.
', 'ExperimentConfig$TrialComponentDisplayName' => 'The display name for the trial component. If this key isn\'t specified, the display name is the trial component name.
', 'ExperimentConfig$RunName' => 'The name of the experiment run to associate with the trial component.
', 'ExperimentSummary$ExperimentName' => 'The name of the experiment.
', 'ExperimentSummary$DisplayName' => 'The name of the experiment as displayed. If DisplayName
isn\'t specified, ExperimentName
is displayed.
The name or Amazon Resource Name (ARN) of the lineage group.
', 'LineageGroupSummary$DisplayName' => 'The display name of the lineage group summary.
', 'ListTrialComponentsRequest$ExperimentName' => 'A filter that returns only components that are part of the specified experiment. If you specify ExperimentName
, you can\'t filter by SourceArn
or TrialName
.
A filter that returns only components that are part of the specified trial. If you specify TrialName
, you can\'t filter by ExperimentName
or SourceArn
.
A filter that returns only trials that are part of the specified experiment.
', 'ListTrialsRequest$TrialComponentName' => 'A filter that returns only trials that are associated with the specified trial component.
', 'Parent$TrialName' => 'The name of the trial.
', 'Parent$ExperimentName' => 'The name of the experiment.
', 'PipelineExperimentConfig$ExperimentName' => 'The name of the experiment.
', 'PipelineExperimentConfig$TrialName' => 'The name of the trial.
', 'Trial$TrialName' => 'The name of the trial.
', 'Trial$DisplayName' => 'The name of the trial as displayed. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the experiment the trial is part of.
', 'TrialComponent$TrialComponentName' => 'The name of the trial component.
', 'TrialComponent$DisplayName' => 'The name of the component as displayed. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the experiment run.
', 'TrialComponentSimpleSummary$TrialComponentName' => 'The name of the trial component.
', 'TrialComponentSummary$TrialComponentName' => 'The name of the trial component.
', 'TrialComponentSummary$DisplayName' => 'The name of the component as displayed. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the trial.
', 'TrialSummary$DisplayName' => 'The name of the trial as displayed. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the action to update.
', 'UpdateArtifactRequest$ArtifactName' => 'The new name for the artifact.
', 'UpdateExperimentRequest$ExperimentName' => 'The name of the experiment to update.
', 'UpdateExperimentRequest$DisplayName' => 'The name of the experiment as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, ExperimentName
is displayed.
The name of the component to update.
', 'UpdateTrialComponentRequest$DisplayName' => 'The name of the component as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the trial to update.
', 'UpdateTrialRequest$DisplayName' => 'The name of the trial as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the action to describe.
', 'DescribeActionResponse$ActionName' => 'The name of the action.
', 'DescribeArtifactResponse$ArtifactName' => 'The name of the artifact.
', 'DescribeTrialComponentRequest$TrialComponentName' => 'The name of the trial component to describe.
', ], ], 'ExperimentSource' => [ 'base' => 'The source of the experiment.
', 'refs' => [ 'DescribeExperimentResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the type.
', 'Experiment$Source' => NULL, 'ExperimentSummary$ExperimentSource' => NULL, ], ], 'ExperimentSourceArn' => [ 'base' => NULL, 'refs' => [ 'ExperimentSource$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'ExperimentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListExperimentsResponse$ExperimentSummaries' => 'A list of the summaries of your experiments.
', ], ], 'ExperimentSummary' => [ 'base' => 'A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName
.
The number of seconds until the pre-signed URL expires. This value defaults to 300.
', ], ], 'Explainability' => [ 'base' => 'Contains explainability metrics for a model.
', 'refs' => [ 'ModelMetrics$Explainability' => 'Metrics that help explain a model.
', ], ], 'ExplainabilityLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$Explainability' => 'The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
', ], ], 'ExplainerConfig' => [ 'base' => 'A parameter to activate explainers.
', 'refs' => [ 'CreateEndpointConfigInput$ExplainerConfig' => 'A member of CreateEndpointConfig
that enables explainers.
The configuration parameters for an explainer.
', 'DescribeEndpointOutput$ExplainerConfig' => 'The configuration parameters for an explainer.
', ], ], 'FailStepMetadata' => [ 'base' => 'The container for the metadata for Fail step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Fail' => 'The configurations and outcomes of a Fail step execution.
', ], ], 'FailureHandlingPolicy' => [ 'base' => NULL, 'refs' => [ 'EdgeDeploymentConfig$FailureHandlingPolicy' => 'Toggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.
', ], ], 'FailureReason' => [ 'base' => NULL, 'refs' => [ 'ConflictException$Message' => NULL, 'DescribeAppResponse$FailureReason' => 'The failure reason.
', 'DescribeCompilationJobResponse$FailureReason' => 'If a model compilation job failed, the reason it failed.
', 'DescribeDomainResponse$FailureReason' => 'The failure reason.
', 'DescribeEndpointOutput$FailureReason' => 'If the status of the endpoint is Failed
, the reason why it failed.
The reason that the FeatureGroup
failed to be replicated in the OfflineStore
. This is failure can occur because:
The FeatureGroup
could not be created in the OfflineStore
.
The FeatureGroup
could not be deleted from the OfflineStore
.
The reason your flow definition failed.
', 'DescribeHubContentResponse$FailureReason' => 'The failure reason if importing hub content failed.
', 'DescribeHubResponse$FailureReason' => 'The failure reason if importing hub content failed.
', 'DescribeHyperParameterTuningJobResponse$FailureReason' => 'If the tuning job failed, the reason it failed.
', 'DescribeImageResponse$FailureReason' => 'When a create, update, or delete operation fails, the reason for the failure.
', 'DescribeImageVersionResponse$FailureReason' => 'When a create or delete operation fails, the reason for the failure.
', 'DescribeInferenceComponentOutput$FailureReason' => 'If the inference component status is Failed
, the reason for the failure.
If the job fails, provides information why the job failed.
', 'DescribeLabelingJobResponse$FailureReason' => 'If the job failed, the reason that it failed.
', 'DescribeModelCardExportJobResponse$FailureReason' => 'The failure reason if the model export job fails.
', 'DescribeMonitoringScheduleResponse$FailureReason' => 'A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
', 'DescribeNotebookInstanceOutput$FailureReason' => 'If status is Failed
, the reason it failed.
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'DescribeSpaceResponse$FailureReason' => 'The failure reason.
', 'DescribeTrainingJobResponse$FailureReason' => 'If the training job failed, the reason it failed.
', 'DescribeTransformJobResponse$FailureReason' => 'If the transform job failed, FailureReason
describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see Log Amazon SageMaker Events with Amazon CloudWatch.
The failure reason.
', 'Endpoint$FailureReason' => 'If the endpoint failed, the reason it failed.
', 'EndpointMetadata$FailureReason' => ' If the status of the endpoint is Failed
, or the status is InService
but update operation fails, this provides the reason why it failed.
The reason that the FeatureGroup
failed to be replicated in the OfflineStore
. This is failure may be due to a failure to create a FeatureGroup
in or delete a FeatureGroup
from the OfflineStore
.
The reason why the flow definition creation failed. A failure reason is returned only when the flow definition status is Failed
.
The reason that the training job failed.
', 'HyperParameterTuningJobSearchEntity$FailureReason' => 'The error that was created when a hyperparameter tuning job failed.
', 'Image$FailureReason' => 'When a create, update, or delete operation fails, the reason for the failure.
', 'ImageVersion$FailureReason' => 'When a create or delete operation fails, the reason for the failure.
', 'InferenceRecommendationsJob$FailureReason' => 'If the job fails, provides information why the job failed.
', 'LabelingJobSummary$FailureReason' => 'If the LabelingJobStatus
field is Failed
, this field contains a description of the error.
If the update wasn\'t successful, indicates the reason why it failed.
', 'ModelDashboardMonitoringSchedule$FailureReason' => 'If a monitoring job failed, provides the reason.
', 'MonitoringExecutionSummary$FailureReason' => 'Contains the reason a monitoring job failed, if it failed.
', 'MonitoringSchedule$FailureReason' => 'If the monitoring schedule failed, the reason it failed.
', 'PipelineExecutionStep$FailureReason' => 'The reason why the step failed execution. This is only returned if the step failed its execution.
', 'ProcessingJob$FailureReason' => 'A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'ProcessingJobSummary$FailureReason' => 'A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'ResourceInUse$Message' => NULL, 'ResourceLimitExceeded$Message' => NULL, 'ResourceNotFound$Message' => NULL, 'TrainingJob$FailureReason' => 'If the training job failed, the reason it failed.
', 'TransformJob$FailureReason' => 'If the transform job failed, the reason it failed.
', 'TransformJobSummary$FailureReason' => 'If the transform job failed, the reason it failed.
', ], ], 'FeatureAdditions' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureGroupRequest$FeatureAdditions' => 'Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you\'ve made a valid request. It takes some time after you\'ve made a valid request for Feature Store to update the feature group.
', ], ], 'FeatureDefinition' => [ 'base' => 'A list of features. You must include FeatureName
and FeatureType
. Valid feature FeatureType
s are Integral
, Fractional
and String
.
A list of Feature
names and types. Name
and Type
is compulsory per Feature
.
Valid feature FeatureType
s are Integral
, Fractional
and String
.
FeatureName
s cannot be any of the following: is_deleted
, write_time
, api_invocation_time
You can create up to 2,500 FeatureDefinition
s per FeatureGroup
.
A list of the Features
in the FeatureGroup
. Each feature is defined by a FeatureName
and FeatureType
.
A list of Feature
s. Each Feature
must include a FeatureName
and a FeatureType
.
Valid FeatureType
s are Integral
, Fractional
and String
.
FeatureName
s cannot be any of the following: is_deleted
, write_time
, api_invocation_time
.
You can create up to 2,500 FeatureDefinition
s per FeatureGroup
.
The description you added to describe the feature.
', 'FeatureMetadata$Description' => 'An optional description that you specify to better describe the feature.
', 'UpdateFeatureMetadataRequest$Description' => 'A description that you can write to better describe the feature.
', ], ], 'FeatureGroup' => [ 'base' => 'Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
', 'refs' => [ 'SearchRecord$FeatureGroup' => NULL, ], ], 'FeatureGroupArn' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupResponse$FeatureGroupArn' => 'The Amazon Resource Name (ARN) of the FeatureGroup
. This is a unique identifier for the feature group.
The Amazon Resource Name (ARN) of the FeatureGroup
.
The Amazon Resource Number (ARN) of the feature group that contains the feature.
', 'FeatureGroup$FeatureGroupArn' => 'The Amazon Resource Name (ARN) of a FeatureGroup
.
Unique identifier for the FeatureGroup
.
The Amazon Resource Number (ARN) of the feature group.
', 'UpdateFeatureGroupResponse$FeatureGroupArn' => 'The Amazon Resource Number (ARN) of the feature group that you\'re updating.
', ], ], 'FeatureGroupMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$MaxResults' => 'The maximum number of results returned by ListFeatureGroups
.
The name of the FeatureGroup
. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account. The name:
Must start and end with an alphanumeric character.
Can only contain alphanumeric character and hyphens. Spaces are not allowed.
The name of the FeatureGroup
you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
he name of the FeatureGroup
.
The name of the feature group that you\'ve specified.
', 'FeatureGroup$FeatureGroupName' => 'The name of the FeatureGroup
.
The name of FeatureGroup
.
The name of the feature group containing the feature.
', 'ProcessingFeatureStoreOutput$FeatureGroupName' => 'The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.
', ], ], 'FeatureGroupNameContains' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$NameContains' => 'A string that partially matches one or more FeatureGroup
s names. Filters FeatureGroup
s by name.
The name or Amazon Resource Name (ARN) of the FeatureGroup
you want described.
The name or Amazon Resource Name (ARN) of the feature group containing the feature.
', 'UpdateFeatureGroupRequest$FeatureGroupName' => 'The name or Amazon Resource Name (ARN) of the feature group that you\'re updating.
', 'UpdateFeatureMetadataRequest$FeatureGroupName' => 'The name or Amazon Resource Name (ARN) of the feature group containing the feature that you\'re updating.
', ], ], 'FeatureGroupSortBy' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$SortBy' => 'The value on which the feature group list is sorted.
', ], ], 'FeatureGroupSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$SortOrder' => 'The order in which feature groups are listed.
', ], ], 'FeatureGroupStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureGroupResponse$FeatureGroupStatus' => 'The status of the feature group.
', 'FeatureGroup$FeatureGroupStatus' => 'A FeatureGroup
status.
The status of a FeatureGroup. The status can be any of the following: Creating
, Created
, CreateFail
, Deleting
or DetailFail
.
A FeatureGroup
status. Filters by FeatureGroup
status.
A summary of feature groups.
', ], ], 'FeatureGroupSummary' => [ 'base' => 'The name, ARN, CreationTime
, FeatureGroup
values, LastUpdatedTime
and EnableOnlineStorage
status of a FeatureGroup
.
The metadata for a feature. It can either be metadata that you specify, or metadata that is updated automatically.
', 'refs' => [ 'SearchRecord$FeatureMetadata' => 'The feature metadata used to search through the features.
', ], ], 'FeatureName' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupRequest$RecordIdentifierFeatureName' => 'The name of the Feature
whose value uniquely identifies a Record
defined in the FeatureStore
. Only the latest record per identifier value will be stored in the OnlineStore
. RecordIdentifierFeatureName
must be one of feature definitions\' names.
You use the RecordIdentifierFeatureName
to access data in a FeatureStore
.
This name:
Must start and end with an alphanumeric character.
Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.
The name of the feature that stores the EventTime
of a Record
in a FeatureGroup
.
An EventTime
is a point in time when a new event occurs that corresponds to the creation or update of a Record
in a FeatureGroup
. All Records
in the FeatureGroup
must have a corresponding EventTime
.
An EventTime
can be a String
or Fractional
.
Fractional
: EventTime
feature values must be a Unix timestamp in seconds.
String
: EventTime
feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd\'T\'HH:mm:ssZ
and yyyy-MM-dd\'T\'HH:mm:ss.SSSZ
where yyyy
, MM
, and dd
represent the year, month, and day respectively and HH
, mm
, ss
, and if applicable, SSS
represent the hour, month, second and milliseconds respsectively. \'T\'
and Z
are constants.
The name of the Feature
used for RecordIdentifier
, whose value uniquely identifies a record stored in the feature store.
The name of the feature that stores the EventTime
of a Record in a FeatureGroup
.
An EventTime
is a point in time when a new event occurs that corresponds to the creation or update of a Record
in a FeatureGroup
. All Records
in the FeatureGroup
have a corresponding EventTime
.
The name of the feature.
', 'DescribeFeatureMetadataResponse$FeatureName' => 'The name of the feature that you\'ve specified.
', 'FeatureDefinition$FeatureName' => 'The name of a feature. The type must be a string. FeatureName
cannot be any of the following: is_deleted
, write_time
, api_invocation_time
.
The name of the Feature
whose value uniquely identifies a Record
defined in the FeatureGroup
FeatureDefinitions
.
The name of the feature that stores the EventTime
of a Record in a FeatureGroup
.
A EventTime
is point in time when a new event occurs that corresponds to the creation or update of a Record
in FeatureGroup
. All Records
in the FeatureGroup
must have a corresponding EventTime
.
The name of feature.
', 'UpdateFeatureMetadataRequest$FeatureName' => 'The name of the feature that you\'re updating.
', ], ], 'FeatureParameter' => [ 'base' => 'A key-value pair that you specify to describe the feature.
', 'refs' => [ 'FeatureParameterAdditions$member' => NULL, 'FeatureParameters$member' => NULL, ], ], 'FeatureParameterAdditions' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureMetadataRequest$ParameterAdditions' => 'A list of key-value pairs that you can add to better describe the feature.
', ], ], 'FeatureParameterKey' => [ 'base' => NULL, 'refs' => [ 'FeatureParameter$Key' => 'A key that must contain a value to describe the feature.
', 'FeatureParameterRemovals$member' => NULL, ], ], 'FeatureParameterRemovals' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureMetadataRequest$ParameterRemovals' => 'A list of parameter keys that you can specify to remove parameters that describe your feature.
', ], ], 'FeatureParameterValue' => [ 'base' => NULL, 'refs' => [ 'FeatureParameter$Value' => 'The value that belongs to a key.
', ], ], 'FeatureParameters' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureMetadataResponse$Parameters' => 'The key-value pairs that you added to describe the feature.
', 'FeatureMetadata$Parameters' => 'Optional key-value pairs that you specify to better describe the feature.
', ], ], 'FeatureStatus' => [ 'base' => NULL, 'refs' => [ 'DirectDeploySettings$Status' => 'Describes whether model deployment permissions are enabled or disabled in the Canvas application.
', 'DockerSettings$EnableDockerAccess' => 'Indicates whether the domain can access Docker.
', 'IdentityProviderOAuthSetting$Status' => 'Describes whether OAuth for a data source is enabled or disabled in the Canvas application.
', 'KendraSettings$Status' => 'Describes whether the document querying feature is enabled or disabled in the Canvas application.
', 'ModelRegisterSettings$Status' => 'Describes whether the integration to the model registry is enabled or disabled in the Canvas application.
', 'TimeSeriesForecastingSettings$Status' => 'Describes whether time series forecasting is enabled or disabled in the Canvas application.
', ], ], 'FeatureType' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureMetadataResponse$FeatureType' => 'The data type of the feature.
', 'FeatureDefinition$FeatureType' => 'The value type of a feature. Valid values are Integral, Fractional, or String.
', 'FeatureMetadata$FeatureType' => 'The data type of the feature.
', ], ], 'FileSource' => [ 'base' => 'Contains details regarding the file source.
', 'refs' => [ 'DriftCheckBias$ConfigFile' => 'The bias config file for a model.
', 'DriftCheckExplainability$ConfigFile' => 'The explainability config file for the model.
', ], ], 'FileSystemAccessMode' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemAccessMode' => 'The access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro
(read-only) or rw
(read-write) mode.
The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
', 'refs' => [ 'JupyterLabAppImageConfig$FileSystemConfig' => NULL, 'KernelGatewayImageConfig$FileSystemConfig' => 'The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
', ], ], 'FileSystemDataSource' => [ 'base' => 'Specifies a file system data source for a channel.
', 'refs' => [ 'DataSource$FileSystemDataSource' => 'The file system that is associated with a channel.
', ], ], 'FileSystemId' => [ 'base' => NULL, 'refs' => [ 'EFSFileSystem$FileSystemId' => 'The ID of your Amazon EFS file system.
', 'EFSFileSystemConfig$FileSystemId' => 'The ID of your Amazon EFS file system.
', 'FileSystemDataSource$FileSystemId' => 'The file system id.
', ], ], 'FileSystemPath' => [ 'base' => NULL, 'refs' => [ 'EFSFileSystemConfig$FileSystemPath' => 'The path to the file system directory that is accessible in Amazon SageMaker Studio. Permitted users can access only this directory and below.
', ], ], 'FileSystemType' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemType' => 'The file system type.
', ], ], 'FillingTransformationMap' => [ 'base' => NULL, 'refs' => [ 'FillingTransformations$value' => NULL, ], ], 'FillingTransformationValue' => [ 'base' => NULL, 'refs' => [ 'FillingTransformationMap$value' => NULL, ], ], 'FillingTransformations' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesTransformations$Filling' => 'A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.
The supported filling methods and their corresponding options are:
frontfill
: none
(Supported only for target column)
middlefill
: zero
, value
, median
, mean
, min
, max
backfill
: zero
, value
, median
, mean
, min
, max
futurefill
: zero
, value
, median
, mean
, min
, max
To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example "backfill" : "value"
), and define the filling value in an additional parameter prefixed with "_value". For example, to set backfill
to a value of 2
, you must include two parameters: "backfill": "value"
and "backfill_value":"2"
.
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value
, but not an Operator
, SageMaker uses the equals operator.
In search, there are several property types:
To define a metric filter, enter a value using the form "Metrics.<name>"
, where <name>
is a metric name. For example, the following filter searches for training jobs with an "accuracy"
metric greater than "0.9"
:
{
"Name": "Metrics.accuracy",
"Operator": "GreaterThan",
"Value": "0.9"
}
To define a hyperparameter filter, enter a value with the form "HyperParameters.<name>"
. Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value
is also a decimal value. If the specified Value
is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a "learning_rate"
hyperparameter that is less than "0.5"
:
{
"Name": "HyperParameters.learning_rate",
"Operator": "LessThan",
"Value": "0.5"
}
To define a tag filter, enter a value with the form Tags.<key>
.
A list of filters. Each filter acts on a property. Filters must contain at least one Filters
value. For example, a NestedFilters
call might include a filter on the PropertyName
parameter of the InputDataConfig
property: InputDataConfig.DataSource.S3DataSource.S3Uri
.
A list of filter objects.
', ], ], 'FilterValue' => [ 'base' => NULL, 'refs' => [ 'Filter$Value' => 'A value used with Name
and Operator
to determine which resources satisfy the filter\'s condition. For numerical properties, Value
must be an integer or floating-point decimal. For timestamp properties, Value
must be an ISO 8601 date-time string of the following format: YYYY-mm-dd\'T\'HH:MM:SS
.
The best candidate result from an AutoML training job.
', 'refs' => [ 'AutoMLCandidate$FinalAutoMLJobObjectiveMetric' => NULL, ], ], 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'base' => 'Shows the latest objective metric emitted by a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective
parameter of HyperParameterTuningJobConfig.
The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.
', ], ], 'FinalMetricDataList' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$FinalMetricDataList' => 'A collection of MetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
', ], ], 'FlatInvocations' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobStoppingConditions$FlatInvocations' => 'Stops a load test when the number of invocations (TPS) peaks and flattens, which means that the instance has reached capacity. The default value is Stop
. If you want the load test to continue after invocations have flattened, set the value to Continue
.
The value of the metric.
', 'MetricDatum$Value' => 'The value of the metric.
', 'RecommendationMetrics$CostPerHour' => 'Defines the cost per hour for the instance.
', 'RecommendationMetrics$CostPerInference' => 'Defines the cost per inference for the instance .
', ], ], 'FlowDefinitionArn' => [ 'base' => NULL, 'refs' => [ 'CreateFlowDefinitionResponse$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow definition you create.
', 'DescribeFlowDefinitionResponse$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow defintion.
', 'FlowDefinitionSummary$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow definition.
', ], ], 'FlowDefinitionName' => [ 'base' => NULL, 'refs' => [ 'CreateFlowDefinitionRequest$FlowDefinitionName' => 'The name of your flow definition.
', 'DeleteFlowDefinitionRequest$FlowDefinitionName' => 'The name of the flow definition you are deleting.
', 'DescribeFlowDefinitionRequest$FlowDefinitionName' => 'The name of the flow definition.
', 'DescribeFlowDefinitionResponse$FlowDefinitionName' => 'The Amazon Resource Name (ARN) of the flow definition.
', 'FlowDefinitionSummary$FlowDefinitionName' => 'The name of the flow definition.
', ], ], 'FlowDefinitionOutputConfig' => [ 'base' => 'Contains information about where human output will be stored.
', 'refs' => [ 'CreateFlowDefinitionRequest$OutputConfig' => 'An object containing information about where the human review results will be uploaded.
', 'DescribeFlowDefinitionResponse$OutputConfig' => 'An object containing information about the output file.
', ], ], 'FlowDefinitionStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeFlowDefinitionResponse$FlowDefinitionStatus' => 'The status of the flow definition. Valid values are listed below.
', 'FlowDefinitionSummary$FlowDefinitionStatus' => 'The status of the flow definition. Valid values:
', ], ], 'FlowDefinitionSummaries' => [ 'base' => NULL, 'refs' => [ 'ListFlowDefinitionsResponse$FlowDefinitionSummaries' => 'An array of objects describing the flow definitions.
', ], ], 'FlowDefinitionSummary' => [ 'base' => 'Contains summary information about the flow definition.
', 'refs' => [ 'FlowDefinitionSummaries$member' => NULL, ], ], 'FlowDefinitionTaskAvailabilityLifetimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskAvailabilityLifetimeInSeconds' => 'The length of time that a task remains available for review by human workers.
', ], ], 'FlowDefinitionTaskCount' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskCount' => 'The number of distinct workers who will perform the same task on each object. For example, if TaskCount
is set to 3
for an image classification labeling job, three workers will classify each input image. Increasing TaskCount
can improve label accuracy.
A description for the human worker task.
', ], ], 'FlowDefinitionTaskKeyword' => [ 'base' => NULL, 'refs' => [ 'FlowDefinitionTaskKeywords$member' => NULL, ], ], 'FlowDefinitionTaskKeywords' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskKeywords' => 'Keywords used to describe the task so that workers can discover the task.
', ], ], 'FlowDefinitionTaskTimeLimitInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskTimeLimitInSeconds' => 'The amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).
', ], ], 'FlowDefinitionTaskTitle' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskTitle' => 'A title for the human worker task.
', ], ], 'ForecastFrequency' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$ForecastFrequency' => 'The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, 1D
indicates every day and 15min
indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of 1H
instead of 60min
.
The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.
', ], ], 'ForecastQuantile' => [ 'base' => NULL, 'refs' => [ 'ForecastQuantiles$member' => NULL, ], ], 'ForecastQuantiles' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$ForecastQuantiles' => 'The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01
(p1) to 0.99
(p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles
is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.
Identifies the framework in which the model was trained. For example: TENSORFLOW.
', ], ], 'FrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'InputConfig$FrameworkVersion' => 'Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
For information about framework versions supported for cloud targets and edge devices, see Cloud Supported Instance Types and Frameworks and Edge Supported Frameworks.
', ], ], 'GenerateCandidateDefinitionsOnly' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobRequest$GenerateCandidateDefinitionsOnly' => 'Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
', 'DescribeAutoMLJobResponse$GenerateCandidateDefinitionsOnly' => 'Indicates whether the output for an AutoML job generates candidate definitions only.
', 'TabularJobConfig$GenerateCandidateDefinitionsOnly' => 'Generates possible candidates without training the models. A model candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
', ], ], 'GetDeviceFleetReportRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetDeviceFleetReportResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetLineageGroupPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetLineageGroupPolicyResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetModelPackageGroupPolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'GetModelPackageGroupPolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetSagemakerServicecatalogPortfolioStatusInput' => [ 'base' => NULL, 'refs' => [], ], 'GetSagemakerServicecatalogPortfolioStatusOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetScalingConfigurationRecommendationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetScalingConfigurationRecommendationResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetSearchSuggestionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetSearchSuggestionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'Gid' => [ 'base' => NULL, 'refs' => [ 'CustomPosixUserConfig$Gid' => 'The POSIX group ID.
', ], ], 'GitConfig' => [ 'base' => 'Specifies configuration details for a Git repository in your Amazon Web Services account.
', 'refs' => [ 'CodeRepositorySummary$GitConfig' => 'Configuration details for the Git repository, including the URL where it is located and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
', 'CreateCodeRepositoryInput$GitConfig' => 'Specifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.
', 'DescribeCodeRepositoryOutput$GitConfig' => 'Configuration details about the repository, including the URL where the repository is located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
', ], ], 'GitConfigForUpdate' => [ 'base' => 'Specifies configuration details for a Git repository when the repository is updated.
', 'refs' => [ 'UpdateCodeRepositoryInput$GitConfig' => 'The configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of AWSCURRENT
and must be in the following format:
{"username": UserName, "password": Password}
The URL where the Git repository is located.
', ], ], 'Group' => [ 'base' => NULL, 'refs' => [ 'Groups$member' => NULL, ], ], 'GroupingAttributeName' => [ 'base' => NULL, 'refs' => [ 'GroupingAttributeNames$member' => NULL, ], ], 'GroupingAttributeNames' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$GroupingAttributeNames' => 'A set of columns names that can be grouped with the item identifier column to create a composite key for which a target value is predicted.
', ], ], 'Groups' => [ 'base' => NULL, 'refs' => [ 'OidcMemberDefinition$Groups' => 'A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.
', ], ], 'HolidayConfig' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$HolidayConfig' => 'The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
', ], ], 'HolidayConfigAttributes' => [ 'base' => 'Stores the holiday featurization attributes applicable to each item of time-series datasets during the training of a forecasting model. This allows the model to identify patterns associated with specific holidays.
', 'refs' => [ 'HolidayConfig$member' => NULL, ], ], 'HookParameters' => [ 'base' => NULL, 'refs' => [ 'DebugHookConfig$HookParameters' => 'Configuration information for the Amazon SageMaker Debugger hook parameters.
', ], ], 'Horovod' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$Horovod' => 'Indicates Horovod compatibility.
', 'DescribeImageVersionResponse$Horovod' => 'Indicates Horovod compatibility.
', 'UpdateImageVersionRequest$Horovod' => 'Indicates Horovod compatibility.
', ], ], 'HubArn' => [ 'base' => NULL, 'refs' => [ 'CreateHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'DescribeHubContentResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub that contains the content.
', 'DescribeHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'HubInfo$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'ImportHubContentResponse$HubArn' => 'The ARN of the hub that the content was imported into.
', 'UpdateHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the updated hub.
', ], ], 'HubContentArn' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentArn' => 'The Amazon Resource Name (ARN) of the hub content.
', 'HubContentInfo$HubContentArn' => 'The Amazon Resource Name (ARN) of the hub content.
', 'ImportHubContentResponse$HubContentArn' => 'The ARN of the hub content that was imported.
', ], ], 'HubContentDependency' => [ 'base' => 'Any dependencies related to hub content, such as scripts, model artifacts, datasets, or notebooks.
', 'refs' => [ 'HubContentDependencyList$member' => NULL, ], ], 'HubContentDependencyList' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDependencies' => 'The location of any dependencies that the hub content has, such as scripts, model artifacts, datasets, or notebooks.
', ], ], 'HubContentDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDescription' => 'A description of the hub content.
', 'HubContentInfo$HubContentDescription' => 'A description of the hub content.
', 'ImportHubContentRequest$HubContentDescription' => 'A description of the hub content to import.
', ], ], 'HubContentDisplayName' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDisplayName' => 'The display name of the hub content.
', 'HubContentInfo$HubContentDisplayName' => 'The display name of the hub content.
', 'ImportHubContentRequest$HubContentDisplayName' => 'The display name of the hub content to import.
', ], ], 'HubContentDocument' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDocument' => 'The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
', 'ImportHubContentRequest$HubContentDocument' => 'The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
', ], ], 'HubContentInfo' => [ 'base' => 'Information about hub content.
', 'refs' => [ 'HubContentInfoList$member' => NULL, ], ], 'HubContentInfoList' => [ 'base' => NULL, 'refs' => [ 'ListHubContentVersionsResponse$HubContentSummaries' => 'The summaries of the listed hub content versions.
', 'ListHubContentsResponse$HubContentSummaries' => 'The summaries of the listed hub content.
', ], ], 'HubContentMarkdown' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentMarkdown' => 'A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
', 'ImportHubContentRequest$HubContentMarkdown' => 'A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
', ], ], 'HubContentName' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentName' => 'The name of the content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentName' => 'The name of the content to describe.
', 'DescribeHubContentResponse$HubContentName' => 'The name of the hub content.
', 'HubContentInfo$HubContentName' => 'The name of the hub content.
', 'ImportHubContentRequest$HubContentName' => 'The name of the hub content to import.
', 'ListHubContentVersionsRequest$HubContentName' => 'The name of the hub content.
', ], ], 'HubContentSearchKeywordList' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentSearchKeywords' => 'The searchable keywords for the hub content.
', 'HubContentInfo$HubContentSearchKeywords' => 'The searchable keywords for the hub content.
', 'ImportHubContentRequest$HubContentSearchKeywords' => 'The searchable keywords of the hub content.
', ], ], 'HubContentSortBy' => [ 'base' => NULL, 'refs' => [ 'ListHubContentVersionsRequest$SortBy' => 'Sort hub content versions by either name or creation time.
', 'ListHubContentsRequest$SortBy' => 'Sort hub content versions by either name or creation time.
', ], ], 'HubContentStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentStatus' => 'The status of the hub content.
', 'HubContentInfo$HubContentStatus' => 'The status of the hub content.
', ], ], 'HubContentType' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentType' => 'The type of content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentType' => 'The type of content in the hub.
', 'DescribeHubContentResponse$HubContentType' => 'The type of hub content.
', 'HubContentInfo$HubContentType' => 'The type of hub content.
', 'ImportHubContentRequest$HubContentType' => 'The type of hub content to import.
', 'ListHubContentVersionsRequest$HubContentType' => 'The type of hub content to list versions of.
', 'ListHubContentsRequest$HubContentType' => 'The type of hub content to list.
', ], ], 'HubContentVersion' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentVersion' => 'The version of the content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentVersion' => 'The version of the content to describe.
', 'DescribeHubContentResponse$HubContentVersion' => 'The version of the hub content.
', 'HubContentInfo$HubContentVersion' => 'The version of the hub content.
', 'ImportHubContentRequest$HubContentVersion' => 'The version of the hub content to import.
', 'ListHubContentVersionsRequest$MinVersion' => 'The lower bound of the hub content versions to list.
', ], ], 'HubDescription' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubDescription' => 'A description of the hub.
', 'DescribeHubResponse$HubDescription' => 'A description of the hub.
', 'HubInfo$HubDescription' => 'A description of the hub.
', 'UpdateHubRequest$HubDescription' => 'A description of the updated hub.
', ], ], 'HubDisplayName' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubDisplayName' => 'The display name of the hub.
', 'DescribeHubResponse$HubDisplayName' => 'The display name of the hub.
', 'HubInfo$HubDisplayName' => 'The display name of the hub.
', 'UpdateHubRequest$HubDisplayName' => 'The display name of the hub.
', ], ], 'HubInfo' => [ 'base' => 'Information about a hub.
', 'refs' => [ 'HubInfoList$member' => NULL, ], ], 'HubInfoList' => [ 'base' => NULL, 'refs' => [ 'ListHubsResponse$HubSummaries' => 'The summaries of the listed hubs.
', ], ], 'HubName' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubName' => 'The name of the hub to create.
', 'DeleteHubContentRequest$HubName' => 'The name of the hub that you want to delete content in.
', 'DeleteHubRequest$HubName' => 'The name of the hub to delete.
', 'DescribeHubContentRequest$HubName' => 'The name of the hub that contains the content to describe.
', 'DescribeHubContentResponse$HubName' => 'The name of the hub that contains the content.
', 'DescribeHubRequest$HubName' => 'The name of the hub to describe.
', 'DescribeHubResponse$HubName' => 'The name of the hub.
', 'HubInfo$HubName' => 'The name of the hub.
', 'ImportHubContentRequest$HubName' => 'The name of the hub to import content into.
', 'ListHubContentVersionsRequest$HubName' => 'The name of the hub to list the content versions of.
', 'ListHubContentsRequest$HubName' => 'The name of the hub to list the contents of.
', 'UpdateHubRequest$HubName' => 'The name of the hub to update.
', ], ], 'HubS3StorageConfig' => [ 'base' => 'The Amazon S3 storage configuration of a hub.
', 'refs' => [ 'CreateHubRequest$S3StorageConfig' => 'The Amazon S3 storage configuration for the hub.
', 'DescribeHubResponse$S3StorageConfig' => 'The Amazon S3 storage configuration for the hub.
', ], ], 'HubSearchKeyword' => [ 'base' => NULL, 'refs' => [ 'HubContentSearchKeywordList$member' => NULL, 'HubSearchKeywordList$member' => NULL, ], ], 'HubSearchKeywordList' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'DescribeHubResponse$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'HubInfo$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'UpdateHubRequest$HubSearchKeywords' => 'The searchable keywords for the hub.
', ], ], 'HubSortBy' => [ 'base' => NULL, 'refs' => [ 'ListHubsRequest$SortBy' => 'Sort hubs by either name or creation time.
', ], ], 'HubStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHubResponse$HubStatus' => 'The status of the hub.
', 'HubInfo$HubStatus' => 'The status of the hub.
', ], ], 'HumanLoopActivationConditions' => [ 'base' => NULL, 'refs' => [ 'HumanLoopActivationConditionsConfig$HumanLoopActivationConditions' => 'JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker Developer Guide.
', ], ], 'HumanLoopActivationConditionsConfig' => [ 'base' => 'Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required format of activation conditions.
', 'refs' => [ 'HumanLoopActivationConfig$HumanLoopActivationConditionsConfig' => 'Container structure for defining under what conditions SageMaker creates a human loop.
', ], ], 'HumanLoopActivationConfig' => [ 'base' => 'Provides information about how and under what conditions SageMaker creates a human loop. If HumanLoopActivationConfig
is not given, then all requests go to humans.
An object containing information about the events that trigger a human workflow.
', 'DescribeFlowDefinitionResponse$HumanLoopActivationConfig' => 'An object containing information about what triggers a human review workflow.
', ], ], 'HumanLoopConfig' => [ 'base' => 'Describes the work to be performed by human workers.
', 'refs' => [ 'CreateFlowDefinitionRequest$HumanLoopConfig' => 'An object containing information about the tasks the human reviewers will perform.
', 'DescribeFlowDefinitionResponse$HumanLoopConfig' => 'An object containing information about who works on the task, the workforce task price, and other task details.
', ], ], 'HumanLoopRequestSource' => [ 'base' => 'Container for configuring the source of human task requests.
', 'refs' => [ 'CreateFlowDefinitionRequest$HumanLoopRequestSource' => 'Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
', 'DescribeFlowDefinitionResponse$HumanLoopRequestSource' => 'Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
', ], ], 'HumanTaskConfig' => [ 'base' => 'Information required for human workers to complete a labeling task.
', 'refs' => [ 'CreateLabelingJobRequest$HumanTaskConfig' => 'Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).
', 'DescribeLabelingJobResponse$HumanTaskConfig' => 'Configuration information required for human workers to complete a labeling task.
', ], ], 'HumanTaskUiArn' => [ 'base' => NULL, 'refs' => [ 'CreateHumanTaskUiResponse$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human review workflow user interface you create.
', 'DescribeHumanTaskUiResponse$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface (worker task template).
', 'HumanLoopConfig$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface.
You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.
To learn how to create a custom HTML template, see Create Custom Worker Task Template.
To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see Create and Delete a Worker Task Templates.
', 'HumanTaskUiSummary$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface.
', 'RenderUiTemplateRequest$HumanTaskUiArn' => 'The HumanTaskUiArn
of the worker UI that you want to render. Do not provide a HumanTaskUiArn
if you use the UiTemplate
parameter.
See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
', 'UiConfig$HumanTaskUiArn' => 'The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace aws-region
with the Amazon Web Services Region you are creating your labeling job in. For example, replace aws-region
with us-west-1
if you create a labeling job in US West (N. California).
Named Entity Recognition
Use the following HumanTaskUiArn
for named entity recognition labeling jobs:
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
3D Point Cloud HumanTaskUiArns
Use this HumanTaskUiArn
for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn
for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn
for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArns
Use this HumanTaskUiArn
for video frame object detection and video frame object detection adjustment labeling jobs.
arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this HumanTaskUiArn
for video frame object tracking and video frame object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
The name of the user interface you are creating.
', 'DeleteHumanTaskUiRequest$HumanTaskUiName' => 'The name of the human task user interface (work task template) you want to delete.
', 'DescribeHumanTaskUiRequest$HumanTaskUiName' => 'The name of the human task user interface (worker task template) you want information about.
', 'DescribeHumanTaskUiResponse$HumanTaskUiName' => 'The name of the human task user interface (worker task template).
', 'HumanTaskUiSummary$HumanTaskUiName' => 'The name of the human task user interface.
', ], ], 'HumanTaskUiStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHumanTaskUiResponse$HumanTaskUiStatus' => 'The status of the human task user interface (worker task template). Valid values are listed below.
', ], ], 'HumanTaskUiSummaries' => [ 'base' => NULL, 'refs' => [ 'ListHumanTaskUisResponse$HumanTaskUiSummaries' => 'An array of objects describing the human task user interfaces.
', ], ], 'HumanTaskUiSummary' => [ 'base' => 'Container for human task user interface information.
', 'refs' => [ 'HumanTaskUiSummaries$member' => NULL, ], ], 'HyperParameterAlgorithmSpecification' => [ 'base' => 'Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
', 'refs' => [ 'HyperParameterTrainingJobDefinition$AlgorithmSpecification' => 'The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
', ], ], 'HyperParameterKey' => [ 'base' => NULL, 'refs' => [ 'HyperParameters$key' => NULL, ], ], 'HyperParameterScalingType' => [ 'base' => NULL, 'refs' => [ 'ContinuousParameterRange$ScalingType' => 'The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.
Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.
The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Defines a hyperparameter to be used by an algorithm.
', 'refs' => [ 'HyperParameterSpecifications$member' => NULL, ], ], 'HyperParameterSpecifications' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$SupportedHyperParameters' => 'A list of the HyperParameterSpecification
objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
Defines the training jobs launched by a hyperparameter tuning job.
', 'refs' => [ 'CreateHyperParameterTuningJobRequest$TrainingJobDefinition' => 'The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
', 'DescribeHyperParameterTuningJobResponse$TrainingJobDefinition' => 'The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.
', 'HyperParameterTrainingJobDefinitions$member' => NULL, 'HyperParameterTuningJobSearchEntity$TrainingJobDefinition' => NULL, ], ], 'HyperParameterTrainingJobDefinitionName' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobDefinition$DefinitionName' => 'The job definition name.
', 'HyperParameterTrainingJobSummary$TrainingJobDefinitionName' => 'The training job definition name.
', ], ], 'HyperParameterTrainingJobDefinitions' => [ 'base' => NULL, 'refs' => [ 'CreateHyperParameterTuningJobRequest$TrainingJobDefinitions' => 'A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
', 'DescribeHyperParameterTuningJobResponse$TrainingJobDefinitions' => 'A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
', 'HyperParameterTuningJobSearchEntity$TrainingJobDefinitions' => 'The job definitions included in a hyperparameter tuning job.
', ], ], 'HyperParameterTrainingJobEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobEnvironmentMap$key' => NULL, ], ], 'HyperParameterTrainingJobEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobDefinition$Environment' => 'An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.
The maximum number of items specified for Map Entries
refers to the maximum number of environment variables for each TrainingJobDefinition
and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can\'t exceed the maximum number specified.
A list of TrainingJobSummary objects that describe the training jobs that the ListTrainingJobsForHyperParameterTuningJob
request returned.
The container for the summary information about a training job.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$BestTrainingJob' => 'A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.
', 'DescribeHyperParameterTuningJobResponse$OverallBestTrainingJob' => 'If the hyperparameter tuning job is an warm start tuning job with a WarmStartType
of IDENTICAL_DATA_AND_ALGORITHM
, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.
The strategy that determines the order of preference for resources specified in InstanceConfigs
used in hyperparameter optimization.
The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These resources include compute instances and storage volumes. Specify one or more compute instance configurations and allocation strategies to select resources (optional).
', 'refs' => [ 'HyperParameterTuningInstanceConfigs$member' => NULL, ], ], 'HyperParameterTuningInstanceConfigs' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningResourceConfig$InstanceConfigs' => 'A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The AllocationStrategy
controls the order in which multiple configurations provided in InstanceConfigs
are used.
If you only want to use a single instance configuration inside the HyperParameterTuningResourceConfig
API, do not provide a value for InstanceConfigs
. Instead, use InstanceType
, VolumeSizeInGB
and InstanceCount
. If you use InstanceConfigs
, do not provide values for InstanceType
, VolumeSizeInGB
or InstanceCount
.
The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of the tuning job.
', 'DescribeTrainingJobResponse$TuningJobArn' => 'The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of the tuning job.
', 'TrainingJob$TuningJobArn' => 'The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
', 'TuningJobStepMetaData$Arn' => 'The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
', ], ], 'HyperParameterTuningJobCompletionDetails' => [ 'base' => 'A structure that contains runtime information about both current and completed hyperparameter tuning jobs.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$TuningJobCompletionDetails' => 'Tuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.
', 'HyperParameterTuningJobSearchEntity$TuningJobCompletionDetails' => 'Information about either a current or completed hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobConfig' => [ 'base' => 'Configures a hyperparameter tuning job.
', 'refs' => [ 'CreateHyperParameterTuningJobRequest$HyperParameterTuningJobConfig' => 'The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobConfig' => 'The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobConfig' => NULL, ], ], 'HyperParameterTuningJobConsumedResources' => [ 'base' => 'The total resources consumed by your hyperparameter tuning job.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$ConsumedResources' => NULL, 'HyperParameterTuningJobSearchEntity$ConsumedResources' => 'The total amount of resources consumed by a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobName' => [ 'base' => NULL, 'refs' => [ 'CreateHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
', 'DescribeHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job.
', 'HyperParameterTrainingJobSummary$TuningJobName' => 'The HyperParameter tuning job that launched the training job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobName' => 'The name of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobName' => 'The name of the tuning job.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job whose training jobs you want to list.
', 'ParentHyperParameterTuningJob$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
', 'StopHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job to stop.
', ], ], 'HyperParameterTuningJobObjective' => [ 'base' => 'Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type
parameter. If you want to define a custom objective metric, see Define metrics and environment variables.
The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
', 'HyperParameterTuningJobObjectives$member' => NULL, ], ], 'HyperParameterTuningJobObjectiveType' => [ 'base' => NULL, 'refs' => [ 'FinalHyperParameterTuningJobObjectiveMetric$Type' => 'Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
', 'HyperParameterTuningJobObjective$Type' => 'Whether to minimize or maximize the objective metric.
', ], ], 'HyperParameterTuningJobObjectives' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$SupportedTuningJobObjectiveMetrics' => 'A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobSearchEntity' => [ 'base' => 'An entity returned by the SearchRecord API containing the properties of a hyperparameter tuning job.
', 'refs' => [ 'SearchRecord$HyperParameterTuningJob' => 'The properties of a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListHyperParameterTuningJobsRequest$SortBy' => 'The field to sort results by. The default is Name
.
The status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobStatus' => 'The status of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobStatus' => 'The status of the tuning job.
', 'ListHyperParameterTuningJobsRequest$StatusEquals' => 'A filter that returns only tuning jobs with the specified status.
', ], ], 'HyperParameterTuningJobStrategyConfig' => [ 'base' => 'The configuration for a training job launched by a hyperparameter tuning job. Choose Bayesian
for Bayesian optimization, and Random
for random search optimization. For more advanced use cases, use Hyperband
, which evaluates objective metrics for training jobs after every epoch. For more information about strategies, see How Hyperparameter Tuning Works.
The configuration for the Hyperband
optimization strategy. This parameter should be provided only if Hyperband
is selected as the strategy for HyperParameterTuningJobConfig
.
The strategy hyperparameter tuning uses to find the best combination of hyperparameters for your model.
', 'refs' => [ 'HyperParameterTuningJobConfig$Strategy' => 'Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.
', 'HyperParameterTuningJobSummary$Strategy' => 'Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to evaluate at each iteration.
', ], ], 'HyperParameterTuningJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListHyperParameterTuningJobsResponse$HyperParameterTuningJobSummaries' => 'A list of HyperParameterTuningJobSummary objects that describe the tuning jobs that the ListHyperParameterTuningJobs
request returned.
Provides summary information about a hyperparameter tuning job.
', 'refs' => [ 'HyperParameterTuningJobSummaries$member' => NULL, ], ], 'HyperParameterTuningJobWarmStartConfig' => [ 'base' => 'Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM
as the WarmStartType
value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
', 'HyperParameterTuningJobSearchEntity$WarmStartConfig' => NULL, ], ], 'HyperParameterTuningJobWarmStartType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningJobWarmStartConfig$WarmStartType' => 'Specifies one of the following:
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The maximum time in seconds that a hyperparameter tuning job can run.
', ], ], 'HyperParameterTuningResourceConfig' => [ 'base' => 'The configuration of resources, including compute instances and storage volumes for use in training jobs launched by hyperparameter tuning jobs. HyperParameterTuningResourceConfig
is similar to ResourceConfig
, but has the additional InstanceConfigs
and AllocationStrategy
fields to allow for flexible instance management. Specify one or more instance types, count, and the allocation strategy for instance selection.
HyperParameterTuningResourceConfig
supports the capabilities of ResourceConfig
with the exception of KeepAlivePeriodInSeconds
. Hyperparameter tuning jobs use warm pools by default, which reuse clusters between training jobs.
The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File
for TrainingInputMode
in the AlgorithmSpecification
parameter to additionally store training data in the storage volume (optional).
The default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.
', 'HyperParameters$value' => NULL, ], ], 'HyperParameters' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$HyperParameters' => 'Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint
.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Algorithm-specific parameters.
', 'HyperParameterTrainingJobDefinition$StaticHyperParameters' => 'Specifies the values of hyperparameters that do not change for the tuning job.
', 'HyperParameterTrainingJobSummary$TunedHyperParameters' => 'A list of the hyperparameters for which you specified ranges to search.
', 'TrainingJob$HyperParameters' => 'Algorithm-specific parameters.
', 'TrainingJobDefinition$HyperParameters' => 'The hyperparameters used for the training job.
', ], ], 'HyperbandStrategyConfig' => [ 'base' => 'The configuration for Hyperband
, a multi-fidelity based hyperparameter tuning strategy. Hyperband
uses the final and intermediate results of a training job to dynamically allocate resources to utilized hyperparameter configurations while automatically stopping under-performing configurations. This parameter should be provided only if Hyperband
is selected as the StrategyConfig
under the HyperParameterTuningJobConfig
API.
The configuration for the object that specifies the Hyperband
strategy. This parameter is only supported for the Hyperband
selection for Strategy
within the HyperParameterTuningJobConfig
API.
The maximum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. Once a job reaches the MaxResource
value, it is stopped. If a value for MaxResource
is not provided, and Hyperband
is selected as the hyperparameter tuning strategy, HyperbandTrainingJ
attempts to infer MaxResource
from the following keys (if present) in StaticsHyperParameters:
epochs
numepochs
n-epochs
n_epochs
num_epochs
If HyperbandStrategyConfig
is unable to infer a value for MaxResource
, it generates a validation error. The maximum value is 20,000 epochs. All metrics that correspond to an objective metric are used to derive early stopping decisions. For distributive training jobs, ensure that duplicate metrics are not printed in the logs across the individual nodes in a training job. If multiple nodes are publishing duplicate or incorrect metrics, training jobs may make an incorrect stopping decision and stop the job prematurely.
The minimum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. If the value for MinResource
has not been reached, the training job is not stopped by Hyperband
.
The IAM Identity details associated with the user. These details are associated with model package groups, model packages and project entities only.
', 'refs' => [ 'UserContext$IamIdentity' => 'The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
', ], ], 'IdempotencyToken' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'DeletePipelineRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'RetryPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', 'SendPipelineExecutionStepFailureRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'SendPipelineExecutionStepSuccessRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'StartPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', 'StopPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', ], ], 'IdentityProviderOAuthSetting' => [ 'base' => 'The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external data source, such as Snowflake.
', 'refs' => [ 'IdentityProviderOAuthSettings$member' => NULL, ], ], 'IdentityProviderOAuthSettings' => [ 'base' => NULL, 'refs' => [ 'CanvasAppSettings$IdentityProviderOAuthSettings' => 'The settings for connecting to an external data source with OAuth.
', ], ], 'Image' => [ 'base' => 'A SageMaker image. A SageMaker image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker ImageVersion
.
The ARN of the image.
', 'DescribeImageResponse$ImageArn' => 'The ARN of the image.
', 'DescribeImageVersionResponse$ImageArn' => 'The ARN of the image the version is based on.
', 'Image$ImageArn' => 'The ARN of the image.
', 'ImageVersion$ImageArn' => 'The ARN of the image the version is based on.
', 'ResourceSpec$SageMakerImageArn' => 'The ARN of the SageMaker image that the image version belongs to.
', 'UpdateImageResponse$ImageArn' => 'The ARN of the image.
', ], ], 'ImageBaseImage' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$BaseImage' => 'The registry path of the container image to use as the starting point for this version. The path is an Amazon Elastic Container Registry (ECR) URI in the following format:
<acct-id>.dkr.ecr.<region>.amazonaws.com/<repo-name[:tag] or [@digest]>
The registry path of the container image on which this image version is based.
', ], ], 'ImageClassificationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the image classification problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$ImageClassificationJobConfig' => 'Settings used to configure an AutoML job V2 for the image classification problem type.
', ], ], 'ImageConfig' => [ 'base' => 'Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
', 'refs' => [ 'ContainerDefinition$ImageConfig' => 'Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The registry path of the container image that contains this image version.
', ], ], 'ImageDeleteProperty' => [ 'base' => NULL, 'refs' => [ 'ImageDeletePropertyList$member' => NULL, ], ], 'ImageDeletePropertyList' => [ 'base' => NULL, 'refs' => [ 'UpdateImageRequest$DeleteProperties' => 'A list of properties to delete. Only the Description
and DisplayName
properties can be deleted.
The description of the image.
', 'DescribeImageResponse$Description' => 'The description of the image.
', 'Image$Description' => 'The description of the image.
', 'UpdateImageRequest$Description' => 'The new description for the image.
', ], ], 'ImageDigest' => [ 'base' => NULL, 'refs' => [ 'ModelPackageContainerDefinition$ImageDigest' => 'An MD5 hash of the training algorithm that identifies the Docker image used for training.
', 'TrainingSpecification$TrainingImageDigest' => 'An MD5 hash of the training algorithm that identifies the Docker image used for training.
', ], ], 'ImageDisplayName' => [ 'base' => NULL, 'refs' => [ 'CreateImageRequest$DisplayName' => 'The display name of the image. If not provided, ImageName
is displayed.
The name of the image as displayed.
', 'Image$DisplayName' => 'The name of the image as displayed.
', 'UpdateImageRequest$DisplayName' => 'The new display name for the image.
', ], ], 'ImageName' => [ 'base' => NULL, 'refs' => [ 'CreateImageRequest$ImageName' => 'The name of the image. Must be unique to your account.
', 'CreateImageVersionRequest$ImageName' => 'The ImageName
of the Image
to create a version of.
The name of the CustomImage. Must be unique to your account.
', 'DeleteImageRequest$ImageName' => 'The name of the image to delete.
', 'DeleteImageVersionRequest$ImageName' => 'The name of the image to delete.
', 'DescribeImageRequest$ImageName' => 'The name of the image to describe.
', 'DescribeImageResponse$ImageName' => 'The name of the image.
', 'DescribeImageVersionRequest$ImageName' => 'The name of the image.
', 'Image$ImageName' => 'The name of the image.
', 'ListAliasesRequest$ImageName' => 'The name of the image.
', 'ListImageVersionsRequest$ImageName' => 'The name of the image to list the versions of.
', 'UpdateImageRequest$ImageName' => 'The name of the image to update.
', 'UpdateImageVersionRequest$ImageName' => 'The name of the image.
', ], ], 'ImageNameContains' => [ 'base' => NULL, 'refs' => [ 'ListImagesRequest$NameContains' => 'A filter that returns only images whose name contains the specified string.
', ], ], 'ImageSortBy' => [ 'base' => NULL, 'refs' => [ 'ListImagesRequest$SortBy' => 'The property used to sort results. The default value is CREATION_TIME
.
The sort order. The default value is DESCENDING
.
The status of the image.
', 'Image$ImageStatus' => 'The status of the image.
', ], ], 'ImageUri' => [ 'base' => NULL, 'refs' => [ 'AppSpecification$ImageUri' => 'The container image to be run by the processing job.
', 'DataQualityAppSpecification$ImageUri' => 'The container image that the data quality monitoring job runs.
', 'ModelBiasAppSpecification$ImageUri' => 'The container image to be run by the model bias job.
', 'ModelExplainabilityAppSpecification$ImageUri' => 'The container image to be run by the model explainability job.
', 'ModelQualityAppSpecification$ImageUri' => 'The address of the container image that the monitoring job runs.
', 'MonitoringAppSpecification$ImageUri' => 'The container image to be run by the monitoring job.
', ], ], 'ImageVersion' => [ 'base' => 'A version of a SageMaker Image
. A version represents an existing container image.
The SageMakerImageVersionAlias of the image to launch with. This value is in SemVer 2.0.0 versioning format.
', ], ], 'ImageVersionArn' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionResponse$ImageVersionArn' => 'The ARN of the image version.
', 'DescribeImageVersionResponse$ImageVersionArn' => 'The ARN of the version.
', 'ImageVersion$ImageVersionArn' => 'The ARN of the version.
', 'ResourceSpec$SageMakerImageVersionArn' => 'The ARN of the image version created on the instance.
', 'UpdateImageVersionResponse$ImageVersionArn' => 'The ARN of the image version.
', ], ], 'ImageVersionNumber' => [ 'base' => NULL, 'refs' => [ 'CustomImage$ImageVersionNumber' => 'The version number of the CustomImage.
', 'DeleteImageVersionRequest$Version' => 'The version to delete.
', 'DescribeImageVersionRequest$Version' => 'The version of the image. If not specified, the latest version is described.
', 'DescribeImageVersionResponse$Version' => 'The version number.
', 'ImageVersion$Version' => 'The version number.
', 'ListAliasesRequest$Version' => 'The version of the image. If image version is not specified, the aliases of all versions of the image are listed.
', 'UpdateImageVersionRequest$Version' => 'The version of the image.
', ], ], 'ImageVersionSortBy' => [ 'base' => NULL, 'refs' => [ 'ListImageVersionsRequest$SortBy' => 'The property used to sort results. The default value is CREATION_TIME
.
The sort order. The default value is DESCENDING
.
The status of the version.
', 'ImageVersion$ImageVersionStatus' => 'The status of the version.
', ], ], 'ImageVersions' => [ 'base' => NULL, 'refs' => [ 'ListImageVersionsResponse$ImageVersions' => 'A list of versions and their properties.
', ], ], 'Images' => [ 'base' => NULL, 'refs' => [ 'ListImagesResponse$Images' => 'A list of images and their properties.
', ], ], 'ImportHubContentRequest' => [ 'base' => NULL, 'refs' => [], ], 'ImportHubContentResponse' => [ 'base' => NULL, 'refs' => [], ], 'InferenceComponentArn' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceComponentOutput$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', 'DescribeInferenceComponentOutput$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', 'InferenceComponentSummary$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', 'UpdateInferenceComponentOutput$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', 'UpdateInferenceComponentRuntimeConfigOutput$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', ], ], 'InferenceComponentComputeResourceRequirements' => [ 'base' => 'Defines the compute resources to allocate to run a model that you assign to an inference component. These resources include CPU cores, accelerators, and memory.
', 'refs' => [ 'InferenceComponentSpecification$ComputeResourceRequirements' => 'The compute resources allocated to run the model assigned to the inference component.
', 'InferenceComponentSpecificationSummary$ComputeResourceRequirements' => 'The compute resources allocated to run the model assigned to the inference component.
', ], ], 'InferenceComponentContainerSpecification' => [ 'base' => 'Defines a container that provides the runtime environment for a model that you deploy with an inference component.
', 'refs' => [ 'InferenceComponentSpecification$Container' => 'Defines a container that provides the runtime environment for a model that you deploy with an inference component.
', ], ], 'InferenceComponentContainerSpecificationSummary' => [ 'base' => 'Details about the resources that are deployed with this inference component.
', 'refs' => [ 'InferenceComponentSpecificationSummary$Container' => 'Details about the container that provides the runtime environment for the model that is deployed with the inference component.
', ], ], 'InferenceComponentCopyCount' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentRuntimeConfig$CopyCount' => 'The number of runtime copies of the model container to deploy with the inference component. Each copy can serve inference requests.
', 'InferenceComponentRuntimeConfigSummary$DesiredCopyCount' => 'The number of runtime copies of the model container that you requested to deploy with the inference component.
', 'InferenceComponentRuntimeConfigSummary$CurrentCopyCount' => 'The number of runtime copies of the model container that are currently deployed.
', ], ], 'InferenceComponentName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceComponentInput$InferenceComponentName' => 'A unique name to assign to the inference component.
', 'DeleteInferenceComponentInput$InferenceComponentName' => 'The name of the inference component to delete.
', 'DescribeInferenceComponentInput$InferenceComponentName' => 'The name of the inference component.
', 'DescribeInferenceComponentOutput$InferenceComponentName' => 'The name of the inference component.
', 'InferenceComponentSummary$InferenceComponentName' => 'The name of the inference component.
', 'UpdateInferenceComponentInput$InferenceComponentName' => 'The name of the inference component.
', 'UpdateInferenceComponentRuntimeConfigInput$InferenceComponentName' => 'The name of the inference component to update.
', ], ], 'InferenceComponentNameContains' => [ 'base' => NULL, 'refs' => [ 'ListInferenceComponentsInput$NameContains' => 'Filters the results to only those inference components with a name that contains the specified string.
', ], ], 'InferenceComponentRuntimeConfig' => [ 'base' => 'Runtime settings for a model that is deployed with an inference component.
', 'refs' => [ 'CreateInferenceComponentInput$RuntimeConfig' => 'Runtime settings for a model that is deployed with an inference component.
', 'UpdateInferenceComponentInput$RuntimeConfig' => 'Runtime settings for a model that is deployed with an inference component.
', 'UpdateInferenceComponentRuntimeConfigInput$DesiredRuntimeConfig' => 'Runtime settings for a model that is deployed with an inference component.
', ], ], 'InferenceComponentRuntimeConfigSummary' => [ 'base' => 'Details about the runtime settings for the model that is deployed with the inference component.
', 'refs' => [ 'DescribeInferenceComponentOutput$RuntimeConfig' => 'Details about the runtime settings for the model that is deployed with the inference component.
', ], ], 'InferenceComponentSortKey' => [ 'base' => NULL, 'refs' => [ 'ListInferenceComponentsInput$SortBy' => 'The field by which to sort the inference components in the response. The default is CreationTime
.
Details about the resources to deploy with this inference component, including the model, container, and compute resources.
', 'refs' => [ 'CreateInferenceComponentInput$Specification' => 'Details about the resources to deploy with this inference component, including the model, container, and compute resources.
', 'UpdateInferenceComponentInput$Specification' => 'Details about the resources to deploy with this inference component, including the model, container, and compute resources.
', ], ], 'InferenceComponentSpecificationSummary' => [ 'base' => 'Details about the resources that are deployed with this inference component.
', 'refs' => [ 'DescribeInferenceComponentOutput$Specification' => 'Details about the resources that are deployed with this inference component.
', ], ], 'InferenceComponentStartupParameters' => [ 'base' => 'Settings that take effect while the model container starts up.
', 'refs' => [ 'InferenceComponentSpecification$StartupParameters' => 'Settings that take effect while the model container starts up.
', 'InferenceComponentSpecificationSummary$StartupParameters' => 'Settings that take effect while the model container starts up.
', ], ], 'InferenceComponentStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceComponentOutput$InferenceComponentStatus' => 'The status of the inference component.
', 'InferenceComponentSummary$InferenceComponentStatus' => 'The status of the inference component.
', 'ListInferenceComponentsInput$StatusEquals' => 'Filters the results to only those inference components with the specified status.
', ], ], 'InferenceComponentSummary' => [ 'base' => 'A summary of the properties of an inference component.
', 'refs' => [ 'InferenceComponentSummaryList$member' => NULL, ], ], 'InferenceComponentSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListInferenceComponentsOutput$InferenceComponents' => 'A list of inference components and their properties that matches any of the filters you specified in the request.
', ], ], 'InferenceExecutionConfig' => [ 'base' => 'Specifies details about how containers in a multi-container endpoint are run.
', 'refs' => [ 'CreateModelInput$InferenceExecutionConfig' => 'Specifies details of how containers in a multi-container endpoint are called.
', 'DescribeModelOutput$InferenceExecutionConfig' => 'Specifies details of how containers in a multi-container endpoint are called.
', 'Model$InferenceExecutionConfig' => NULL, ], ], 'InferenceExecutionMode' => [ 'base' => NULL, 'refs' => [ 'InferenceExecutionConfig$Mode' => 'How containers in a multi-container are run. The following values are valid.
SERIAL
- Containers run as a serial pipeline.
DIRECT
- Only the individual container that you specify is run.
The ARN for your inference experiment.
', 'DeleteInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the deleted inference experiment.
', 'DescribeInferenceExperimentResponse$Arn' => 'The ARN of the inference experiment being described.
', 'StartInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the started inference experiment to start.
', 'StopInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the stopped inference experiment.
', 'UpdateInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the updated inference experiment.
', ], ], 'InferenceExperimentDataStorageConfig' => [ 'base' => 'The Amazon S3 location and configuration for storing inference request and response data.
', 'refs' => [ 'CreateInferenceExperimentRequest$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
', 'DescribeInferenceExperimentResponse$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
', 'UpdateInferenceExperimentRequest$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
', ], ], 'InferenceExperimentDescription' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Description' => 'A description for the inference experiment.
', 'DescribeInferenceExperimentResponse$Description' => 'The description of the inference experiment.
', 'InferenceExperimentSummary$Description' => 'The description of the inference experiment.
', 'UpdateInferenceExperimentRequest$Description' => 'The description of the inference experiment.
', ], ], 'InferenceExperimentList' => [ 'base' => NULL, 'refs' => [ 'ListInferenceExperimentsResponse$InferenceExperiments' => 'List of inference experiments.
', ], ], 'InferenceExperimentName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Name' => 'The name for the inference experiment.
', 'DeleteInferenceExperimentRequest$Name' => 'The name of the inference experiment you want to delete.
', 'DescribeInferenceExperimentRequest$Name' => 'The name of the inference experiment to describe.
', 'DescribeInferenceExperimentResponse$Name' => 'The name of the inference experiment.
', 'InferenceExperimentSummary$Name' => 'The name of the inference experiment.
', 'StartInferenceExperimentRequest$Name' => 'The name of the inference experiment to start.
', 'StopInferenceExperimentRequest$Name' => 'The name of the inference experiment to stop.
', 'UpdateInferenceExperimentRequest$Name' => 'The name of the inference experiment to be updated.
', ], ], 'InferenceExperimentSchedule' => [ 'base' => 'The start and end times of an inference experiment.
The maximum duration that you can set for an inference experiment is 30 days.
', 'refs' => [ 'CreateInferenceExperimentRequest$Schedule' => 'The duration for which you want the inference experiment to run. If you don\'t specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
', 'DescribeInferenceExperimentResponse$Schedule' => 'The duration for which the inference experiment ran or will run.
', 'InferenceExperimentSummary$Schedule' => 'The duration for which the inference experiment ran or will run.
The maximum duration that you can set for an inference experiment is 30 days.
', 'UpdateInferenceExperimentRequest$Schedule' => ' The duration for which the inference experiment will run. If the status of the inference experiment is Created
, then you can update both the start and end dates. If the status of the inference experiment is Running
, then you can update only the end date.
The status of the inference experiment. The following are the possible statuses for an inference experiment:
Creating
- Amazon SageMaker is creating your experiment.
Created
- Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.
Updating
- When you make changes to your experiment, your experiment shows as updating.
Starting
- Amazon SageMaker is beginning your experiment.
Running
- Your experiment is in progress.
Stopping
- Amazon SageMaker is stopping your experiment.
Completed
- Your experiment has completed.
Cancelled
- When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.
The status of the inference experiment.
', 'ListInferenceExperimentsRequest$StatusEquals' => 'Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment.
', ], ], 'InferenceExperimentStatusReason' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceExperimentResponse$StatusReason' => ' The error message or client-specified Reason
from the StopInferenceExperiment API, that explains the status of the inference experiment.
The error message for the inference experiment status result.
', 'StopInferenceExperimentRequest$Reason' => 'The reason for stopping the experiment.
', ], ], 'InferenceExperimentStopDesiredState' => [ 'base' => NULL, 'refs' => [ 'StopInferenceExperimentRequest$DesiredState' => 'The desired state of the experiment after stopping. The possible states are the following:
Completed
: The experiment completed successfully
Cancelled
: The experiment was canceled
Lists a summary of properties of an inference experiment.
', 'refs' => [ 'InferenceExperimentList$member' => NULL, ], ], 'InferenceExperimentType' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Type' => 'The type of the inference experiment that you want to run. The following types of experiments are possible:
ShadowMode
: You can use this type to validate a shadow variant. For more information, see Shadow tests.
The type of the inference experiment.
', 'InferenceExperimentSummary$Type' => 'The type of the inference experiment.
', 'ListInferenceExperimentsRequest$Type' => 'Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment.
', ], ], 'InferenceImage' => [ 'base' => NULL, 'refs' => [ 'DescribeCompilationJobResponse$InferenceImage' => 'The inference image to use when compiling a model. Specify an image only if the target device is a cloud instance.
', ], ], 'InferenceMetrics' => [ 'base' => 'The metrics for an existing endpoint compared in an Inference Recommender job.
', 'refs' => [ 'EndpointPerformance$Metrics' => 'The metrics for an existing endpoint.
', 'RecommendationJobInferenceBenchmark$EndpointMetrics' => NULL, ], ], 'InferenceRecommendation' => [ 'base' => 'A list of recommendations made by Amazon SageMaker Inference Recommender.
', 'refs' => [ 'InferenceRecommendations$member' => NULL, ], ], 'InferenceRecommendations' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$InferenceRecommendations' => 'The recommendations made by Inference Recommender.
', ], ], 'InferenceRecommendationsJob' => [ 'base' => 'A structure that contains a list of recommendation jobs.
', 'refs' => [ 'InferenceRecommendationsJobs$member' => NULL, ], ], 'InferenceRecommendationsJobStep' => [ 'base' => 'A returned array object for the Steps
response field in the ListInferenceRecommendationsJobSteps API command.
A list of all subtask details in Inference Recommender.
', ], ], 'InferenceRecommendationsJobs' => [ 'base' => NULL, 'refs' => [ 'ListInferenceRecommendationsJobsResponse$InferenceRecommendationsJobs' => 'The recommendations created from the Amazon SageMaker Inference Recommender job.
', ], ], 'InferenceSpecification' => [ 'base' => 'Defines how to perform inference generation after a training job is run.
', 'refs' => [ 'BatchDescribeModelPackageSummary$InferenceSpecification' => NULL, 'CreateAlgorithmInput$InferenceSpecification' => 'Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
Specifies details about inference jobs that can be run with models based on this model package, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the model package supports for inference.
Details about inference jobs that the algorithm runs.
', 'DescribeModelPackageOutput$InferenceSpecification' => 'Details about inference jobs that can be run with models based on this model package.
', 'ModelPackage$InferenceSpecification' => 'Defines how to perform inference generation after a training job is run.
', ], ], 'InferenceSpecificationName' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$InferenceSpecificationName' => 'The inference specification name in the model package version.
', 'EndpointInputConfiguration$InferenceSpecificationName' => 'The inference specification name in the model package version.
', 'ModelConfiguration$InferenceSpecificationName' => 'The inference specification name in the model package version.
', ], ], 'InfraCheckConfig' => [ 'base' => 'Configuration information for the infrastructure health check of a training job. A SageMaker-provided health check tests the health of instance hardware and cluster network connectivity.
', 'refs' => [ 'CreateTrainingJobRequest$InfraCheckConfig' => 'Contains information about the infrastructure health check configuration for the training job.
', 'DescribeTrainingJobResponse$InfraCheckConfig' => 'Contains information about the infrastructure health check configuration for the training job.
', ], ], 'InitialInstanceCount' => [ 'base' => NULL, 'refs' => [ 'EndpointOutputConfiguration$InitialInstanceCount' => 'The number of instances recommended to launch initially.
', ], ], 'InitialNumberOfUsers' => [ 'base' => NULL, 'refs' => [ 'Phase$InitialNumberOfUsers' => 'Specifies how many concurrent users to start with. The value should be between 1 and 3.
', ], ], 'InitialTaskCount' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$InitialInstanceCount' => 'Number of instances to launch initially.
', ], ], 'InputConfig' => [ 'base' => 'Contains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', 'refs' => [ 'CreateCompilationJobRequest$InputConfig' => 'Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', 'DescribeCompilationJobResponse$InputConfig' => 'Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', ], ], 'InputDataConfig' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$InputDataConfig' => 'An array of Channel
objects. Each channel is a named input source. InputDataConfig
describes the input data and its location.
Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data, training_data
and validation_data
. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.
Your input must be in the same Amazon Web Services region as your training job.
', 'DescribeTrainingJobResponse$InputDataConfig' => 'An array of Channel
objects that describes each data input channel.
An array of Channel objects that specify the input for the training jobs that the tuning job launches.
', 'TrainingJob$InputDataConfig' => 'An array of Channel
objects that describes each data input channel.
Your input must be in the same Amazon Web Services region as your training job.
', 'TrainingJobDefinition$InputDataConfig' => 'An array of Channel
objects, each of which specifies an input source.
Whether to use File
or Pipe
input mode. In File
(default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe
mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
The allowed input mode, either FILE or PIPE.
In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.
In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
', ], ], 'InstanceGroup' => [ 'base' => 'Defines an instance group for heterogeneous cluster training. When requesting a training job using the CreateTrainingJob API, you can configure multiple instance groups .
', 'refs' => [ 'InstanceGroups$member' => NULL, ], ], 'InstanceGroupName' => [ 'base' => NULL, 'refs' => [ 'InstanceGroup$InstanceGroupName' => 'Specifies the name of the instance group.
', 'InstanceGroupNames$member' => NULL, ], ], 'InstanceGroupNames' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$InstanceGroupNames' => 'A list of names of instance groups that get data from the S3 data source.
', ], ], 'InstanceGroups' => [ 'base' => NULL, 'refs' => [ 'ResourceConfig$InstanceGroups' => 'The configuration of a heterogeneous cluster in JSON format.
', ], ], 'InstanceMetadataServiceConfiguration' => [ 'base' => 'Information on the IMDS configuration of the notebook instance
', 'refs' => [ 'CreateNotebookInstanceInput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', 'DescribeNotebookInstanceOutput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', 'UpdateNotebookInstanceInput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', ], ], 'InstanceType' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$InstanceType' => 'The type of ML compute instance to launch for the notebook instance.
', 'DescribeNotebookInstanceOutput$InstanceType' => 'The type of ML compute instance running on the notebook instance.
', 'NotebookInstanceSummary$InstanceType' => 'The type of ML compute instance that the notebook instance is running on.
', 'RealTimeInferenceConfig$InstanceType' => 'The instance type the model is deployed to.
', 'UpdateNotebookInstanceInput$InstanceType' => 'The Amazon ML compute instance type.
', ], ], 'Integer' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobRequest$ModelCardVersion' => 'The version of the model card to export. If a version is not provided, then the latest version of the model card is exported.
', 'DescribeDeviceResponse$MaxModels' => 'The maximum number of models.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentSuccess' => 'The number of edge devices with the successful deployment.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPending' => 'The number of edge devices yet to pick up deployment, or in progress.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentFailed' => 'The number of edge devices that failed the deployment.
', 'DescribeModelCardExportJobResponse$ModelCardVersion' => 'The version of the model card that the model export job exports.
', 'DescribeModelCardRequest$ModelCardVersion' => 'The version of the model card to describe. If a version is not provided, then the latest version of the model card is described.
', 'DescribeModelCardResponse$ModelCardVersion' => 'The version of the model card.
', 'DynamicScalingConfiguration$MinCapacity' => 'The recommended minimum capacity to specify for your autoscaling policy.
', 'DynamicScalingConfiguration$MaxCapacity' => 'The recommended maximum capacity to specify for your autoscaling policy.
', 'DynamicScalingConfiguration$ScaleInCooldown' => 'The recommended scale in cooldown time for your autoscaling policy.
', 'DynamicScalingConfiguration$ScaleOutCooldown' => 'The recommended scale out cooldown time for your autoscaling policy.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentSuccess' => 'The number of edge devices with the successful deployment.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPending' => 'The number of edge devices yet to pick up the deployment, or in progress.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentFailed' => 'The number of edge devices that failed the deployment.
', 'EdgeDeploymentStatus$EdgeDeploymentSuccessInStage' => 'The number of edge devices with the successful deployment in the current stage.
', 'EdgeDeploymentStatus$EdgeDeploymentPendingInStage' => 'The number of edge devices yet to pick up the deployment in current stage, or in progress.
', 'EdgeDeploymentStatus$EdgeDeploymentFailedInStage' => 'The number of edge devices that failed the deployment in current stage.
', 'HyperParameterTuningJobCompletionDetails$NumberOfTrainingJobsObjectiveNotImproving' => 'The number of training jobs launched by a tuning job that are not improving (1% or less) as measured by model performance evaluated against an objective function.
', 'HyperParameterTuningJobConsumedResources$RuntimeInSeconds' => 'The wall clock runtime in seconds used by your hyperparameter tuning job.
', 'InferenceMetrics$MaxInvocations' => 'The expected maximum number of requests per minute for the instance.
', 'InferenceMetrics$ModelLatency' => 'The expected model latency at maximum invocations per minute for the instance.
', 'ListModelCardExportJobsRequest$ModelCardVersion' => 'List export jobs for the model card with the specified version.
', 'ModelCard$ModelCardVersion' => 'The version of the model card.
', 'ModelCardExportJobSummary$ModelCardVersion' => 'The version of the model card that the export job exports.
', 'ModelCardVersionSummary$ModelCardVersion' => 'A version of the model card.
', 'ModelDashboardModelCard$ModelCardVersion' => 'The model card version.
', 'ModelLatencyThreshold$ValueInMilliseconds' => 'The model latency percentile value in milliseconds.
', 'PipelineExecutionStep$AttemptCount' => 'The current attempt of the execution step. For more information, see Retry Policy for SageMaker Pipelines steps.
', 'RecommendationJobStoppingConditions$MaxInvocations' => 'The maximum number of requests per minute expected for the endpoint.
', 'RecommendationMetrics$MaxInvocations' => 'The expected maximum number of requests per minute for the instance.
', 'RecommendationMetrics$ModelLatency' => 'The expected model latency at maximum invocation per minute for the instance.
', 'ScalingPolicyMetric$InvocationsPerInstance' => 'The number of invocations sent to a model, normalized by InstanceCount
in each ProductionVariant. 1/numberOfInstances
is sent as the value on each request, where numberOfInstances
is the number of active instances for the ProductionVariant behind the endpoint at the time of the request.
The interval of time taken by a model to respond as viewed from SageMaker. This interval includes the local communication times taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
', 'ScalingPolicyObjective$MinInvocationsPerMinute' => 'The minimum number of expected requests to your endpoint per minute.
', 'ScalingPolicyObjective$MaxInvocationsPerMinute' => 'The maximum number of expected requests to your endpoint per minute.
', ], ], 'IntegerParameterRange' => [ 'base' => 'For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
', 'refs' => [ 'IntegerParameterRanges$member' => NULL, ], ], 'IntegerParameterRangeSpecification' => [ 'base' => 'Defines the possible values for an integer hyperparameter.
', 'refs' => [ 'ParameterRange$IntegerParameterRangeSpecification' => 'A IntegerParameterRangeSpecification
object that defines the possible values for an integer hyperparameter.
The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.
', ], ], 'InvocationEndTime' => [ 'base' => NULL, 'refs' => [ 'InferenceRecommendation$InvocationEndTime' => 'A timestamp that shows when the benchmark completed.
', 'RecommendationJobInferenceBenchmark$InvocationEndTime' => 'A timestamp that shows when the benchmark completed.
', ], ], 'InvocationStartTime' => [ 'base' => NULL, 'refs' => [ 'InferenceRecommendation$InvocationStartTime' => 'A timestamp that shows when the benchmark started.
', 'RecommendationJobInferenceBenchmark$InvocationStartTime' => 'A timestamp that shows when the benchmark started.
', ], ], 'InvocationsMaxRetries' => [ 'base' => NULL, 'refs' => [ 'ModelClientConfig$InvocationsMaxRetries' => 'The maximum number of retries when invocation requests are failing. The default value is 3.
', ], ], 'InvocationsTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'ModelClientConfig$InvocationsTimeoutInSeconds' => 'The timeout value in seconds for an invocation request. The default value is 600.
', ], ], 'IotRoleAlias' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceFleetResponse$IotRoleAlias' => 'The Amazon Resource Name (ARN) alias created in Amazon Web Services Internet of Things (IoT).
', ], ], 'ItemIdentifierAttributeName' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$ItemIdentifierAttributeName' => 'The name of the column that represents the set of item identifiers for which you want to predict the target value.
', ], ], 'JobDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$JobDurationInSeconds' => 'Specifies the maximum duration of the job, in seconds. The maximum value is 18,000 seconds.
', ], ], 'JobReferenceCode' => [ 'base' => NULL, 'refs' => [ 'DescribeLabelingJobResponse$JobReferenceCode' => 'A unique identifier for work done as part of a labeling job.
', 'LabelingJobForWorkteamSummary$JobReferenceCode' => 'A unique identifier for a labeling job. You can use this to refer to a specific labeling job.
', ], ], 'JobReferenceCodeContains' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamRequest$JobReferenceCodeContains' => 'A filter the limits jobs to only the ones whose job reference code contains the specified string.
', ], ], 'JobType' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$JobType' => 'Indicates SageMaker job type compatibility.
TRAINING
: The image version is compatible with SageMaker training jobs.
INFERENCE
: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
Indicates SageMaker job type compatibility.
TRAINING
: The image version is compatible with SageMaker training jobs.
INFERENCE
: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
Indicates SageMaker job type compatibility.
TRAINING
: The image version is compatible with SageMaker training jobs.
INFERENCE
: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
Specifies the source of the data to join with the transformed data. The valid values are None
and Input
. The default value is None
, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set JoinSource
to Input
. You can specify OutputFilter
as an additional filter to select a portion of the joined dataset and store it in the output file.
For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput
. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput
key and the results are stored in SageMakerOutput
.
For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.
For information on how joining in applied, see Workflow for Associating Inferences with Input Records.
', ], ], 'JsonContentType' => [ 'base' => NULL, 'refs' => [ 'JsonContentTypes$member' => NULL, ], ], 'JsonContentTypes' => [ 'base' => NULL, 'refs' => [ 'CaptureContentTypeHeader$JsonContentTypes' => 'The list of all content type headers that SageMaker will treat as JSON and capture accordingly.
', ], ], 'JsonPath' => [ 'base' => NULL, 'refs' => [ 'DataProcessing$InputFilter' => 'A JSONPath expression used to select a portion of the input data to pass to the algorithm. Use the InputFilter
parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $
.
Examples: "$"
, "$[1:]"
, "$.features"
A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $
. If you specify indexes that aren\'t within the dimension size of the joined dataset, you get an error.
Examples: "$"
, "$[0,5:]"
, "$[\'id\',\'SageMakerOutput\']"
The configuration for the file system and kernels in a SageMaker image running as a JupyterLab app.
', 'refs' => [ 'AppImageConfigDetails$JupyterLabAppImageConfig' => 'The configuration for the file system and the runtime, such as the environment variables and entry point.
', 'CreateAppImageConfigRequest$JupyterLabAppImageConfig' => 'The JupyterLabAppImageConfig
. You can only specify one image kernel in the AppImageConfig
API. This kernel is shown to users before the image starts. After the image runs, all kernels are visible in JupyterLab.
The configuration of the JupyterLab app.
', 'UpdateAppImageConfigRequest$JupyterLabAppImageConfig' => 'The JupyterLab app running on the image.
', ], ], 'JupyterLabAppSettings' => [ 'base' => 'The settings for the JupyterLab application.
', 'refs' => [ 'UserSettings$JupyterLabAppSettings' => 'The settings for the JupyterLab application.
', ], ], 'JupyterServerAppSettings' => [ 'base' => 'The JupyterServer app settings.
', 'refs' => [ 'DefaultSpaceSettings$JupyterServerAppSettings' => NULL, 'SpaceSettings$JupyterServerAppSettings' => NULL, 'UserSettings$JupyterServerAppSettings' => 'The Jupyter server\'s app settings.
', ], ], 'KeepAlivePeriodInSeconds' => [ 'base' => 'Optional. Customer requested period in seconds for which the Training cluster is kept alive after the job is finished.', 'refs' => [ 'ResourceConfig$KeepAlivePeriodInSeconds' => 'The duration of time in seconds to retain configured resources in a warm pool for subsequent training jobs.
', 'ResourceConfigForUpdate$KeepAlivePeriodInSeconds' => 'The KeepAlivePeriodInSeconds
value specified in the ResourceConfig
to update.
The Amazon SageMaker Canvas application setting where you configure document querying.
', 'refs' => [ 'CanvasAppSettings$KendraSettings' => 'The settings for document querying.
', ], ], 'KernelDisplayName' => [ 'base' => NULL, 'refs' => [ 'KernelSpec$DisplayName' => 'The display name of the kernel.
', ], ], 'KernelGatewayAppSettings' => [ 'base' => 'The KernelGateway app settings.
', 'refs' => [ 'DefaultSpaceSettings$KernelGatewayAppSettings' => NULL, 'SpaceSettings$KernelGatewayAppSettings' => NULL, 'UserSettings$KernelGatewayAppSettings' => 'The kernel gateway app settings.
', ], ], 'KernelGatewayImageConfig' => [ 'base' => 'The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.
', 'refs' => [ 'AppImageConfigDetails$KernelGatewayImageConfig' => 'The configuration for the file system and kernels in the SageMaker image.
', 'CreateAppImageConfigRequest$KernelGatewayImageConfig' => 'The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.
', 'DescribeAppImageConfigResponse$KernelGatewayImageConfig' => 'The configuration of a KernelGateway app.
', 'UpdateAppImageConfigRequest$KernelGatewayImageConfig' => 'The new KernelGateway app to run on the image.
', ], ], 'KernelName' => [ 'base' => NULL, 'refs' => [ 'KernelSpec$Name' => 'The name of the Jupyter kernel in the image. This value is case sensitive.
', ], ], 'KernelSpec' => [ 'base' => 'The specification of a Jupyter kernel.
', 'refs' => [ 'KernelSpecs$member' => NULL, ], ], 'KernelSpecs' => [ 'base' => NULL, 'refs' => [ 'KernelGatewayImageConfig$KernelSpecs' => 'The specification of the Jupyter kernels in the image.
', ], ], 'Key' => [ 'base' => NULL, 'refs' => [ 'PipelineDefinitionS3Location$ObjectKey' => 'The object key (or key name) uniquely identifies the object in an S3 bucket.
', ], ], 'KmsKeyId' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
', 'AthenaDatasetDefinition$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
', 'AutoMLOutputDataConfig$KmsKeyId' => 'The Key Management Service (KMS) encryption key ID.
', 'AutoMLSecurityConfig$VolumeKmsKeyId' => 'The key used to encrypt stored data.
', 'BatchDataCaptureConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Use KmsKeyId
.
SageMaker uses Amazon Web Services KMS to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.
', 'CreateEdgePackagingJobRequest$ResourceKey' => 'The Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on.
', 'CreateEndpointConfigInput$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint
, UpdateEndpoint
requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a KmsKeyId
when using an instance type with local storage. If any of the models that you specify in the ProductionVariants
parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId
parameter. If you specify a value for KmsKeyId
when using any nitro-based instances with local storage, the call to CreateEndpointConfig
fails.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey
can be any of the following formats:
KMS key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
KMS key Alias
"alias/ExampleAlias"
Amazon Resource Name (ARN) of a KMS key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call kms:Encrypt
. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig
. If you use a bucket policy with an s3:PutObject
permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption
to "aws:kms"
. For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint
and UpdateEndpoint
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.
', 'DataCaptureConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key being used to encrypt the data in Amazon S3.
', 'DescribeDomainResponse$HomeEfsFileSystemKmsKeyId' => 'Use KmsKeyId
.
The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.
', 'DescribeEdgePackagingJobResponse$ResourceKey' => 'The Amazon Web Services KMS key to use when encrypting the EBS volume the job run on.
', 'DescribeEndpointConfigOutput$KmsKeyId' => 'Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
', 'DescribeInferenceExperimentResponse$KmsKey' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.
', 'DescribeNotebookInstanceOutput$KmsKeyId' => 'The Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
', 'EdgeOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account.
', 'FlowDefinitionOutputConfig$KmsKeyId' => 'The Amazon Key Management Service (KMS) key ID for server-side encryption.
', 'HyperParameterTuningResourceConfig$VolumeKmsKeyId' => 'A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a VolumeKmsKeyId
. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information.
The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3 server-side encryption.
', 'LabelingJobOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
If you provide your own KMS key ID, you must add the required permissions to your KMS key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
If you don\'t provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role\'s account to encrypt your output data.
If you use a bucket policy with an s3:PutObject
permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption
to "aws:kms"
. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.
You can only specify a VolumeKmsKeyId
when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob
. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see Output Data and Storage Volume Encryption.
The VolumeKmsKeyId
can be any of the following formats:
KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
A Key Management Service key ID to use for encrypting a model card.
', 'MonitoringClusterConfig$VolumeKmsKeyId' => 'The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
', 'MonitoringOutputConfig$KmsKeyId' => 'The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
', 'OnlineStoreSecurityConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side encryption.
The caller (either user or IAM role) of CreateFeatureGroup
must have below permissions to the OnlineStore
KmsKeyId
:
"kms:Encrypt"
"kms:Decrypt"
"kms:DescribeKey"
"kms:CreateGrant"
"kms:RetireGrant"
"kms:ReEncryptFrom"
"kms:ReEncryptTo"
"kms:GenerateDataKey"
"kms:ListAliases"
"kms:ListGrants"
"kms:RevokeGrant"
The caller (either user or IAM role) to all DataPlane operations (PutRecord
, GetRecord
, DeleteRecord
) must have the following permissions to the KmsKeyId
:
"kms:Decrypt"
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId
can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt
. If you don\'t provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide. If the output data is stored in Amazon S3 Express One Zone, it is encrypted with server-side encryption with Amazon S3 managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One Zone
The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob
, CreateTransformJob
, or CreateHyperParameterTuningJob
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId
when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId
can be an ID of a KMS key, ARN of a KMS key, alias of a KMS key, or alias of a KMS key. The KmsKeyId
is applied to all outputs.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId
can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt
. If you don\'t provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role\'s account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig
. If you use a bucket policy with an s3:PutObject
permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption
to "aws:kms"
. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint
and UpdateEndpoint
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.
The SageMaker execution role must have kms:CreateGrant
permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant
permission.
The KmsKeyId
can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
', 'RecommendationJobOutputConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey
permission.
The KmsKeyId
can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
', 'RedshiftDatasetDefinition$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
', 'ResourceConfig$VolumeKmsKeyId' => 'The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId
when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId
can be in any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt any objects written into the OfflineStore
S3 location.
The IAM roleARN
that is passed as a parameter to CreateFeatureGroup
must have below permissions to the KmsKeyId
:
"kms:GenerateDataKey"
When NotebookOutputOption
is Allowed
, the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId
can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateModel request. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
', 'TransformResources$VolumeKmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId
when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId
can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The Amazon Web Services Key Management Service (KMS) encryption key ID that is used to encrypt artifacts generated by Canvas in the Amazon S3 bucket.
', ], ], 'LabelAttributeName' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobRequest$LabelAttributeName' => 'The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName
must meet the following requirements.
The name can\'t end with "-metadata".
If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
Image semantic segmentation (SemanticSegmentation)
, and adjustment (AdjustmentSemanticSegmentation
) and verification (VerificationSemanticSegmentation
) labeling jobs for this task type.
Video frame object detection (VideoObjectDetection
), and adjustment and verification (AdjustmentVideoObjectDetection
) labeling jobs for this task type.
Video frame object tracking (VideoObjectTracking
), and adjustment and verification (AdjustmentVideoObjectTracking
) labeling jobs for this task type.
3D point cloud semantic segmentation (3DPointCloudSemanticSegmentation
), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation
) labeling jobs for this task type.
3D point cloud object tracking (3DPointCloudObjectTracking
), and adjustment and verification (Adjustment3DPointCloudObjectTracking
) labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a different LabelAttributeName
than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.
The attribute used as the label in the output manifest file.
', ], ], 'LabelCounter' => [ 'base' => NULL, 'refs' => [ 'LabelCounters$TotalLabeled' => 'The total number of objects labeled.
', 'LabelCounters$HumanLabeled' => 'The total number of objects labeled by a human worker.
', 'LabelCounters$MachineLabeled' => 'The total number of objects labeled by automated data labeling.
', 'LabelCounters$FailedNonRetryableError' => 'The total number of objects that could not be labeled due to an error.
', 'LabelCounters$Unlabeled' => 'The total number of objects not yet labeled.
', 'LabelCountersForWorkteam$HumanLabeled' => 'The total number of data objects labeled by a human worker.
', 'LabelCountersForWorkteam$PendingHuman' => 'The total number of data objects that need to be labeled by a human worker.
', 'LabelCountersForWorkteam$Total' => 'The total number of tasks in the labeling job.
', ], ], 'LabelCounters' => [ 'base' => 'Provides a breakdown of the number of objects labeled.
', 'refs' => [ 'DescribeLabelingJobResponse$LabelCounters' => 'Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn\'t be labeled, and the total number of objects labeled.
', 'LabelingJobSummary$LabelCounters' => 'Counts showing the progress of the labeling job.
', ], ], 'LabelCountersForWorkteam' => [ 'base' => 'Provides counts for human-labeled tasks in the labeling job.
', 'refs' => [ 'LabelingJobForWorkteamSummary$LabelCounters' => 'Provides information about the progress of a labeling job.
', ], ], 'LabelingJobAlgorithmSpecificationArn' => [ 'base' => NULL, 'refs' => [ 'LabelingJobAlgorithmsConfig$LabelingJobAlgorithmSpecificationArn' => 'Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
Text classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
Object detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
Semantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig
object must be supplied in order to use auto-labeling.
Configures the information required to perform automated data labeling.
', 'DescribeLabelingJobResponse$LabelingJobAlgorithmsConfig' => 'Configuration information for automated data labeling.
', ], ], 'LabelingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.
', 'DescribeLabelingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job.
', 'DescribeTrainingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
', 'DescribeTransformJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
', 'LabelingJobSummary$LabelingJobArn' => 'The Amazon Resource Name (ARN) assigned to the labeling job when it was created.
', 'TrainingJob$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job.
', 'TransformJob$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job that created the transform job.
', ], ], 'LabelingJobDataAttributes' => [ 'base' => 'Attributes of the data specified by the customer. Use these to describe the data to be labeled.
', 'refs' => [ 'LabelingJobInputConfig$DataAttributes' => 'Attributes of the data specified by the customer.
', ], ], 'LabelingJobDataSource' => [ 'base' => 'Provides information about the location of input data.
You must specify at least one of the following: S3DataSource
or SnsDataSource
.
Use SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource
is optional if you use SnsDataSource
to create a streaming labeling job.
The location of the input data.
', ], ], 'LabelingJobForWorkteamSummary' => [ 'base' => 'Provides summary information for a work team.
', 'refs' => [ 'LabelingJobForWorkteamSummaryList$member' => NULL, ], ], 'LabelingJobForWorkteamSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamResponse$LabelingJobSummaryList' => 'An array of LabelingJobSummary
objects, each describing a labeling job.
Input configuration information for a labeling job.
', 'refs' => [ 'CreateLabelingJobRequest$InputConfig' => 'Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following: S3DataSource
or SnsDataSource
.
Use SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.
Use S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource
is optional if you use SnsDataSource
to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers
to specify that your data is free of personally identifiable information and adult content.
Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
', 'LabelingJobSummary$InputConfig' => 'Input configuration for the labeling job.
', ], ], 'LabelingJobName' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobRequest$LabelingJobName' => 'The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName
is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.
The name of the labeling job to return information for.
', 'DescribeLabelingJobResponse$LabelingJobName' => 'The name assigned to the labeling job when it was created.
', 'LabelingJobForWorkteamSummary$LabelingJobName' => 'The name of the labeling job that the work team is assigned to.
', 'LabelingJobSummary$LabelingJobName' => 'The name of the labeling job.
', 'StopLabelingJobRequest$LabelingJobName' => 'The name of the labeling job to stop.
', ], ], 'LabelingJobOutput' => [ 'base' => 'Specifies the location of the output produced by the labeling job.
', 'refs' => [ 'DescribeLabelingJobResponse$LabelingJobOutput' => 'The location of the output produced by the labeling job.
', 'LabelingJobSummary$LabelingJobOutput' => 'The location of the output produced by the labeling job.
', ], ], 'LabelingJobOutputConfig' => [ 'base' => 'Output configuration information for a labeling job.
', 'refs' => [ 'CreateLabelingJobRequest$OutputConfig' => 'The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
', 'DescribeLabelingJobResponse$OutputConfig' => 'The location of the job\'s output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
', ], ], 'LabelingJobResourceConfig' => [ 'base' => 'Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.
', 'refs' => [ 'LabelingJobAlgorithmsConfig$LabelingJobResourceConfig' => 'Provides configuration information for a labeling job.
', ], ], 'LabelingJobS3DataSource' => [ 'base' => 'The Amazon S3 location of the input data objects.
', 'refs' => [ 'LabelingJobDataSource$S3DataSource' => 'The Amazon S3 location of the input data objects.
', ], ], 'LabelingJobSnsDataSource' => [ 'base' => 'An Amazon SNS data source used for streaming labeling jobs.
', 'refs' => [ 'LabelingJobDataSource$SnsDataSource' => 'An Amazon SNS data source used for streaming labeling jobs. To learn more, see Send Data to a Streaming Labeling Job.
', ], ], 'LabelingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeLabelingJobResponse$LabelingJobStatus' => 'The processing status of the labeling job.
', 'LabelingJobSummary$LabelingJobStatus' => 'The current status of the labeling job.
', 'ListLabelingJobsRequest$StatusEquals' => 'A filter that retrieves only labeling jobs with a specific status.
', ], ], 'LabelingJobStoppingConditions' => [ 'base' => 'A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
Labeling jobs fail after 30 days with an appropriate client error message.
A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
', 'DescribeLabelingJobResponse$StoppingConditions' => 'A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
', ], ], 'LabelingJobSummary' => [ 'base' => 'Provides summary information about a labeling job.
', 'refs' => [ 'LabelingJobSummaryList$member' => NULL, ], ], 'LabelingJobSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsResponse$LabelingJobSummaryList' => 'An array of LabelingJobSummary
objects, each describing a labeling job.
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn
. For custom labeling workflows, see Post-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Bounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn
. For custom labeling workflows, see Pre-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.
', 'LabelingJobSummary$AnnotationConsolidationLambdaArn' => 'The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see Annotation Consolidation.
', ], ], 'LambdaStepMetadata' => [ 'base' => 'Metadata for a Lambda step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Lambda' => 'The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.
', ], ], 'LandingUri' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlRequest$LandingUri' => 'The landing page that the user is directed to when accessing the presigned URL. Using this value, users can access Studio or Studio Classic, even if it is not the default experience for the domain. The supported values are:
studio::relative/path
: Directs users to the relative path in Studio.
app:JupyterServer:relative/path
: Directs users to the relative path in the Studio Classic application.
app:JupyterLab:relative/path
: Directs users to the relative path in the JupyterLab application.
app:RStudioServerPro:relative/path
: Directs users to the relative path in the RStudio application.
app:CodeEditor:relative/path
: Directs users to the relative path in the Code Editor, based on Code-OSS, Visual Studio Code - Open Source application.
app:Canvas:relative/path
: Directs users to the relative path in the Canvas application.
The default experience that the user is directed to when accessing the domain. The supported values are:
studio::
: Indicates that Studio is the default experience. This value can only be passed if StudioWebPortal
is set to ENABLED
.
app:JupyterServer:
: Indicates that Studio Classic is the default experience.
The date and time that the Git repository was last modified.
', 'CompilationJobSummary$LastModifiedTime' => 'The time when the model compilation job was last modified.
', 'DescribeCodeRepositoryOutput$LastModifiedTime' => 'The date and time that the repository was last changed.
', 'DescribeCompilationJobResponse$LastModifiedTime' => 'The time that the status of the model compilation job was last modified.
', 'DescribeDomainResponse$LastModifiedTime' => 'The last modified time.
', 'DescribeFeatureGroupResponse$LastModifiedTime' => 'A timestamp indicating when the feature group was last updated.
', 'DescribeFeatureMetadataResponse$LastModifiedTime' => 'A timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time you
', 'DescribeInferenceRecommendationsJobResponse$LastModifiedTime' => 'A timestamp that shows when the job was last modified.
', 'DescribeNotebookInstanceLifecycleConfigOutput$LastModifiedTime' => 'A timestamp that tells when the lifecycle configuration was last modified.
', 'DescribeNotebookInstanceOutput$LastModifiedTime' => 'A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
', 'DescribeSpaceResponse$LastModifiedTime' => 'The last modified time.
', 'DescribeUserProfileResponse$LastModifiedTime' => 'The last modified time.
', 'DomainDetails$LastModifiedTime' => 'The last modified time.
', 'FeatureGroup$LastModifiedTime' => 'A timestamp indicating the last time you updated the feature group.
', 'FeatureMetadata$LastModifiedTime' => 'A timestamp indicating when the feature was last modified.
', 'InferenceRecommendationsJob$LastModifiedTime' => 'A timestamp that shows when the job was last modified.
', 'ListCompilationJobsRequest$LastModifiedTimeAfter' => 'A filter that returns the model compilation jobs that were modified after a specified time.
', 'ListCompilationJobsRequest$LastModifiedTimeBefore' => 'A filter that returns the model compilation jobs that were modified before a specified time.
', 'ListInferenceRecommendationsJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only jobs that were last modified after the specified time (timestamp).
', 'ListInferenceRecommendationsJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only jobs that were last modified before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$LastModifiedTimeBefore' => 'A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$LastModifiedTimeAfter' => 'A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).
', 'ListNotebookInstancesInput$LastModifiedTimeBefore' => 'A filter that returns only notebook instances that were modified before the specified time (timestamp).
', 'ListNotebookInstancesInput$LastModifiedTimeAfter' => 'A filter that returns only notebook instances that were modified after the specified time (timestamp).
', 'NotebookInstanceLifecycleConfigSummary$LastModifiedTime' => 'A timestamp that tells when the lifecycle configuration was last modified.
', 'NotebookInstanceSummary$LastModifiedTime' => 'A timestamp that shows when the notebook instance was last modified.
', 'SpaceDetails$LastModifiedTime' => 'The last modified time.
', 'UserProfileDetails$LastModifiedTime' => 'The last modified time.
', ], ], 'LastUpdateStatus' => [ 'base' => 'A value that indicates whether the update was successful.
', 'refs' => [ 'DescribeFeatureGroupResponse$LastUpdateStatus' => 'A value indicating whether the update made to the feature group was successful.
', 'FeatureGroup$LastUpdateStatus' => 'A value that indicates whether the feature group was updated successfully.
', ], ], 'LastUpdateStatusValue' => [ 'base' => NULL, 'refs' => [ 'LastUpdateStatus$Status' => 'A value that indicates whether the update was made successful.
', ], ], 'LifecycleConfigArns' => [ 'base' => NULL, 'refs' => [ 'CodeEditorAppSettings$LifecycleConfigArns' => 'The Amazon Resource Name (ARN) of the Code Editor application lifecycle configuration.
', 'JupyterLabAppSettings$LifecycleConfigArns' => 'The Amazon Resource Name (ARN) of the lifecycle configurations attached to the user profile or domain. To remove a lifecycle config, you must set LifecycleConfigArns
to an empty list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec
parameter is also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns
to an empty list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
To remove a Lifecycle Config, you must set LifecycleConfigArns
to an empty list.
A list of properties to add to the action.
', 'CreateContextRequest$Properties' => 'A list of properties to add to the context.
', 'DescribeActionResponse$Properties' => 'A list of the action\'s properties.
', 'DescribeArtifactResponse$Properties' => 'A list of the artifact\'s properties.
', 'DescribeContextResponse$Properties' => 'A list of the context\'s properties.
', 'UpdateActionRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', 'UpdateContextRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', ], ], 'LineageGroupArn' => [ 'base' => NULL, 'refs' => [ 'DescribeActionResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeArtifactResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeContextResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeLineageGroupResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeTrialComponentResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'GetLineageGroupPolicyResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'LineageGroupSummary$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group resource.
', 'TrialComponent$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group resource.
', ], ], 'LineageGroupNameOrArn' => [ 'base' => NULL, 'refs' => [ 'GetLineageGroupPolicyRequest$LineageGroupName' => 'The name or Amazon Resource Name (ARN) of the lineage group.
', ], ], 'LineageGroupSummaries' => [ 'base' => NULL, 'refs' => [ 'ListLineageGroupsResponse$LineageGroupSummaries' => 'A list of lineage groups and their properties.
', ], ], 'LineageGroupSummary' => [ 'base' => 'Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity resources.
', 'refs' => [ 'LineageGroupSummaries$member' => NULL, ], ], 'LineageType' => [ 'base' => NULL, 'refs' => [ 'QueryLineageTypes$member' => NULL, 'Vertex$LineageType' => 'The type of resource of the lineage entity.
', ], ], 'ListActionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListActionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAlgorithmsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListAlgorithmsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListAliasesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAliasesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAppImageConfigsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAppImageConfigsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAppsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAppsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListArtifactsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListArtifactsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAssociationsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAssociationsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAutoMLJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAutoMLJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCandidatesForAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCandidatesForAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListClusterNodesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListClusterNodesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListClustersRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListClustersResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCodeRepositoriesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListCodeRepositoriesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCompilationJobsRequest$SortBy' => 'The field by which to sort results. The default is CreationTime
.
The column to sort by.
', ], ], 'ListDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListDevicesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListDomainsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListDomainsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansSortBy' => [ 'base' => NULL, 'refs' => [ 'ListEdgeDeploymentPlansRequest$SortBy' => 'The column by which to sort the edge deployment plans. Can be one of NAME
, DEVICEFLEETNAME
, CREATIONTIME
, LASTMODIFIEDTIME
.
Use to specify what column to sort by.
', ], ], 'ListEndpointConfigsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointConfigsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListExperimentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListExperimentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListFeatureGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListFeatureGroupsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListFlowDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListFlowDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHumanTaskUisRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHumanTaskUisResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHyperParameterTuningJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHyperParameterTuningJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListImageVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListImageVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListImagesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListImagesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceComponentsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceComponentsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceExperimentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceExperimentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobStepsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobStepsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListInferenceRecommendationsJobsRequest$SortBy' => 'The parameter by which to sort the results.
', ], ], 'ListLabelingJobsForWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListLabelingJobsForWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListLabelingJobsForWorkteamSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamRequest$SortBy' => 'The field to sort results by. The default is CreationTime
.
A list of properties to remove.
', 'UpdateArtifactRequest$PropertiesToRemove' => 'A list of properties to remove.
', 'UpdateContextRequest$PropertiesToRemove' => 'A list of properties to remove.
', ], ], 'ListLineageGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListLineageGroupsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListDeviceFleetsRequest$MaxResults' => 'The maximum number of results to select.
', 'ListDevicesRequest$MaxResults' => 'Maximum number of results to select.
', 'ListEdgeDeploymentPlansRequest$MaxResults' => 'The maximum number of results to select (50 by default).
', 'ListEdgePackagingJobsRequest$MaxResults' => 'Maximum number of results to select.
', 'ListStageDevicesRequest$MaxResults' => 'The maximum number of requests to select.
', ], ], 'ListModelBiasJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelBiasJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardExportJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardExportJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelExplainabilityJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelExplainabilityJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelMetadataResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackageGroupsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackageGroupsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackagesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackagesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelQualityJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelQualityJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertHistoryRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertHistoryResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringExecutionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringExecutionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringSchedulesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringSchedulesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstanceLifecycleConfigsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstanceLifecycleConfigsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstancesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstancesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionStepsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionStepsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineParametersForExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineParametersForExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelinesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelinesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListProcessingJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListProcessingJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListProjectsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListProjectsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListResourceCatalogsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListResourceCatalogsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListSpacesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListSpacesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListStageDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStageDevicesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListStudioLifecycleConfigsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStudioLifecycleConfigsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListSubscribedWorkteamsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListSubscribedWorkteamsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListTagsInput$MaxResults' => 'Maximum number of tags to return.
', ], ], 'ListTagsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsForHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsForHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTransformJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTransformJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialComponentKey256' => [ 'base' => NULL, 'refs' => [ 'UpdateTrialComponentRequest$ParametersToRemove' => 'The hyperparameters to remove from the component.
', 'UpdateTrialComponentRequest$InputArtifactsToRemove' => 'The input artifacts to remove from the component.
', 'UpdateTrialComponentRequest$OutputArtifactsToRemove' => 'The output artifacts to remove from the component.
', ], ], 'ListTrialComponentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialComponentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListUserProfilesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListUserProfilesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListWorkforcesRequest$SortBy' => 'Sort workforces using the workforce name or creation date.
', ], ], 'ListWorkteamsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkteamsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkteamsSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListWorkteamsRequest$SortBy' => 'The field to sort results by. The default is CreationTime
.
The number of Edge Manager agents.
', 'DeviceStats$ConnectedDeviceCount' => 'The number of devices connected with a heartbeat.
', 'DeviceStats$RegisteredDeviceCount' => 'The number of registered devices.
', 'EdgeModelStat$OfflineDeviceCount' => 'The number of devices that have this model version and do not have a heart beat.
', 'EdgeModelStat$ConnectedDeviceCount' => 'The number of devices that have this model version and have a heart beat.
', 'EdgeModelStat$ActiveDeviceCount' => 'The number of devices that have this model version, a heart beat, and are currently running.
', 'EdgeModelStat$SamplingDeviceCount' => 'The number of devices with this model version and are producing sample data.
', ], ], 'MLFramework' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$MLFramework' => 'The machine learning framework vended in the image version.
', 'DescribeImageVersionResponse$MLFramework' => 'The machine learning framework vended in the image version.
', 'UpdateImageVersionRequest$MLFramework' => 'The machine learning framework vended in the image version.
', ], ], 'ManagedInstanceScalingMaxInstanceCount' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantManagedInstanceScaling$MaxInstanceCount' => 'The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic.
', ], ], 'ManagedInstanceScalingMinInstanceCount' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantManagedInstanceScaling$MinInstanceCount' => 'The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic.
', ], ], 'ManagedInstanceScalingStatus' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantManagedInstanceScaling$Status' => 'Indicates whether managed instance scaling is enabled.
', ], ], 'MaxAutoMLJobRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobCompletionCriteria$MaxAutoMLJobRuntimeInSeconds' => 'The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, are not completed.
', ], ], 'MaxCandidates' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobCompletionCriteria$MaxCandidates' => 'The maximum number of times a training job is allowed to run.
For text and image classification, time-series forecasting, as well as text generation (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the maximum value is 750.
', ], ], 'MaxConcurrentInvocationsPerInstance' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceClientConfig$MaxConcurrentInvocationsPerInstance' => 'The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
', ], ], 'MaxConcurrentTaskCount' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$MaxConcurrentTaskCount' => 'Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
', ], ], 'MaxConcurrentTransforms' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$MaxConcurrentTransforms' => 'The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms
is set to 0
or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1
. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms
.
The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.
', 'TransformJob$MaxConcurrentTransforms' => 'The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms
is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms
.
The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
', ], ], 'MaxHumanLabeledObjectCount' => [ 'base' => NULL, 'refs' => [ 'LabelingJobStoppingConditions$MaxHumanLabeledObjectCount' => 'The maximum number of objects that can be labeled by human workers.
', ], ], 'MaxNumberOfTests' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobResourceLimit$MaxNumberOfTests' => 'Defines the maximum number of load tests.
', ], ], 'MaxNumberOfTrainingJobs' => [ 'base' => NULL, 'refs' => [ 'ResourceLimits$MaxNumberOfTrainingJobs' => 'The maximum number of training jobs that a hyperparameter tuning job can launch.
', ], ], 'MaxNumberOfTrainingJobsNotImproving' => [ 'base' => NULL, 'refs' => [ 'BestObjectiveNotImproving$MaxNumberOfTrainingJobsNotImproving' => 'The number of training jobs that have failed to improve model performance by 1% or greater over prior training jobs as evaluated against an objective function.
', ], ], 'MaxParallelExecutionSteps' => [ 'base' => NULL, 'refs' => [ 'ParallelismConfiguration$MaxParallelExecutionSteps' => 'The max number of steps that can be executed in parallel.
', ], ], 'MaxParallelOfTests' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobResourceLimit$MaxParallelOfTests' => 'Defines the maximum number of parallel load tests.
', ], ], 'MaxParallelTrainingJobs' => [ 'base' => NULL, 'refs' => [ 'ResourceLimits$MaxParallelTrainingJobs' => 'The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.
', ], ], 'MaxPayloadInMB' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$MaxPayloadInMB' => 'The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB
must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6
MB.
The value of MaxPayloadInMB
cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms
parameter, the value of (MaxConcurrentTransforms * MaxPayloadInMB)
also cannot exceed 100 MB.
For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0
. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.
The maximum payload size, in MB, used in the transform job.
', 'TransformJob$MaxPayloadInMB' => 'The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB
must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.
The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
', ], ], 'MaxPendingTimeInSeconds' => [ 'base' => 'Maximum job scheduler pending time in seconds.', 'refs' => [ 'StoppingCondition$MaxPendingTimeInSeconds' => 'The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.
', ], ], 'MaxPercentageOfInputDatasetLabeled' => [ 'base' => NULL, 'refs' => [ 'LabelingJobStoppingConditions$MaxPercentageOfInputDatasetLabeled' => 'The maximum number of input data objects that should be labeled.
', ], ], 'MaxResults' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$MaxResults' => 'The maximum number of actions to return in the response. The default value is 10.
', 'ListAlgorithmsInput$MaxResults' => 'The maximum number of algorithms to return in the response.
', 'ListAliasesRequest$MaxResults' => 'The maximum number of aliases to return.
', 'ListAppImageConfigsRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The maximum number of artifacts to return in the response. The default value is 10.
', 'ListAssociationsRequest$MaxResults' => 'The maximum number of associations to return in the response. The default value is 10.
', 'ListClusterNodesRequest$MaxResults' => 'The maximum number of nodes to return in the response.
', 'ListClustersRequest$MaxResults' => 'Set the maximum number of SageMaker HyperPod clusters to list.
', 'ListCodeRepositoriesInput$MaxResults' => 'The maximum number of Git repositories to return in the response.
', 'ListCompilationJobsRequest$MaxResults' => 'The maximum number of model compilation jobs to return in the response.
', 'ListContextsRequest$MaxResults' => 'The maximum number of contexts to return in the response. The default value is 10.
', 'ListDataQualityJobDefinitionsRequest$MaxResults' => 'The maximum number of data quality monitoring job definitions to return in the response.
', 'ListDomainsRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The maximum number of training jobs to return in the response.
', 'ListEndpointsInput$MaxResults' => 'The maximum number of endpoints to return in the response. This value defaults to 10.
', 'ListExperimentsRequest$MaxResults' => 'The maximum number of experiments to return in the response. The default value is 10.
', 'ListFlowDefinitionsRequest$MaxResults' => 'The total number of items to return. If the total number of available items is more than the value specified in MaxResults
, then a NextToken
will be provided in the output that you can use to resume pagination.
The maximum number of hub content versions to list.
', 'ListHubContentsRequest$MaxResults' => 'The maximum amount of hub content to list.
', 'ListHubsRequest$MaxResults' => 'The maximum number of hubs to list.
', 'ListHumanTaskUisRequest$MaxResults' => 'The total number of items to return. If the total number of available items is more than the value specified in MaxResults
, then a NextToken
will be provided in the output that you can use to resume pagination.
The maximum number of tuning jobs to return. The default value is 10.
', 'ListImageVersionsRequest$MaxResults' => 'The maximum number of versions to return in the response. The default value is 10.
', 'ListImagesRequest$MaxResults' => 'The maximum number of images to return in the response. The default value is 10.
', 'ListInferenceComponentsInput$MaxResults' => 'The maximum number of inference components to return in the response. This value defaults to 10.
', 'ListInferenceExperimentsRequest$MaxResults' => 'The maximum number of results to select.
', 'ListInferenceRecommendationsJobStepsRequest$MaxResults' => 'The maximum number of results to return.
', 'ListInferenceRecommendationsJobsRequest$MaxResults' => 'The maximum number of recommendations to return in the response.
', 'ListLabelingJobsForWorkteamRequest$MaxResults' => 'The maximum number of labeling jobs to return in each page of the response.
', 'ListLabelingJobsRequest$MaxResults' => 'The maximum number of labeling jobs to return in each page of the response.
', 'ListLineageGroupsRequest$MaxResults' => 'The maximum number of endpoints to return in the response. This value defaults to 10.
', 'ListModelBiasJobDefinitionsRequest$MaxResults' => 'The maximum number of model bias jobs to return in the response. The default value is 10.
', 'ListModelCardExportJobsRequest$MaxResults' => 'The maximum number of model card export jobs to list.
', 'ListModelCardVersionsRequest$MaxResults' => 'The maximum number of model card versions to list.
', 'ListModelCardsRequest$MaxResults' => 'The maximum number of model cards to list.
', 'ListModelExplainabilityJobDefinitionsRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListModelMetadataRequest$MaxResults' => 'The maximum number of models to return in the response.
', 'ListModelPackageGroupsInput$MaxResults' => 'The maximum number of results to return in the response.
', 'ListModelPackagesInput$MaxResults' => 'The maximum number of model packages to return in the response.
', 'ListModelQualityJobDefinitionsRequest$MaxResults' => 'The maximum number of results to return in a call to ListModelQualityJobDefinitions
.
The maximum number of models to return in the response.
', 'ListMonitoringAlertHistoryRequest$MaxResults' => 'The maximum number of results to display. The default is 100.
', 'ListMonitoringAlertsRequest$MaxResults' => 'The maximum number of results to display. The default is 100.
', 'ListMonitoringExecutionsRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListMonitoringSchedulesRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListNotebookInstanceLifecycleConfigsInput$MaxResults' => 'The maximum number of lifecycle configurations to return in the response.
', 'ListNotebookInstancesInput$MaxResults' => 'The maximum number of notebook instances to return.
', 'ListPipelineExecutionStepsRequest$MaxResults' => 'The maximum number of pipeline execution steps to return in the response.
', 'ListPipelineExecutionsRequest$MaxResults' => 'The maximum number of pipeline executions to return in the response.
', 'ListPipelineParametersForExecutionRequest$MaxResults' => 'The maximum number of parameters to return in the response.
', 'ListPipelinesRequest$MaxResults' => 'The maximum number of pipelines to return in the response.
', 'ListProcessingJobsRequest$MaxResults' => 'The maximum number of processing jobs to return in the response.
', 'ListProjectsInput$MaxResults' => 'The maximum number of projects to return in the response.
', 'ListResourceCatalogsRequest$MaxResults' => ' The maximum number of results returned by ListResourceCatalogs
.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The maximum number of work teams to return in each page of the response.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$MaxResults' => 'The maximum number of training jobs to return. The default value is 10.
', 'ListTrainingJobsRequest$MaxResults' => 'The maximum number of training jobs to return in the response.
', 'ListTransformJobsRequest$MaxResults' => 'The maximum number of transform jobs to return in the response. The default value is 10
.
The maximum number of components to return in the response. The default value is 10.
', 'ListTrialsRequest$MaxResults' => 'The maximum number of trials to return in the response. The default value is 10.
', 'ListUserProfilesRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The maximum number of workforces returned in the response.
', 'ListWorkteamsRequest$MaxResults' => 'The maximum number of work teams to return in each page of the response.
', 'SearchRequest$MaxResults' => 'The maximum number of results to return.
', ], ], 'MaxRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'StoppingCondition$MaxRuntimeInSeconds' => 'The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.
For compilation jobs, if the job does not complete during this time, a TimeOut
error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.
For all other jobs, if the job does not complete during this time, SageMaker ends the job. When RetryStrategy
is specified in the job request, MaxRuntimeInSeconds
specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.
The maximum time that a TrainingJob
can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.
The maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the StoppingCondition used by the CreateHyperParameterTuningJob action.
For job V2s (jobs created by calling CreateAutoMLJobV2
), this field controls the runtime of the job candidate.
For TextGenerationJobConfig problem types, the maximum time defaults to 72 hours (259200 seconds).
', ], ], 'MaxWaitTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'StoppingCondition$MaxWaitTimeInSeconds' => 'The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds
. If the job does not complete during this time, SageMaker ends the job.
When RetryStrategy
is specified in the job request, MaxWaitTimeInSeconds
specifies the maximum time for all of the attempts in total, not each individual attempt.
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in TerminationWaitInSeconds
and WaitIntervalInSeconds
.
The time limit for the total deployment. Exceeding this limit causes a timeout.
', ], ], 'MaximumRetryAttempts' => [ 'base' => NULL, 'refs' => [ 'RetryStrategy$MaximumRetryAttempts' => 'The number of times to retry the job. When the job is retried, it\'s SecondaryStatus
is changed to STARTING
.
The media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.
', ], ], 'MemberDefinition' => [ 'base' => 'Defines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.
', 'refs' => [ 'MemberDefinitions$member' => NULL, ], ], 'MemberDefinitions' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$MemberDefinitions' => 'A list of MemberDefinition
objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition
. Do not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition
objects that make up the member definition must have the same ClientId
and UserPool
values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition
by listing those groups in Groups
.
A list of MemberDefinition
objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition
. You should not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition
objects that make up the member definition must have the same ClientId
and UserPool
values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition
by listing those groups in Groups
. Be aware that user groups that are already in the work team must also be listed in Groups
when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.
A list of MemberDefinition
objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition
.
The minimum MB of memory to allocate to run a model that you assign to an inference component.
', 'InferenceComponentComputeResourceRequirements$MaxMemoryRequiredInMb' => 'The maximum MB of memory to allocate to run a model that you assign to an inference component.
', ], ], 'MetadataProperties' => [ 'base' => 'Metadata properties of the tracking entity, trial, or trial component.
', 'refs' => [ 'CreateActionRequest$MetadataProperties' => NULL, 'CreateArtifactRequest$MetadataProperties' => NULL, 'CreateModelPackageInput$MetadataProperties' => NULL, 'CreateTrialComponentRequest$MetadataProperties' => NULL, 'CreateTrialRequest$MetadataProperties' => NULL, 'DescribeActionResponse$MetadataProperties' => NULL, 'DescribeArtifactResponse$MetadataProperties' => NULL, 'DescribeModelPackageOutput$MetadataProperties' => NULL, 'DescribeTrialComponentResponse$MetadataProperties' => NULL, 'DescribeTrialResponse$MetadataProperties' => NULL, 'ModelPackage$MetadataProperties' => 'Metadata properties of the tracking entity, trial, or trial component.
', 'Trial$MetadataProperties' => NULL, 'TrialComponent$MetadataProperties' => NULL, ], ], 'MetadataPropertyValue' => [ 'base' => NULL, 'refs' => [ 'MetadataProperties$CommitId' => 'The commit ID.
', 'MetadataProperties$Repository' => 'The repository.
', 'MetadataProperties$GeneratedBy' => 'The entity this entity was generated by.
', 'MetadataProperties$ProjectId' => 'The project ID.
', ], ], 'MetricData' => [ 'base' => 'The name, value, and date and time of a metric that was emitted to Amazon CloudWatch.
', 'refs' => [ 'FinalMetricDataList$member' => NULL, ], ], 'MetricDataList' => [ 'base' => NULL, 'refs' => [ 'CandidateProperties$CandidateMetrics' => 'Information about the candidate metrics for an AutoML job.
', ], ], 'MetricDatum' => [ 'base' => 'Information about the metric for a candidate produced by an AutoML job.
', 'refs' => [ 'MetricDataList$member' => NULL, ], ], 'MetricDefinition' => [ 'base' => 'Specifies a metric that the training algorithm writes to stderr
or stdout
. You can view these logs to understand how your training job performs and check for any errors encountered during training. SageMaker hyperparameter tuning captures all defined metrics. Specify one of the defined metrics to use as an objective metric using the TuningObjective parameter in the HyperParameterTrainingJobDefinition
API to evaluate job performance during hyperparameter tuning.
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
', 'HyperParameterAlgorithmSpecification$MetricDefinitions' => 'An array of MetricDefinition objects that specify the metrics that the algorithm emits.
', 'TrainingSpecification$MetricDefinitions' => 'A list of MetricDefinition
objects, which are used for parsing metrics generated by the algorithm.
The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the metrics for XGBoost as an example. You can also use a custom algorithm for training and define your own metrics. For more information, see Define metrics and environment variables.
', 'HyperParameterTuningJobObjective$MetricName' => 'The name of the metric to use for the objective metric.
', 'MetricData$MetricName' => 'The name of the metric.
', 'MetricDefinition$Name' => 'The name of the metric.
', 'TrialComponentMetricSummary$MetricName' => 'The name of the metric.
', ], ], 'MetricRegex' => [ 'base' => NULL, 'refs' => [ 'MetricDefinition$Regex' => 'A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see Defining metrics and environment variables.
', ], ], 'MetricSetSource' => [ 'base' => NULL, 'refs' => [ 'MetricDatum$Set' => 'The dataset split from which the AutoML job produced the metric.
', ], ], 'MetricSpecification' => [ 'base' => 'An object containing information about a metric.
', 'refs' => [ 'TargetTrackingScalingPolicyConfiguration$MetricSpecification' => 'An object containing information about a metric.
', ], ], 'MetricValue' => [ 'base' => NULL, 'refs' => [ 'FinalAutoMLJobObjectiveMetric$Value' => 'The value of the metric with the best result.
', 'FinalHyperParameterTuningJobObjectiveMetric$Value' => 'The value of the objective metric.
', ], ], 'MetricsSource' => [ 'base' => 'Details about the metrics source.
', 'refs' => [ 'Bias$Report' => 'The bias report for a model
', 'Bias$PreTrainingReport' => 'The pre-training bias report for a model.
', 'Bias$PostTrainingReport' => 'The post-training bias report for a model.
', 'DriftCheckBias$PreTrainingConstraints' => 'The pre-training constraints.
', 'DriftCheckBias$PostTrainingConstraints' => 'The post-training constraints.
', 'DriftCheckExplainability$Constraints' => 'The drift check explainability constraints.
', 'DriftCheckModelDataQuality$Statistics' => 'The drift check model data quality statistics.
', 'DriftCheckModelDataQuality$Constraints' => 'The drift check model data quality constraints.
', 'DriftCheckModelQuality$Statistics' => 'The drift check model quality statistics.
', 'DriftCheckModelQuality$Constraints' => 'The drift check model quality constraints.
', 'Explainability$Report' => 'The explainability report for a model.
', 'ModelDataQuality$Statistics' => 'Data quality statistics for a model.
', 'ModelDataQuality$Constraints' => 'Data quality constraints for a model.
', 'ModelQuality$Statistics' => 'Model quality statistics.
', 'ModelQuality$Constraints' => 'Model quality constraints.
', ], ], 'MinimumInstanceMetadataServiceVersion' => [ 'base' => NULL, 'refs' => [ 'InstanceMetadataServiceConfiguration$MinimumInstanceMetadataServiceVersion' => 'Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance
, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance
, there is no default.
The properties of a model as returned by the Search API.
', 'refs' => [ 'ModelDashboardModel$Model' => 'A model displayed in the Model Dashboard.
', ], ], 'ModelAccessConfig' => [ 'base' => 'The access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig
. For more information, see End-user license agreements.
Specifies the access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig
. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The approval status of the model.
', 'CreateModelPackageInput$ModelApprovalStatus' => 'Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to Approved
to deploy the model.
The approval status of the model package.
', 'ListModelPackagesInput$ModelApprovalStatus' => 'A filter that returns only the model packages with the specified approval status.
', 'ModelPackage$ModelApprovalStatus' => 'The approval status of the model. This can be one of the following values.
APPROVED
- The model is approved
REJECTED
- The model is rejected.
PENDING_MANUAL_APPROVAL
- The model is waiting for manual approval.
The approval status of the model. This can be one of the following values.
APPROVED
- The model is approved
REJECTED
- The model is rejected.
PENDING_MANUAL_APPROVAL
- The model is waiting for manual approval.
The approval status of the model.
', ], ], 'ModelArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelOutput$ModelArn' => 'The ARN of the model created in SageMaker.
', 'DescribeModelOutput$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', 'LabelingJobAlgorithmsConfig$InitialActiveLearningModelArn' => 'At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
', 'LabelingJobOutput$FinalActiveLearningModelArn' => 'The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.
', 'Model$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', 'ModelSummary$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', ], ], 'ModelArtifacts' => [ 'base' => 'Provides information about the location that is configured for storing model artifacts.
Model artifacts are the output that results from training a model, and typically consist of trained parameters, a model definition that describes how to compute inferences, and other metadata.
', 'refs' => [ 'DescribeCompilationJobResponse$ModelArtifacts' => 'Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.
', 'DescribeTrainingJobResponse$ModelArtifacts' => 'Information about the Amazon S3 location that is configured for storing model artifacts.
', 'TrainingJob$ModelArtifacts' => 'Information about the Amazon S3 location that is configured for storing model artifacts.
', ], ], 'ModelBiasAppSpecification' => [ 'base' => 'Docker container image configuration object for the model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasAppSpecification' => 'Configures the model bias job to run a specified Docker container image.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasAppSpecification' => 'Configures the model bias job to run a specified Docker container image.
', ], ], 'ModelBiasBaselineConfig' => [ 'base' => 'The configuration for a baseline model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasBaselineConfig' => 'The baseline configuration for a model bias job.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasBaselineConfig' => 'The baseline configuration for a model bias job.
', ], ], 'ModelBiasJobInput' => [ 'base' => 'Inputs for the model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasJobInput' => 'Inputs for the model bias job.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasJobInput' => 'Inputs for the model bias job.
', ], ], 'ModelCacheSetting' => [ 'base' => NULL, 'refs' => [ 'MultiModelConfig$ModelCacheSetting' => 'Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to Disabled
.
An Amazon SageMaker Model Card.
', 'refs' => [ 'SearchRecord$ModelCard' => 'An Amazon SageMaker Model Card that documents details about a machine learning model.
', ], ], 'ModelCardArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the successfully created model card.
', 'DescribeModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCard$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCardSummary$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCardVersionSummary$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelDashboardModelCard$ModelCardArn' => 'The Amazon Resource Name (ARN) for a model card.
', 'UpdateModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the updated model card.
', ], ], 'ModelCardContent' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardRequest$Content' => 'The content of the model card. Content must be in model card JSON schema and provided as a string.
', 'DescribeModelCardResponse$Content' => 'The content of the model card.
', 'ModelCard$Content' => 'The content of the model card. Content uses the model card JSON schema and provided as a string.
', 'UpdateModelCardRequest$Content' => 'The updated model card content. Content must be in model card JSON schema and provided as a string.
When updating model card content, be sure to include the full content and not just updated content.
', ], ], 'ModelCardExportArtifacts' => [ 'base' => 'The artifacts of the model card export job.
', 'refs' => [ 'DescribeModelCardExportJobResponse$ExportArtifacts' => 'The exported model card artifacts.
', ], ], 'ModelCardExportJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobResponse$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', 'DescribeModelCardExportJobRequest$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job to describe.
', 'DescribeModelCardExportJobResponse$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', 'ModelCardExportJobSummary$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', ], ], 'ModelCardExportJobSortBy' => [ 'base' => 'Attribute by which to sort returned export jobs.', 'refs' => [ 'ListModelCardExportJobsRequest$SortBy' => 'Sort model card export jobs by either name or creation time. Sorts by creation time by default.
', ], ], 'ModelCardExportJobSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListModelCardExportJobsRequest$SortOrder' => 'Sort model card export jobs by ascending or descending order.
', ], ], 'ModelCardExportJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeModelCardExportJobResponse$Status' => 'The completion status of the model card export job.
InProgress
: The model card export job is in progress.
Completed
: The model card export job is complete.
Failed
: The model card export job failed. To see the reason for the failure, see the FailureReason
field in the response to a DescribeModelCardExportJob
call.
Only list model card export jobs with the specified status.
', 'ModelCardExportJobSummary$Status' => 'The completion status of the model card export job.
', ], ], 'ModelCardExportJobSummary' => [ 'base' => 'The summary of the Amazon SageMaker Model Card export job.
', 'refs' => [ 'ModelCardExportJobSummaryList$member' => NULL, ], ], 'ModelCardExportJobSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardExportJobsResponse$ModelCardExportJobSummaries' => 'The summaries of the listed model card export jobs.
', ], ], 'ModelCardExportOutputConfig' => [ 'base' => 'Configure the export output details for an Amazon SageMaker Model Card.
', 'refs' => [ 'CreateModelCardExportJobRequest$OutputConfig' => 'The model card output configuration that specifies the Amazon S3 path for exporting.
', 'DescribeModelCardExportJobResponse$OutputConfig' => 'The export output details for the model card.
', ], ], 'ModelCardNameOrArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to export.
', 'DescribeModelCardRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to describe.
', 'ListModelCardVersionsRequest$ModelCardName' => 'List model card versions for the model card with the specified name or Amazon Resource Name (ARN).
', 'UpdateModelCardRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to update.
', ], ], 'ModelCardProcessingStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeModelCardResponse$ModelCardProcessingStatus' => 'The processing status of model card deletion. The ModelCardProcessingStatus
updates throughout the different deletion steps.
DeletePending
: Model card deletion request received.
DeleteInProgress
: Model card deletion is in progress.
ContentDeleted
: Deleted model card content.
ExportJobsDeleted
: Deleted all export jobs associated with the model card.
DeleteCompleted
: Successfully deleted the model card.
DeleteFailed
: The model card failed to delete.
Configure the security settings to protect model card data.
', 'refs' => [ 'CreateModelCardRequest$SecurityConfig' => 'An optional Key Management Service key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with highly sensitive data.
', 'DescribeModelCardResponse$SecurityConfig' => 'The security configuration used to protect model card content.
', 'ModelCard$SecurityConfig' => 'The security configuration used to protect model card data.
', 'ModelDashboardModelCard$SecurityConfig' => 'The KMS Key ID (KMSKeyId
) for encryption of model card information.
Sort model cards by either name or creation time. Sorts by creation time by default.
', ], ], 'ModelCardSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsRequest$SortOrder' => 'Sort model card versions by ascending or descending order.
', 'ListModelCardsRequest$SortOrder' => 'Sort model cards by ascending or descending order.
', ], ], 'ModelCardStatus' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardRequest$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
Only list model card versions with the specified approval status.
', 'ListModelCardsRequest$ModelCardStatus' => 'Only list model cards with the specified approval status.
', 'ModelCard$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The model card status.
', 'UpdateModelCardRequest$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
A summary of the model card.
', 'refs' => [ 'ModelCardSummaryList$member' => NULL, ], ], 'ModelCardSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardsResponse$ModelCardSummaries' => 'The summaries of the listed model cards.
', ], ], 'ModelCardVersionSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsRequest$SortBy' => 'Sort listed model card versions by version. Sorts by version by default.
', ], ], 'ModelCardVersionSummary' => [ 'base' => 'A summary of a specific version of the model card.
', 'refs' => [ 'ModelCardVersionSummaryList$member' => NULL, ], ], 'ModelCardVersionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsResponse$ModelCardVersionSummaryList' => 'The summaries of the listed versions of the model card.
', ], ], 'ModelClientConfig' => [ 'base' => 'Configures the timeout and maximum number of retries for processing a transform job invocation.
', 'refs' => [ 'CreateTransformJobRequest$ModelClientConfig' => 'Configures the timeout and maximum number of retries for processing a transform job invocation.
', 'DescribeTransformJobResponse$ModelClientConfig' => 'The timeout and maximum number of retries for processing a transform job invocation.
', 'TransformJob$ModelClientConfig' => NULL, ], ], 'ModelCompressionType' => [ 'base' => NULL, 'refs' => [ 'S3ModelDataSource$CompressionType' => 'Specifies how the ML model data is prepared.
If you choose Gzip
and choose S3Object
as the value of S3DataType
, S3Uri
identifies an object that is a gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during model deployment.
If you choose None
and chooose S3Object
as the value of S3DataType
, S3Uri
identifies an object that represents an uncompressed ML model to deploy.
If you choose None and choose S3Prefix
as the value of S3DataType
, S3Uri
identifies a key name prefix, under which all objects represents the uncompressed ML model to deploy.
If you choose None, then SageMaker will follow rules below when creating model data files under /opt/ml/model directory for use by your inference code:
If you choose S3Object
as the value of S3DataType
, then SageMaker will split the key of the S3 object referenced by S3Uri
by slash (/), and use the last part as the filename of the file holding the content of the S3 object.
If you choose S3Prefix
as the value of S3DataType
, then for each S3 object under the key name pefix referenced by S3Uri
, SageMaker will trim its key by the prefix, and use the remainder as the path (relative to /opt/ml/model
) of the file holding the content of the S3 object. SageMaker will split the remainder by slash (/), using intermediate parts as directory names and the last part as filename of the file holding the content of the S3 object.
Do not use any of the following as file names or directory names:
An empty or blank string
A string which contains null bytes
A string longer than 255 bytes
A single dot (.
)
A double dot (..
)
Ambiguous file names will result in model deployment failure. For example, if your uncompressed ML model consists of two S3 objects s3://mybucket/model/weights
and s3://mybucket/model/weights/part1
and you specify s3://mybucket/model/
as the value of S3Uri
and S3Prefix
as the value of S3DataType
, then it will result in name clash between /opt/ml/model/weights
(a regular file) and /opt/ml/model/weights/
(a directory).
Do not organize the model artifacts in S3 console using folders. When you create a folder in S3 console, S3 creates a 0-byte object with a key set to the folder name you provide. They key of the 0-byte object ends with a slash (/) which violates SageMaker restrictions on model artifact file names, leading to model deployment failure.
Defines the model configuration. Includes the specification name and environment parameters.
', 'refs' => [ 'InferenceRecommendation$ModelConfiguration' => 'Defines the model configuration.
', 'RecommendationJobInferenceBenchmark$ModelConfiguration' => NULL, ], ], 'ModelDashboardEndpoint' => [ 'base' => 'An endpoint that hosts a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardEndpoints$member' => NULL, ], ], 'ModelDashboardEndpoints' => [ 'base' => NULL, 'refs' => [ 'ModelDashboardModel$Endpoints' => 'The endpoints that host a model.
', ], ], 'ModelDashboardIndicatorAction' => [ 'base' => 'An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into InAlert
status.
An alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert
status.
A model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'SearchRecord$Model' => NULL, ], ], 'ModelDashboardModelCard' => [ 'base' => 'The model card for a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardModel$ModelCard' => 'The model card for a model.
', ], ], 'ModelDashboardMonitoringSchedule' => [ 'base' => 'A monitoring schedule for a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardMonitoringSchedules$member' => NULL, ], ], 'ModelDashboardMonitoringSchedules' => [ 'base' => NULL, 'refs' => [ 'ModelDashboardModel$MonitoringSchedules' => 'The monitoring schedules for a model.
', ], ], 'ModelDataQuality' => [ 'base' => 'Data quality constraints and statistics for a model.
', 'refs' => [ 'ModelMetrics$ModelDataQuality' => 'Metrics that measure the quality of the input data for a model.
', ], ], 'ModelDataSource' => [ 'base' => 'Specifies the location of ML model data to deploy. If specified, you must specify one and only one of the available data sources.
', 'refs' => [ 'ContainerDefinition$ModelDataSource' => 'Specifies the location of ML model data to deploy.
Currently you cannot use ModelDataSource
in conjunction with SageMaker batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker Marketplace.
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'refs' => [ 'CreateAutoMLJobRequest$ModelDeployConfig' => 'Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'CreateAutoMLJobV2Request$ModelDeployConfig' => 'Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'DescribeAutoMLJobResponse$ModelDeployConfig' => 'Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
', 'DescribeAutoMLJobV2Response$ModelDeployConfig' => 'Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
', ], ], 'ModelDeployResult' => [ 'base' => 'Provides information about the endpoint of the model deployment.
', 'refs' => [ 'DescribeAutoMLJobResponse$ModelDeployResult' => 'Provides information about endpoint for the model deployment.
', 'DescribeAutoMLJobV2Response$ModelDeployResult' => 'Provides information about endpoint for the model deployment.
', ], ], 'ModelDigests' => [ 'base' => 'Provides information to verify the integrity of stored model artifacts.
', 'refs' => [ 'DescribeCompilationJobResponse$ModelDigests' => 'Provides a BLAKE2 hash value that identifies the compiled model artifacts in Amazon S3.
', ], ], 'ModelExplainabilityAppSpecification' => [ 'base' => 'Docker container image configuration object for the model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityAppSpecification' => 'Configures the model explainability job to run a specified Docker container image.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityAppSpecification' => 'Configures the model explainability job to run a specified Docker container image.
', ], ], 'ModelExplainabilityBaselineConfig' => [ 'base' => 'The configuration for a baseline model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityBaselineConfig' => 'The baseline configuration for a model explainability job.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityBaselineConfig' => 'The baseline configuration for a model explainability job.
', ], ], 'ModelExplainabilityJobInput' => [ 'base' => 'Inputs for the model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityJobInput' => 'Inputs for the model explainability job.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityJobInput' => 'Inputs for the model explainability job.
', ], ], 'ModelInfrastructureConfig' => [ 'base' => 'The configuration for the infrastructure that the model will be deployed to.
', 'refs' => [ 'ModelVariantConfig$InfrastructureConfig' => 'The configuration for the infrastructure that the model will be deployed to.
', 'ModelVariantConfigSummary$InfrastructureConfig' => 'The configuration of the infrastructure that the model has been deployed to.
', ], ], 'ModelInfrastructureType' => [ 'base' => NULL, 'refs' => [ 'ModelInfrastructureConfig$InfrastructureType' => 'The inference option to which to deploy your model. Possible values are the following:
RealTime
: Deploy to real-time inference.
Input object for the model.
', 'refs' => [ 'ModelPackageContainerDefinition$ModelInput' => 'A structure with Model Input details.
', ], ], 'ModelInsightsLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$ModelInsights' => 'The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
', ], ], 'ModelLatencyThreshold' => [ 'base' => 'The model latency threshold.
', 'refs' => [ 'ModelLatencyThresholds$member' => NULL, ], ], 'ModelLatencyThresholds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobStoppingConditions$ModelLatencyThresholds' => 'The interval of time taken by a model to respond as viewed from SageMaker. The interval includes the local communication time taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
', ], ], 'ModelMetadataFilter' => [ 'base' => 'Part of the search expression. You can specify the name and value (domain, task, framework, framework version, task, and model).
', 'refs' => [ 'ModelMetadataFilters$member' => NULL, ], ], 'ModelMetadataFilterType' => [ 'base' => NULL, 'refs' => [ 'ModelMetadataFilter$Name' => 'The name of the of the model to filter by.
', ], ], 'ModelMetadataFilters' => [ 'base' => NULL, 'refs' => [ 'ModelMetadataSearchExpression$Filters' => 'A list of filter objects.
', ], ], 'ModelMetadataSearchExpression' => [ 'base' => 'One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results
', 'refs' => [ 'ListModelMetadataRequest$SearchExpression' => 'One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results. Specify the Framework, FrameworkVersion, Domain or Task to filter supported. Filter names and values are case-sensitive.
', ], ], 'ModelMetadataSummaries' => [ 'base' => NULL, 'refs' => [ 'ListModelMetadataResponse$ModelMetadataSummaries' => 'A structure that holds model metadata.
', ], ], 'ModelMetadataSummary' => [ 'base' => 'A summary of the model metadata.
', 'refs' => [ 'ModelMetadataSummaries$member' => NULL, ], ], 'ModelMetrics' => [ 'base' => 'Contains metrics captured from a model.
', 'refs' => [ 'CreateModelPackageInput$ModelMetrics' => 'A structure that contains model metrics reports.
', 'DescribeModelPackageOutput$ModelMetrics' => 'Metrics for the model.
', 'ModelPackage$ModelMetrics' => 'Metrics for the model.
', ], ], 'ModelName' => [ 'base' => NULL, 'refs' => [ 'CreateModelInput$ModelName' => 'The name of the new model.
', 'CreateTransformJobRequest$ModelName' => 'The name of the model that you want to use for the transform job. ModelName
must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.
The name of the model to delete.
', 'DescribeModelInput$ModelName' => 'The name of the model.
', 'DescribeModelOutput$ModelName' => 'Name of the SageMaker model.
', 'DescribeTransformJobResponse$ModelName' => 'The name of the model used in the transform job.
', 'InferenceComponentSpecification$ModelName' => 'The name of an existing SageMaker model object in your account that you want to deploy with the inference component.
', 'InferenceComponentSpecificationSummary$ModelName' => 'The name of the SageMaker model object that is deployed with the inference component.
', 'InferenceRecommendationsJob$ModelName' => 'The name of the created model.
', 'ListInferenceRecommendationsJobsRequest$ModelNameEquals' => 'A filter that returns only jobs that were created for this model.
', 'Model$ModelName' => 'The name of the model.
', 'ModelSummary$ModelName' => 'The name of the model that you want a summary for.
', 'ModelVariantConfig$ModelName' => 'The name of the Amazon SageMaker Model entity.
', 'ModelVariantConfigSummary$ModelName' => 'The name of the Amazon SageMaker Model entity.
', 'ProductionVariant$ModelName' => 'The name of the model that you want to host. This is the name that you specified when creating the model.
', 'RecommendationJobInputConfig$ModelName' => 'The name of the created model.
', 'TransformJob$ModelName' => 'The name of the model associated with the transform job.
', ], ], 'ModelNameContains' => [ 'base' => NULL, 'refs' => [ 'ListModelsInput$NameContains' => 'A string in the model name. This filter returns only models whose name contains the specified string.
', ], ], 'ModelPackage' => [ 'base' => 'A versioned model that can be deployed for SageMaker inference.
', 'refs' => [ 'SearchRecord$ModelPackage' => NULL, ], ], 'ModelPackageArn' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageErrorMap$key' => NULL, 'BatchDescribeModelPackageSummary$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'CreateCompilationJobRequest$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn
or an InputConfig
object in the request syntax. The presence of both objects in the CreateCompilationJob
request will return an exception.
The Amazon Resource Name (ARN) of the new model package.
', 'DescribeCompilationJobResponse$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of the versioned model package that was provided to SageMaker Neo when you initiated a compilation job.
', 'DescribeModelPackageOutput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'InferenceRecommendationsJob$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package.
', 'ListInferenceRecommendationsJobsRequest$ModelPackageVersionArnEquals' => 'A filter that returns only jobs that were created for this versioned model package.
', 'ModelPackage$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'ModelPackageArnList$member' => NULL, 'ModelPackageSummaries$key' => NULL, 'ModelPackageSummary$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'RecommendationJobInputConfig$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package.
', 'UpdateModelPackageInput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'UpdateModelPackageOutput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model.
', ], ], 'ModelPackageArnList' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageInput$ModelPackageArnList' => 'The list of Amazon Resource Name (ARN) of the model package groups.
', ], ], 'ModelPackageContainerDefinition' => [ 'base' => 'Describes the Docker container for the model package.
', 'refs' => [ 'ModelPackageContainerDefinitionList$member' => NULL, ], ], 'ModelPackageContainerDefinitionList' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Containers' => 'The Amazon ECR registry path of the Docker image that contains the inference code.
', 'InferenceSpecification$Containers' => 'The Amazon ECR registry path of the Docker image that contains the inference code.
', ], ], 'ModelPackageFrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'ModelPackageContainerDefinition$FrameworkVersion' => 'The framework version of the Model Package Container Image.
', ], ], 'ModelPackageGroup' => [ 'base' => 'A group of versioned models in the model registry.
', 'refs' => [ 'SearchRecord$ModelPackageGroup' => NULL, ], ], 'ModelPackageGroupArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageGroupOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'ModelPackageGroup$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'PutModelPackageGroupPolicyOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model package group.
', ], ], 'ModelPackageGroupSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelPackageGroupsInput$SortBy' => 'The field to sort results by. The default is CreationTime
.
The status of the model group.
', 'ModelPackageGroup$ModelPackageGroupStatus' => 'The status of the model group. This can be one of the following values.
PENDING
- The model group is pending being created.
IN_PROGRESS
- The model group is in the process of being created.
COMPLETED
- The model group was successfully created.
FAILED
- The model group failed.
DELETING
- The model group is in the process of being deleted.
DELETE_FAILED
- SageMaker failed to delete the model group.
The status of the model group.
', ], ], 'ModelPackageGroupSummary' => [ 'base' => 'Summary information about a model group.
', 'refs' => [ 'ModelPackageGroupSummaryList$member' => NULL, ], ], 'ModelPackageGroupSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelPackageGroupsOutput$ModelPackageGroupSummaryList' => 'A list of summaries of the model groups in your Amazon Web Services account.
', ], ], 'ModelPackageSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelPackagesInput$SortBy' => 'The parameter by which to sort the results. The default is CreationTime
.
The status of the mortgage package.
', 'DescribeModelPackageOutput$ModelPackageStatus' => 'The current status of the model package.
', 'ModelPackage$ModelPackageStatus' => 'The status of the model package. This can be one of the following values.
PENDING
- The model package is pending being created.
IN_PROGRESS
- The model package is in the process of being created.
COMPLETED
- The model package was successfully created.
FAILED
- The model package failed.
DELETING
- The model package is in the process of being deleted.
The overall status of the model package.
', ], ], 'ModelPackageStatusDetails' => [ 'base' => 'Specifies the validation and image scan statuses of the model package.
', 'refs' => [ 'DescribeModelPackageOutput$ModelPackageStatusDetails' => 'Details about the current status of the model package.
', 'ModelPackage$ModelPackageStatusDetails' => 'Specifies the validation and image scan statuses of the model package.
', ], ], 'ModelPackageStatusItem' => [ 'base' => 'Represents the overall status of a model package.
', 'refs' => [ 'ModelPackageStatusItemList$member' => NULL, ], ], 'ModelPackageStatusItemList' => [ 'base' => NULL, 'refs' => [ 'ModelPackageStatusDetails$ValidationStatuses' => 'The validation status of the model package.
', 'ModelPackageStatusDetails$ImageScanStatuses' => 'The status of the scan of the Docker image container for the model package.
', ], ], 'ModelPackageSummaries' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageOutput$ModelPackageSummaries' => 'The summaries for the model package versions
', ], ], 'ModelPackageSummary' => [ 'base' => 'Provides summary information about a model package.
', 'refs' => [ 'ModelPackageSummaryList$member' => NULL, ], ], 'ModelPackageSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelPackagesOutput$ModelPackageSummaryList' => 'An array of ModelPackageSummary
objects, each of which lists a model package.
A filter that returns only the model packages of the specified type. This can be one of the following values.
UNVERSIONED
- List only unversioined models. This is the default value if no ModelPackageType
is specified.
VERSIONED
- List only versioned models.
BOTH
- List both versioned and unversioned models.
Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
', 'refs' => [ 'ModelPackageValidationProfiles$member' => NULL, ], ], 'ModelPackageValidationProfiles' => [ 'base' => NULL, 'refs' => [ 'ModelPackageValidationSpecification$ValidationProfiles' => 'An array of ModelPackageValidationProfile
objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
Specifies batch transform jobs that SageMaker runs to validate your model package.
', 'refs' => [ 'CreateModelPackageInput$ValidationSpecification' => 'Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
', 'DescribeModelPackageOutput$ValidationSpecification' => 'Configurations for one or more transform jobs that SageMaker runs to test the model package.
', 'ModelPackage$ValidationSpecification' => 'Specifies batch transform jobs that SageMaker runs to validate your model package.
', ], ], 'ModelPackageVersion' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageSummary$ModelPackageVersion' => 'The version number of a versioned model.
', 'DescribeModelPackageOutput$ModelPackageVersion' => 'The version of the model package.
', 'ModelPackage$ModelPackageVersion' => 'The version number of a versioned model.
', 'ModelPackageSummary$ModelPackageVersion' => 'If the model package is a versioned model, the version of the model.
', ], ], 'ModelQuality' => [ 'base' => 'Model quality statistics and constraints.
', 'refs' => [ 'ModelMetrics$ModelQuality' => 'Metrics that measure the quality of a model.
', ], ], 'ModelQualityAppSpecification' => [ 'base' => 'Container image configuration object for the monitoring job.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityAppSpecification' => 'The container that runs the monitoring job.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityAppSpecification' => 'Configures the model quality job to run a specified Docker container image.
', ], ], 'ModelQualityBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityBaselineConfig' => 'Specifies the constraints and baselines for the monitoring job.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityBaselineConfig' => 'The baseline configuration for a model quality job.
', ], ], 'ModelQualityJobInput' => [ 'base' => 'The input for the model quality monitoring job. Currently endpoints are supported for input for model quality monitoring jobs.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityJobInput' => 'A list of the inputs that are monitored. Currently endpoints are supported.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityJobInput' => 'Inputs for the model quality job.
', ], ], 'ModelRegisterSettings' => [ 'base' => 'The model registry settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$ModelRegisterSettings' => 'The model registry settings for the SageMaker Canvas application.
', ], ], 'ModelSetupTime' => [ 'base' => NULL, 'refs' => [ 'RecommendationMetrics$ModelSetupTime' => 'The time it takes to launch new compute resources for a serverless endpoint. The time can vary depending on the model size, how long it takes to download the model, and the start-up time of the container.
NaN
indicates that the value is not available.
Sorts the list of results. The default is CreationTime
.
Metadata for Model steps.
', 'refs' => [ 'PipelineExecutionStepMetadata$Model' => 'The Amazon Resource Name (ARN) of the model that was created by this step execution.
', ], ], 'ModelSummary' => [ 'base' => 'Provides summary information about a model.
', 'refs' => [ 'ModelSummaryList$member' => NULL, ], ], 'ModelSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelsOutput$Models' => 'An array of ModelSummary
objects, each of which lists a model.
Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:
Promote
- Promote the shadow variant to a production variant
Remove
- Delete the variant
Retain
- Keep the variant as it is
Contains information about the deployment options of a model.
', 'refs' => [ 'ModelVariantConfigList$member' => NULL, ], ], 'ModelVariantConfigList' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$ModelVariants' => ' An array of ModelVariantConfig
objects. There is one for each variant in the inference experiment. Each ModelVariantConfig
object in the array describes the infrastructure configuration for the corresponding variant.
An array of ModelVariantConfig
objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig
describes the infrastructure configuration for deploying the corresponding variant.
An array of ModelVariantConfig
objects. There is one for each variant, whose infrastructure configuration you want to update.
Summary of the deployment configuration of a model.
', 'refs' => [ 'ModelVariantConfigSummaryList$member' => NULL, ], ], 'ModelVariantConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceExperimentResponse$ModelVariants' => ' An array of ModelVariantConfigSummary
objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary
object in the array describes the infrastructure configuration for deploying the corresponding variant.
The name of the variant.
', 'ModelVariantConfigSummary$VariantName' => 'The name of the variant.
', 'ShadowModeConfig$SourceModelVariantName' => 'The name of the production variant, which takes all the inference requests.
', 'ShadowModelVariantConfig$ShadowModelVariantName' => 'The name of the shadow variant.
', ], ], 'ModelVariantStatus' => [ 'base' => NULL, 'refs' => [ 'ModelVariantConfigSummary$Status' => 'The status of deployment for the model variant on the hosted inference endpoint.
Creating
- Amazon SageMaker is preparing the model variant on the hosted inference endpoint.
InService
- The model variant is running on the hosted inference endpoint.
Updating
- Amazon SageMaker is updating the model variant on the hosted inference endpoint.
Deleting
- Amazon SageMaker is deleting the model variant on the hosted inference endpoint.
Deleted
- The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.
A list of alert actions taken in response to an alert going into InAlert
status.
A list of alert actions taken in response to an alert going into InAlert
status.
An alert history for a model monitoring schedule.
', ], ], 'MonitoringAlertHistorySortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$SortBy' => 'The field used to sort results. The default is CreationTime
.
Provides summary information of an alert\'s history.
', 'refs' => [ 'MonitoringAlertHistoryList$member' => NULL, ], ], 'MonitoringAlertName' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$MonitoringAlertName' => 'The name of a monitoring alert.
', 'MonitoringAlertHistorySummary$MonitoringAlertName' => 'The name of a monitoring alert.
', 'MonitoringAlertSummary$MonitoringAlertName' => 'The name of a monitoring alert.
', 'UpdateMonitoringAlertRequest$MonitoringAlertName' => 'The name of a monitoring alert.
', 'UpdateMonitoringAlertResponse$MonitoringAlertName' => 'The name of a monitoring alert.
', ], ], 'MonitoringAlertStatus' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$StatusEquals' => 'A filter that retrieves only alerts with a specific status.
', 'MonitoringAlertHistorySummary$AlertStatus' => 'The current alert status of an alert.
', 'MonitoringAlertSummary$AlertStatus' => 'The current status of an alert.
', ], ], 'MonitoringAlertSummary' => [ 'base' => 'Provides summary information about a monitor alert.
', 'refs' => [ 'MonitoringAlertSummaryList$member' => NULL, ], ], 'MonitoringAlertSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertsResponse$MonitoringAlertSummaries' => 'A JSON array where each element is a summary for a monitoring alert.
', 'ModelDashboardMonitoringSchedule$MonitoringAlertSummaries' => 'A JSON array where each element is a summary for a monitoring alert.
', ], ], 'MonitoringAppSpecification' => [ 'base' => 'Container image configuration object for the monitoring job.
', 'refs' => [ 'MonitoringJobDefinition$MonitoringAppSpecification' => 'Configures the monitoring job to run a specified Docker container image.
', ], ], 'MonitoringBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'MonitoringJobDefinition$BaselineConfig' => 'Baseline configuration used to validate that the data conforms to the specified constraints and statistics
', ], ], 'MonitoringClusterConfig' => [ 'base' => 'Configuration for the cluster used to run model monitoring jobs.
', 'refs' => [ 'MonitoringResources$ClusterConfig' => 'The configuration for the cluster resources used to run the processing job.
', ], ], 'MonitoringConstraintsResource' => [ 'base' => 'The constraints resource for a monitoring job.
', 'refs' => [ 'DataQualityBaselineConfig$ConstraintsResource' => NULL, 'ModelBiasBaselineConfig$ConstraintsResource' => NULL, 'ModelExplainabilityBaselineConfig$ConstraintsResource' => NULL, 'ModelQualityBaselineConfig$ConstraintsResource' => NULL, 'MonitoringBaselineConfig$ConstraintsResource' => 'The baseline constraint file in Amazon S3 that the current monitoring job should validated against.
', ], ], 'MonitoringContainerArguments' => [ 'base' => NULL, 'refs' => [ 'DataQualityAppSpecification$ContainerArguments' => 'The arguments to send to the container that the monitoring job runs.
', 'ModelQualityAppSpecification$ContainerArguments' => 'An array of arguments for the container used to run the monitoring job.
', 'MonitoringAppSpecification$ContainerArguments' => 'An array of arguments for the container used to run the monitoring job.
', ], ], 'MonitoringCsvDatasetFormat' => [ 'base' => 'Represents the CSV dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Csv' => 'The CSV dataset used in the monitoring job.
', ], ], 'MonitoringDatapointsToAlert' => [ 'base' => NULL, 'refs' => [ 'MonitoringAlertSummary$DatapointsToAlert' => 'Within EvaluationPeriod
, how many execution failures will raise an alert.
Within EvaluationPeriod
, how many execution failures will raise an alert.
Represents the dataset format used when running a monitoring job.
', 'refs' => [ 'BatchTransformInput$DatasetFormat' => 'The dataset format for your batch transform job.
', ], ], 'MonitoringEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'DataQualityAppSpecification$Environment' => 'Sets the environment variables in the container that the monitoring job runs.
', 'ModelBiasAppSpecification$Environment' => 'Sets the environment variables in the Docker container.
', 'ModelExplainabilityAppSpecification$Environment' => 'Sets the environment variables in the Docker container.
', 'ModelQualityAppSpecification$Environment' => 'Sets the environment variables in the container that the monitoring job runs.
', 'MonitoringJobDefinition$Environment' => 'Sets the environment variables in the Docker container.
', ], ], 'MonitoringEvaluationPeriod' => [ 'base' => NULL, 'refs' => [ 'MonitoringAlertSummary$EvaluationPeriod' => 'The number of most recent monitoring executions to consider when evaluating alert status.
', 'UpdateMonitoringAlertRequest$EvaluationPeriod' => 'The number of most recent monitoring executions to consider when evaluating alert status.
', ], ], 'MonitoringExecutionSortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringExecutionsRequest$SortBy' => 'Whether to sort the results by the Status
, CreationTime
, or ScheduledTime
field. The default is CreationTime
.
Summary of information about the last monitoring job to run.
', 'refs' => [ 'DescribeMonitoringScheduleResponse$LastMonitoringExecutionSummary' => 'Describes metadata on the last execution to run, if there was one.
', 'ModelDashboardMonitoringSchedule$LastMonitoringExecutionSummary' => NULL, 'MonitoringExecutionSummaryList$member' => NULL, 'MonitoringSchedule$LastMonitoringExecutionSummary' => NULL, ], ], 'MonitoringExecutionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringExecutionsResponse$MonitoringExecutionSummaries' => 'A JSON array in which each element is a summary for a monitoring execution.
', ], ], 'MonitoringGroundTruthS3Input' => [ 'base' => 'The ground truth labels for the dataset used for the monitoring job.
', 'refs' => [ 'ModelBiasJobInput$GroundTruthS3Input' => 'Location of ground truth labels to use in model bias job.
', 'ModelQualityJobInput$GroundTruthS3Input' => 'The ground truth label provided for the model.
', ], ], 'MonitoringInput' => [ 'base' => 'The inputs for a monitoring job.
', 'refs' => [ 'MonitoringInputs$member' => NULL, ], ], 'MonitoringInputs' => [ 'base' => NULL, 'refs' => [ 'MonitoringJobDefinition$MonitoringInputs' => 'The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
', ], ], 'MonitoringJobDefinition' => [ 'base' => 'Defines the monitoring job.
', 'refs' => [ 'MonitoringScheduleConfig$MonitoringJobDefinition' => 'Defines the monitoring job.
', ], ], 'MonitoringJobDefinitionArn' => [ 'base' => NULL, 'refs' => [ 'CreateDataQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the job definition.
', 'CreateModelBiasJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model bias job.
', 'CreateModelExplainabilityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model explainability job.
', 'CreateModelQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model quality monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the data quality monitoring job definition.
', 'DescribeModelBiasJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model bias job.
', 'DescribeModelExplainabilityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model explainability job.
', 'DescribeModelQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model quality job.
', 'MonitoringJobDefinitionSummary$MonitoringJobDefinitionArn' => 'The Amazon Resource Name (ARN) of the monitoring job.
', ], ], 'MonitoringJobDefinitionName' => [ 'base' => NULL, 'refs' => [ 'CreateDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name for the monitoring job definition.
', 'CreateModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'CreateModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'CreateModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the monitoring job definition.
', 'DeleteDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the data quality monitoring job definition to delete.
', 'DeleteModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the model bias job definition to delete.
', 'DeleteModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition to delete.
', 'DeleteModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the model quality monitoring job definition to delete.
', 'DescribeDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the data quality monitoring job definition to describe.
', 'DescribeDataQualityJobDefinitionResponse$JobDefinitionName' => 'The name of the data quality monitoring job definition.
', 'DescribeModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelBiasJobDefinitionResponse$JobDefinitionName' => 'The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelExplainabilityJobDefinitionResponse$JobDefinitionName' => 'The name of the explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelQualityJobDefinitionResponse$JobDefinitionName' => 'The name of the quality job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'ListMonitoringExecutionsRequest$MonitoringJobDefinitionName' => 'Gets a list of the monitoring job runs of the specified monitoring job definitions.
', 'ListMonitoringSchedulesRequest$MonitoringJobDefinitionName' => 'Gets a list of the monitoring schedules for the specified monitoring job definition.
', 'MonitoringExecutionSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job.
', 'MonitoringJobDefinitionSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job.
', 'MonitoringScheduleConfig$MonitoringJobDefinitionName' => 'The name of the monitoring job definition to schedule.
', 'MonitoringScheduleSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job definition that the schedule is for.
', ], ], 'MonitoringJobDefinitionSortKey' => [ 'base' => NULL, 'refs' => [ 'ListDataQualityJobDefinitionsRequest$SortBy' => 'The field to sort results by. The default is CreationTime
.
Whether to sort results by the Name
or CreationTime
field. The default is CreationTime
.
Whether to sort results by the Name
or CreationTime
field. The default is CreationTime
.
The field to sort results by. The default is CreationTime
.
Summary information about a monitoring job.
', 'refs' => [ 'MonitoringJobDefinitionSummaryList$member' => NULL, ], ], 'MonitoringJobDefinitionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListDataQualityJobDefinitionsResponse$JobDefinitionSummaries' => 'A list of data quality monitoring job definitions.
', 'ListModelBiasJobDefinitionsResponse$JobDefinitionSummaries' => 'A JSON array in which each element is a summary for a model bias jobs.
', 'ListModelExplainabilityJobDefinitionsResponse$JobDefinitionSummaries' => 'A JSON array in which each element is a summary for a explainability bias jobs.
', 'ListModelQualityJobDefinitionsResponse$JobDefinitionSummaries' => 'A list of summaries of model quality monitoring job definitions.
', ], ], 'MonitoringJsonDatasetFormat' => [ 'base' => 'Represents the JSON dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Json' => 'The JSON dataset used in the monitoring job
', ], ], 'MonitoringMaxRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'MonitoringStoppingCondition$MaxRuntimeInSeconds' => 'The maximum runtime allowed in seconds.
The MaxRuntimeInSeconds
cannot exceed the frequency of the job. For data quality and model explainability, this can be up to 3600 seconds for an hourly schedule. For model bias and model quality hourly schedules, this can be up to 1800 seconds.
The networking configuration for the monitoring job.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$NetworkConfig' => 'Specifies networking configuration for the monitoring job.
', 'CreateModelBiasJobDefinitionRequest$NetworkConfig' => 'Networking options for a model bias job.
', 'CreateModelExplainabilityJobDefinitionRequest$NetworkConfig' => 'Networking options for a model explainability job.
', 'CreateModelQualityJobDefinitionRequest$NetworkConfig' => 'Specifies the network configuration for the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$NetworkConfig' => 'The networking configuration for the data quality monitoring job.
', 'DescribeModelBiasJobDefinitionResponse$NetworkConfig' => 'Networking options for a model bias job.
', 'DescribeModelExplainabilityJobDefinitionResponse$NetworkConfig' => 'Networking options for a model explainability job.
', 'DescribeModelQualityJobDefinitionResponse$NetworkConfig' => 'Networking options for a model quality job.
', ], ], 'MonitoringOutput' => [ 'base' => 'The output object for a monitoring job.
', 'refs' => [ 'MonitoringOutputs$member' => NULL, ], ], 'MonitoringOutputConfig' => [ 'base' => 'The output configuration for monitoring jobs.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityJobOutputConfig' => NULL, 'CreateModelBiasJobDefinitionRequest$ModelBiasJobOutputConfig' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityJobOutputConfig' => NULL, 'CreateModelQualityJobDefinitionRequest$ModelQualityJobOutputConfig' => NULL, 'DescribeDataQualityJobDefinitionResponse$DataQualityJobOutputConfig' => NULL, 'DescribeModelBiasJobDefinitionResponse$ModelBiasJobOutputConfig' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityJobOutputConfig' => NULL, 'DescribeModelQualityJobDefinitionResponse$ModelQualityJobOutputConfig' => NULL, 'MonitoringJobDefinition$MonitoringOutputConfig' => 'The array of outputs from the monitoring job to be uploaded to Amazon S3.
', ], ], 'MonitoringOutputs' => [ 'base' => NULL, 'refs' => [ 'MonitoringOutputConfig$MonitoringOutputs' => 'Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
', ], ], 'MonitoringParquetDatasetFormat' => [ 'base' => 'Represents the Parquet dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Parquet' => 'The Parquet dataset used in the monitoring job
', ], ], 'MonitoringProblemType' => [ 'base' => NULL, 'refs' => [ 'ModelQualityAppSpecification$ProblemType' => 'The machine learning problem type of the model that the monitoring job monitors.
', ], ], 'MonitoringResources' => [ 'base' => 'Identifies the resources to deploy for a monitoring job.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$JobResources' => NULL, 'CreateModelBiasJobDefinitionRequest$JobResources' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$JobResources' => NULL, 'CreateModelQualityJobDefinitionRequest$JobResources' => NULL, 'DescribeDataQualityJobDefinitionResponse$JobResources' => NULL, 'DescribeModelBiasJobDefinitionResponse$JobResources' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$JobResources' => NULL, 'DescribeModelQualityJobDefinitionResponse$JobResources' => NULL, 'MonitoringJobDefinition$MonitoringResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
', ], ], 'MonitoringS3Output' => [ 'base' => 'Information about where and how you want to store the results of a monitoring job.
', 'refs' => [ 'MonitoringOutput$S3Output' => 'The Amazon S3 storage location where the results of a monitoring job are saved.
', ], ], 'MonitoringS3Uri' => [ 'base' => NULL, 'refs' => [ 'MonitoringGroundTruthS3Input$S3Uri' => 'The address of the Amazon S3 location of the ground truth labels.
', 'MonitoringS3Output$S3Uri' => 'A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
', ], ], 'MonitoringSchedule' => [ 'base' => 'A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'refs' => [ 'MonitoringScheduleList$member' => NULL, ], ], 'MonitoringScheduleArn' => [ 'base' => NULL, 'refs' => [ 'CreateMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'DescribeProcessingJobResponse$MonitoringScheduleArn' => 'The ARN of a monitoring schedule for an endpoint associated with this processing job.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of a monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'MonitoringScheduleSummary$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'ProcessingJob$MonitoringScheduleArn' => 'The ARN of a monitoring schedule for an endpoint associated with this processing job.
', 'UpdateMonitoringAlertResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'UpdateMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', ], ], 'MonitoringScheduleConfig' => [ 'base' => 'Configures the monitoring schedule and defines the monitoring job.
', 'refs' => [ 'CreateMonitoringScheduleRequest$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleConfig' => NULL, 'MonitoringSchedule$MonitoringScheduleConfig' => NULL, 'UpdateMonitoringScheduleRequest$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', ], ], 'MonitoringScheduleList' => [ 'base' => NULL, 'refs' => [ 'Endpoint$MonitoringSchedules' => 'A list of monitoring schedules for the endpoint. For information about model monitoring, see Amazon SageMaker Model Monitor.
', ], ], 'MonitoringScheduleName' => [ 'base' => NULL, 'refs' => [ 'CreateMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
', 'DeleteMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule to delete.
', 'DescribeMonitoringScheduleRequest$MonitoringScheduleName' => 'Name of a previously created monitoring schedule.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleName' => 'Name of the monitoring schedule.
', 'ListMonitoringAlertHistoryRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'ListMonitoringAlertsRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'ListMonitoringExecutionsRequest$MonitoringScheduleName' => 'Name of a specific schedule to fetch jobs for.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'MonitoringAlertHistorySummary$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'MonitoringExecutionSummary$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'MonitoringScheduleSummary$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'StartMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the schedule to start.
', 'StopMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the schedule to stop.
', 'UpdateMonitoringAlertRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'UpdateMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
', ], ], 'MonitoringScheduleSortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringSchedulesRequest$SortBy' => 'Whether to sort the results by the Status
, CreationTime
, or ScheduledTime
field. The default is CreationTime
.
Summarizes the monitoring schedule.
', 'refs' => [ 'MonitoringScheduleSummaryList$member' => NULL, ], ], 'MonitoringScheduleSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringSchedulesResponse$MonitoringScheduleSummaries' => 'A JSON array in which each element is a summary for a monitoring schedule.
', ], ], 'MonitoringStatisticsResource' => [ 'base' => 'The statistics resource for a monitoring job.
', 'refs' => [ 'DataQualityBaselineConfig$StatisticsResource' => NULL, 'MonitoringBaselineConfig$StatisticsResource' => 'The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
', ], ], 'MonitoringStoppingCondition' => [ 'base' => 'A time limit for how long the monitoring job is allowed to run before stopping.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelBiasJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelQualityJobDefinitionRequest$StoppingCondition' => NULL, 'DescribeDataQualityJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelBiasJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelQualityJobDefinitionResponse$StoppingCondition' => NULL, 'MonitoringJobDefinition$StoppingCondition' => 'Specifies a time limit for how long the monitoring job is allowed to run.
', ], ], 'MonitoringTimeOffsetString' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$StartTimeOffset' => 'If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'BatchTransformInput$EndTimeOffset' => 'If specified, monitoring jobs subtract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'EndpointInput$StartTimeOffset' => 'If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'EndpointInput$EndTimeOffset' => 'If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', ], ], 'MonitoringType' => [ 'base' => NULL, 'refs' => [ 'DescribeMonitoringScheduleResponse$MonitoringType' => 'The type of the monitoring job that this schedule runs. This is one of the following values.
DATA_QUALITY
- The schedule is for a data quality monitoring job.
MODEL_QUALITY
- The schedule is for a model quality monitoring job.
MODEL_BIAS
- The schedule is for a bias monitoring job.
MODEL_EXPLAINABILITY
- The schedule is for an explainability monitoring job.
A filter that returns only the monitoring job runs of the specified monitoring type.
', 'ListMonitoringSchedulesRequest$MonitoringTypeEquals' => 'A filter that returns only the monitoring schedules for the specified monitoring type.
', 'ModelDashboardMonitoringSchedule$MonitoringType' => 'The monitor type of a model monitor.
', 'MonitoringExecutionSummary$MonitoringType' => 'The type of the monitoring job.
', 'MonitoringSchedule$MonitoringType' => 'The type of the monitoring job definition to schedule.
', 'MonitoringScheduleConfig$MonitoringType' => 'The type of the monitoring job definition to schedule.
', 'MonitoringScheduleSummary$MonitoringType' => 'The type of the monitoring job definition that the schedule is for.
', ], ], 'MountPath' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$MountPath' => 'The path within the image to mount the user\'s EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.
', ], ], 'MultiModelConfig' => [ 'base' => 'Specifies additional configuration for hosting multi-model endpoints.
', 'refs' => [ 'ContainerDefinition$MultiModelConfig' => 'Specifies additional configuration for multi-model endpoints.
', ], ], 'NameContains' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsInput$NameContains' => 'A string in the algorithm name. This filter returns only algorithms whose name contains the specified string.
', 'ListClustersRequest$NameContains' => 'Set the maximum number of instances to print in the list.
', 'ListCompilationJobsRequest$NameContains' => 'A filter that returns the model compilation jobs whose name contains a specified string.
', 'ListDataQualityJobDefinitionsRequest$NameContains' => 'A string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.
', 'ListDeviceFleetsRequest$NameContains' => 'Filter for fleets containing this name in their fleet device name.
', 'ListEdgeDeploymentPlansRequest$NameContains' => 'Selects edge deployment plans with names containing this name.
', 'ListEdgeDeploymentPlansRequest$DeviceFleetNameContains' => 'Selects edge deployment plans with a device fleet name containing this name.
', 'ListEdgePackagingJobsRequest$NameContains' => 'Filter for jobs containing this name in their packaging job name.
', 'ListEdgePackagingJobsRequest$ModelNameContains' => 'Filter for jobs where the model name contains this string.
', 'ListHubContentsRequest$NameContains' => 'Only list hub content if the name contains the specified string.
', 'ListHubsRequest$NameContains' => 'Only list hubs with names that contain the specified string.
', 'ListHyperParameterTuningJobsRequest$NameContains' => 'A string in the tuning job name. This filter returns only tuning jobs whose name contains the specified string.
', 'ListInferenceExperimentsRequest$NameContains' => 'Selects inference experiments whose names contain this name.
', 'ListInferenceRecommendationsJobsRequest$NameContains' => 'A string in the job name. This filter returns only recommendations whose name contains the specified string.
', 'ListLabelingJobsRequest$NameContains' => 'A string in the labeling job name. This filter returns only labeling jobs whose name contains the specified string.
', 'ListModelBiasJobDefinitionsRequest$NameContains' => 'Filter for model bias jobs whose name contains a specified string.
', 'ListModelExplainabilityJobDefinitionsRequest$NameContains' => 'Filter for model explainability jobs whose name contains a specified string.
', 'ListModelPackageGroupsInput$NameContains' => 'A string in the model group name. This filter returns only model groups whose name contains the specified string.
', 'ListModelPackagesInput$NameContains' => 'A string in the model package name. This filter returns only model packages whose name contains the specified string.
', 'ListModelQualityJobDefinitionsRequest$NameContains' => 'A string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.
', 'ListMonitoringSchedulesRequest$NameContains' => 'Filter for monitoring schedules whose name contains a specified string.
', 'ListTrainingJobsRequest$NameContains' => 'A string in the training job name. This filter returns only training jobs whose name contains the specified string.
', 'ListTransformJobsRequest$NameContains' => 'A string in the transform job name. This filter returns only transform jobs whose name contains the specified string.
', ], ], 'NeoVpcConfig' => [ 'base' => 'The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker Compilation Jobs Access to Resources in Your Amazon VPC.
', 'refs' => [ 'CreateCompilationJobRequest$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
', 'DescribeCompilationJobResponse$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
', ], ], 'NeoVpcSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'NeoVpcSecurityGroupIds$member' => NULL, ], ], 'NeoVpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'NeoVpcConfig$SecurityGroupIds' => 'The VPC security group IDs. IDs have the form of sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in the Subnets
field.
The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the model in Amazon S3.
', ], ], 'NestedFilters' => [ 'base' => 'A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
For example, to filter on a training job\'s InputDataConfig
property with a specific channel name and S3Uri
prefix, define the following filters:
\'{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}\',
\'{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}\'
A list of nested filter objects.
', ], ], 'NetworkConfig' => [ 'base' => 'Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
', 'refs' => [ 'CreateProcessingJobRequest$NetworkConfig' => 'Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.
', 'DescribeProcessingJobResponse$NetworkConfig' => 'Networking options for a processing job.
', 'MonitoringJobDefinition$NetworkConfig' => 'Specifies networking options for an monitoring job.
', 'ProcessingJob$NetworkConfig' => NULL, ], ], 'NetworkInterfaceId' => [ 'base' => NULL, 'refs' => [ 'DescribeNotebookInstanceOutput$NetworkInterfaceId' => 'The network interface IDs that SageMaker created at the time of creating the instance.
', ], ], 'NextToken' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceRequest$NextToken' => 'Next token of device description.
', 'DescribeDeviceResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'DescribeEdgeDeploymentPlanRequest$NextToken' => 'If the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.
', 'DescribeEdgeDeploymentPlanResponse$NextToken' => 'Token to use when calling the next set of stages in the edge deployment plan.
', 'DescribeFeatureGroupRequest$NextToken' => 'A token to resume pagination of the list of Features
(FeatureDefinitions
). 2,500 Features
are returned by default.
A token to resume pagination of the list of Features
(FeatureDefinitions
).
If the previous call to ListActions
didn\'t return the full set of actions, the call returns a token for getting the next set of actions.
A token for getting the next set of actions, if there are any.
', 'ListAlgorithmsInput$NextToken' => 'If the response to a previous ListAlgorithms
request was truncated, the response includes a NextToken
. To retrieve the next set of algorithms, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListAliasesRequest$NextToken' => 'If the previous call to ListAliases
didn\'t return the full set of aliases, the call returns a token for retrieving the next set of aliases.
A token for getting the next set of aliases, if more aliases exist.
', 'ListAppImageConfigsRequest$NextToken' => 'If the previous call to ListImages
didn\'t return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.
A token for getting the next set of AppImageConfigs, if there are any.
', 'ListAppsRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListAppsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListArtifactsRequest$NextToken' => 'If the previous call to ListArtifacts
didn\'t return the full set of artifacts, the call returns a token for getting the next set of artifacts.
A token for getting the next set of artifacts, if there are any.
', 'ListAssociationsRequest$NextToken' => 'If the previous call to ListAssociations
didn\'t return the full set of associations, the call returns a token for getting the next set of associations.
A token for getting the next set of associations, if there are any.
', 'ListAutoMLJobsRequest$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListAutoMLJobsResponse$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCandidatesForAutoMLJobRequest$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCandidatesForAutoMLJobResponse$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListClusterNodesRequest$NextToken' => 'If the result of the previous ListClusterNodes
request was truncated, the response includes a NextToken
. To retrieve the next set of cluster nodes, use the token in the next request.
The next token specified for listing instances in a SageMaker HyperPod cluster.
', 'ListClustersRequest$NextToken' => 'Set the next token to retrieve the list of SageMaker HyperPod clusters.
', 'ListClustersResponse$NextToken' => 'If the result of the previous ListClusters
request was truncated, the response includes a NextToken
. To retrieve the next set of clusters, use the token in the next request.
If the result of a ListCodeRepositoriesOutput
request was truncated, the response includes a NextToken
. To get the next set of Git repositories, use the token in the next request.
If the result of a ListCodeRepositoriesOutput
request was truncated, the response includes a NextToken
. To get the next set of Git repositories, use the token in the next request.
If the result of the previous ListCompilationJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of model compilation jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this NextToken
. To retrieve the next set of model compilation jobs, use this token in the next request.
If the previous call to ListContexts
didn\'t return the full set of contexts, the call returns a token for getting the next set of contexts.
A token for getting the next set of contexts, if there are any.
', 'ListDataQualityJobDefinitionsRequest$NextToken' => 'If the result of the previous ListDataQualityJobDefinitions
request was truncated, the response includes a NextToken
. To retrieve the next set of transform jobs, use the token in the next request.>
If the result of the previous ListDataQualityJobDefinitions
request was truncated, the response includes a NextToken
. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.
The response from the last list when returning a list large enough to need tokening.
', 'ListDeviceFleetsResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDevicesRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDevicesResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDomainsRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListDomainsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListEdgeDeploymentPlansRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListEdgeDeploymentPlansResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListEdgePackagingJobsRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListEdgePackagingJobsResponse$NextToken' => 'Token to use when calling the next page of results.
', 'ListExperimentsRequest$NextToken' => 'If the previous call to ListExperiments
didn\'t return the full set of experiments, the call returns a token for getting the next set of experiments.
A token for getting the next set of experiments, if there are any.
', 'ListFeatureGroupsRequest$NextToken' => 'A token to resume pagination of ListFeatureGroups
results.
A token to resume pagination of ListFeatureGroups
results.
A token to resume pagination.
', 'ListFlowDefinitionsResponse$NextToken' => 'A token to resume pagination.
', 'ListHubContentVersionsRequest$NextToken' => 'If the response to a previous ListHubContentVersions
request was truncated, the response includes a NextToken
. To retrieve the next set of hub content versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content versions, use it in the subsequent request.
', 'ListHubContentsRequest$NextToken' => 'If the response to a previous ListHubContents
request was truncated, the response includes a NextToken
. To retrieve the next set of hub content, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content, use it in the subsequent request.
', 'ListHubsRequest$NextToken' => 'If the response to a previous ListHubs
request was truncated, the response includes a NextToken
. To retrieve the next set of hubs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hubs, use it in the subsequent request.
', 'ListHumanTaskUisRequest$NextToken' => 'A token to resume pagination.
', 'ListHumanTaskUisResponse$NextToken' => 'A token to resume pagination.
', 'ListHyperParameterTuningJobsRequest$NextToken' => 'If the result of the previous ListHyperParameterTuningJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of tuning jobs, use the token in the next request.
If the result of this ListHyperParameterTuningJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of tuning jobs, use the token in the next request.
If the previous call to ListImageVersions
didn\'t return the full set of versions, the call returns a token for getting the next set of versions.
A token for getting the next set of versions, if there are any.
', 'ListImagesRequest$NextToken' => 'If the previous call to ListImages
didn\'t return the full set of images, the call returns a token for getting the next set of images.
A token for getting the next set of images, if there are any.
', 'ListInferenceExperimentsRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListInferenceExperimentsResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListInferenceRecommendationsJobStepsRequest$NextToken' => 'A token that you can specify to return more results from the list. Specify this field if you have a token that was returned from a previous request.
', 'ListInferenceRecommendationsJobStepsResponse$NextToken' => 'A token that you can specify in your next request to return more results from the list.
', 'ListInferenceRecommendationsJobsRequest$NextToken' => 'If the response to a previous ListInferenceRecommendationsJobsRequest
request was truncated, the response includes a NextToken
. To retrieve the next set of recommendations, use the token in the next request.
A token for getting the next set of recommendations, if there are any.
', 'ListLabelingJobsForWorkteamRequest$NextToken' => 'If the result of the previous ListLabelingJobsForWorkteam
request was truncated, the response includes a NextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
', 'ListLabelingJobsRequest$NextToken' => 'If the result of the previous ListLabelingJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
', 'ListLineageGroupsRequest$NextToken' => 'If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListLineageGroupsResponse$NextToken' => 'If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListModelBiasJobDefinitionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelBiasJobDefinitionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelCardExportJobsRequest$NextToken' => 'If the response to a previous ListModelCardExportJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of model card export jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card export jobs, use it in the subsequent request.
', 'ListModelCardVersionsRequest$NextToken' => 'If the response to a previous ListModelCardVersions
request was truncated, the response includes a NextToken
. To retrieve the next set of model card versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card versions, use it in the subsequent request.
', 'ListModelCardsRequest$NextToken' => 'If the response to a previous ListModelCards
request was truncated, the response includes a NextToken
. To retrieve the next set of model cards, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model cards, use it in the subsequent request.
', 'ListModelExplainabilityJobDefinitionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelExplainabilityJobDefinitionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelMetadataRequest$NextToken' => 'If the response to a previous ListModelMetadataResponse
request was truncated, the response includes a NextToken. To retrieve the next set of model metadata, use the token in the next request.
A token for getting the next set of recommendations, if there are any.
', 'ListModelPackageGroupsInput$NextToken' => 'If the result of the previous ListModelPackageGroups
request was truncated, the response includes a NextToken
. To retrieve the next set of model groups, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model groups, use it in the subsequent request.
', 'ListModelPackagesInput$NextToken' => 'If the response to a previous ListModelPackages
request was truncated, the response includes a NextToken
. To retrieve the next set of model packages, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model packages, use it in the subsequent request.
', 'ListModelQualityJobDefinitionsRequest$NextToken' => 'If the result of the previous ListModelQualityJobDefinitions
request was truncated, the response includes a NextToken
. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.
', 'ListMonitoringAlertHistoryRequest$NextToken' => 'If the result of the previous ListMonitoringAlertHistory
request was truncated, the response includes a NextToken
. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
', 'ListMonitoringAlertsRequest$NextToken' => 'If the result of the previous ListMonitoringAlerts
request was truncated, the response includes a NextToken
. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
', 'ListMonitoringExecutionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringExecutionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringSchedulesRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringSchedulesResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListNotebookInstanceLifecycleConfigsInput$NextToken' => 'If the result of a ListNotebookInstanceLifecycleConfigs
request was truncated, the response includes a NextToken
. To get the next set of lifecycle configurations, use the token in the next request.
If the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.
', 'ListNotebookInstancesInput$NextToken' => ' If the previous call to the ListNotebookInstances
is truncated, the response includes a NextToken
. You can use this token in your subsequent ListNotebookInstances
request to fetch the next set of notebook instances.
You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.
If the response to the previous ListNotebookInstances
request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps
request was truncated, the response includes a NextToken
. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps
request was truncated, the response includes a NextToken
. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutions
request was truncated, the response includes a NextToken
. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutions
request was truncated, the response includes a NextToken
. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution
request was truncated, the response includes a NextToken
. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution
request was truncated, the response includes a NextToken
. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelines
request was truncated, the response includes a NextToken
. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListPipelines
request was truncated, the response includes a NextToken
. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListProcessingJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of processing jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of processing jobs, use it in the subsequent request.
', 'ListProjectsInput$NextToken' => 'If the result of the previous ListProjects
request was truncated, the response includes a NextToken
. To retrieve the next set of projects, use the token in the next request.
If the result of the previous ListCompilationJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of model compilation jobs, use the token in the next request.
A token to resume pagination of ListResourceCatalogs
results.
A token to resume pagination of ListResourceCatalogs
results.
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListSpacesResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListStageDevicesRequest$NextToken' => 'The response from the last list when returning a list large enough to neeed tokening.
', 'ListStageDevicesResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListStudioLifecycleConfigsRequest$NextToken' => 'If the previous call to ListStudioLifecycleConfigs didn\'t return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.
', 'ListStudioLifecycleConfigsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListSubscribedWorkteamsRequest$NextToken' => 'If the result of the previous ListSubscribedWorkteams
request was truncated, the response includes a NextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
', 'ListTagsInput$NextToken' => ' If the response to the previous ListTags
request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.
If response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$NextToken' => 'If the result of the previous ListTrainingJobsForHyperParameterTuningJob
request was truncated, the response includes a NextToken
. To retrieve the next set of training jobs, use the token in the next request.
If the result of this ListTrainingJobsForHyperParameterTuningJob
request was truncated, the response includes a NextToken
. To retrieve the next set of training jobs, use the token in the next request.
If the result of the previous ListTrainingJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of training jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
', 'ListTransformJobsRequest$NextToken' => 'If the result of the previous ListTransformJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of transform jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.
', 'ListTrialComponentsRequest$NextToken' => 'If the previous call to ListTrialComponents
didn\'t return the full set of components, the call returns a token for getting the next set of components.
A token for getting the next set of components, if there are any.
', 'ListTrialsRequest$NextToken' => 'If the previous call to ListTrials
didn\'t return the full set of trials, the call returns a token for getting the next set of trials.
A token for getting the next set of trials, if there are any.
', 'ListUserProfilesRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListUserProfilesResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListWorkforcesRequest$NextToken' => 'A token to resume pagination.
', 'ListWorkforcesResponse$NextToken' => 'A token to resume pagination.
', 'ListWorkteamsRequest$NextToken' => 'If the result of the previous ListWorkteams
request was truncated, the response includes a NextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
', 'SearchRequest$NextToken' => 'If more than MaxResults
resources match the specified SearchExpression
, the response includes a NextToken
. The NextToken
can be passed to the next SearchRequest
to continue retrieving results.
If the result of the previous Search
request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.
The name of the space that appears in the SageMaker Studio UI.
', 'CustomImageContainerArguments$member' => NULL, 'DescribeSpaceResponse$SpaceDisplayName' => 'The name of the space that appears in the Amazon SageMaker Studio UI.
', 'SpaceDetails$SpaceDisplayName' => 'The name of the space that appears in the Studio UI.
', 'UpdateSpaceRequest$SpaceDisplayName' => 'The name of the space that appears in the Amazon SageMaker Studio UI.
', ], ], 'NotebookInstanceAcceleratorType' => [ 'base' => NULL, 'refs' => [ 'NotebookInstanceAcceleratorTypes$member' => NULL, ], ], 'NotebookInstanceAcceleratorTypes' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$AcceleratorTypes' => 'A list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'DescribeNotebookInstanceOutput$AcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'UpdateNotebookInstanceInput$AcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types to associate with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', ], ], 'NotebookInstanceArn' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceOutput$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', 'DescribeNotebookInstanceOutput$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', 'NotebookInstanceSummary$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', ], ], 'NotebookInstanceLifecycleConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', 'DescribeNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', 'NotebookInstanceLifecycleConfigSummary$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigContent' => [ 'base' => NULL, 'refs' => [ 'NotebookInstanceLifecycleHook$Content' => 'A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigList' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceLifecycleConfigInput$OnCreate' => 'A shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
', 'CreateNotebookInstanceLifecycleConfigInput$OnStart' => 'A shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
', 'DescribeNotebookInstanceLifecycleConfigOutput$OnCreate' => 'The shell script that runs only once, when you create a notebook instance.
', 'DescribeNotebookInstanceLifecycleConfigOutput$OnStart' => 'The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
', 'UpdateNotebookInstanceLifecycleConfigInput$OnCreate' => 'The shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
', 'UpdateNotebookInstanceLifecycleConfigInput$OnStart' => 'The shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
', ], ], 'NotebookInstanceLifecycleConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$LifecycleConfigName' => 'The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'CreateNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'DeleteNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration to delete.
', 'DescribeNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration to describe.
', 'DescribeNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'DescribeNotebookInstanceOutput$NotebookInstanceLifecycleConfigName' => 'Returns the name of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance
', 'ListNotebookInstancesInput$NotebookInstanceLifecycleConfigNameContains' => 'A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.
', 'NotebookInstanceLifecycleConfigSummary$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'NotebookInstanceSummary$NotebookInstanceLifecycleConfigName' => 'The name of a notebook instance lifecycle configuration associated with this notebook instance.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'UpdateNotebookInstanceInput$LifecycleConfigName' => 'The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'UpdateNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigNameContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsInput$NameContains' => 'A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.
', ], ], 'NotebookInstanceLifecycleConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsInput$SortBy' => 'Sorts the list of results. The default is CreationTime
.
The sort order for results.
', ], ], 'NotebookInstanceLifecycleConfigSummary' => [ 'base' => 'Provides a summary of a notebook instance lifecycle configuration.
', 'refs' => [ 'NotebookInstanceLifecycleConfigSummaryList$member' => NULL, ], ], 'NotebookInstanceLifecycleConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsOutput$NotebookInstanceLifecycleConfigs' => 'An array of NotebookInstanceLifecycleConfiguration
objects, each listing a lifecycle configuration.
Contains the notebook instance lifecycle configuration script.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH
environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin
.
View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances
in log stream [notebook-instance-name]/[LifecycleConfigHook]
.
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'refs' => [ 'NotebookInstanceLifecycleConfigList$member' => NULL, ], ], 'NotebookInstanceName' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$NotebookInstanceName' => 'The name of the new notebook instance.
', 'CreatePresignedNotebookInstanceUrlInput$NotebookInstanceName' => 'The name of the notebook instance.
', 'DeleteNotebookInstanceInput$NotebookInstanceName' => 'The name of the SageMaker notebook instance to delete.
', 'DescribeNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance that you want information about.
', 'DescribeNotebookInstanceOutput$NotebookInstanceName' => 'The name of the SageMaker notebook instance.
', 'NotebookInstanceSummary$NotebookInstanceName' => 'The name of the notebook instance that you want a summary for.
', 'StartNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to start.
', 'StopNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to terminate.
', 'UpdateNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to update.
', ], ], 'NotebookInstanceNameContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$NameContains' => 'A string in the notebook instances\' name. This filter returns only notebook instances whose name contains the specified string.
', ], ], 'NotebookInstanceSortKey' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$SortBy' => 'The field to sort results by. The default is Name
.
The sort order for results.
', ], ], 'NotebookInstanceStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeNotebookInstanceOutput$NotebookInstanceStatus' => 'The status of the notebook instance.
', 'ListNotebookInstancesInput$StatusEquals' => 'A filter that returns only notebook instances with the specified status.
', 'NotebookInstanceSummary$NotebookInstanceStatus' => 'The status of the notebook instance.
', ], ], 'NotebookInstanceSummary' => [ 'base' => 'Provides summary information for an SageMaker notebook instance.
', 'refs' => [ 'NotebookInstanceSummaryList$member' => NULL, ], ], 'NotebookInstanceSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesOutput$NotebookInstances' => 'An array of NotebookInstanceSummary
objects, one for each notebook instance.
A JSON object that contains the URL string.
', 'DescribeNotebookInstanceOutput$Url' => 'The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
', 'NotebookInstanceSummary$Url' => 'The URL that you use to connect to the Jupyter notebook running in your notebook instance.
', ], ], 'NotebookInstanceVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
', 'DescribeNotebookInstanceOutput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to the notebook instance.
', 'UpdateNotebookInstanceInput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can\'t determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can\'t decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.
', ], ], 'NotebookOutputOption' => [ 'base' => NULL, 'refs' => [ 'SharingSettings$NotebookOutputOption' => 'Whether to include the notebook cell output when sharing the notebook. The default is Disabled
.
Configures Amazon SNS notifications of available or expiring work items for work teams.
', 'refs' => [ 'CreateWorkteamRequest$NotificationConfiguration' => 'Configures notification of workers regarding available or expiring work items.
', 'UpdateWorkteamRequest$NotificationConfiguration' => 'Configures SNS topic notifications for available or expiring work items
', 'Workteam$NotificationConfiguration' => 'Configures SNS notifications of available or expiring work items for work teams.
', ], ], 'NotificationTopicArn' => [ 'base' => NULL, 'refs' => [ 'NotificationConfiguration$NotificationTopicArn' => 'The ARN for the Amazon SNS topic to which notifications should be published.
', ], ], 'NumberOfAcceleratorDevices' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentComputeResourceRequirements$NumberOfAcceleratorDevicesRequired' => 'The number of accelerators to allocate to run a model that you assign to an inference component. Accelerators include GPUs and Amazon Web Services Inferentia.
', ], ], 'NumberOfCpuCores' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentComputeResourceRequirements$NumberOfCpuCoresRequired' => 'The number of CPU cores to allocate to run a model that you assign to an inference component.
', ], ], 'NumberOfHumanWorkersPerDataObject' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$NumberOfHumanWorkersPerDataObject' => 'The number of human workers that will label an object.
', 'LabelingJobForWorkteamSummary$NumberOfHumanWorkersPerDataObject' => 'The configured number of workers per data object.
', ], ], 'NumberOfSteps' => [ 'base' => NULL, 'refs' => [ 'Stairs$NumberOfSteps' => 'Specifies how many steps to perform during traffic.
', ], ], 'ObjectiveStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$ObjectiveStatus' => 'The objective\'s status.
', 'HyperParameterTrainingJobSummary$ObjectiveStatus' => 'The status of the objective metric for the training job:
Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
Pending: The training job is in progress and evaluation of its final objective metric is pending.
Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
', 'ObjectiveStatusCounters$Pending' => 'The number of training jobs that are in progress and pending evaluation of their final objective metric.
', 'ObjectiveStatusCounters$Failed' => 'The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
', ], ], 'ObjectiveStatusCounters' => [ 'base' => 'Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$ObjectiveStatusCounters' => 'The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
', 'HyperParameterTuningJobSearchEntity$ObjectiveStatusCounters' => NULL, 'HyperParameterTuningJobSummary$ObjectiveStatusCounters' => 'The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
', ], ], 'OfflineStoreConfig' => [ 'base' => 'The configuration of an OfflineStore
.
Provide an OfflineStoreConfig
in a request to CreateFeatureGroup
to create an OfflineStore
.
To encrypt an OfflineStore
using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId
, in S3StorageConfig
.
Use this to configure an OfflineFeatureStore
. This parameter allows you to specify:
The Amazon Simple Storage Service (Amazon S3) location of an OfflineStore
.
A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.
An KMS encryption key to encrypt the Amazon S3 location used for OfflineStore
. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.
Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
To learn more about this parameter, see OfflineStoreConfig.
', 'DescribeFeatureGroupResponse$OfflineStoreConfig' => 'The configuration of the offline store. It includes the following configurations:
Amazon S3 location of the offline store.
Configuration of the Glue data catalog.
Table format of the offline store.
Option to disable the automatic creation of a Glue table for the offline store.
Encryption configuration.
The status of OfflineStore
.
The status of the OfflineStore
. Notifies you if replicating data into the OfflineStore
has failed. Returns either: Active
or Blocked
Notifies you if replicating data into the OfflineStore
has failed. Returns either: Active
or Blocked
.
An OfflineStore
status. Filters by OfflineStore
status.
An OfflineStore
status.
Use this parameter to configure your OIDC Identity Provider (IdP).
', 'refs' => [ 'CreateWorkforceRequest$OidcConfig' => 'Use this parameter to configure a private workforce using your own OIDC Identity Provider.
Do not use CognitoConfig
if you specify values for OidcConfig
.
Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.
', ], ], 'OidcConfigForResponse' => [ 'base' => 'Your OIDC IdP workforce configuration.
', 'refs' => [ 'Workforce$OidcConfig' => 'The configuration of an OIDC Identity Provider (IdP) private workforce.
', ], ], 'OidcEndpoint' => [ 'base' => NULL, 'refs' => [ 'OidcConfig$Issuer' => 'The OIDC IdP issuer used to configure your private workforce.
', 'OidcConfig$AuthorizationEndpoint' => 'The OIDC IdP authorization endpoint used to configure your private workforce.
', 'OidcConfig$TokenEndpoint' => 'The OIDC IdP token endpoint used to configure your private workforce.
', 'OidcConfig$UserInfoEndpoint' => 'The OIDC IdP user information endpoint used to configure your private workforce.
', 'OidcConfig$LogoutEndpoint' => 'The OIDC IdP logout endpoint used to configure your private workforce.
', 'OidcConfig$JwksUri' => 'The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
', 'OidcConfigForResponse$Issuer' => 'The OIDC IdP issuer used to configure your private workforce.
', 'OidcConfigForResponse$AuthorizationEndpoint' => 'The OIDC IdP authorization endpoint used to configure your private workforce.
', 'OidcConfigForResponse$TokenEndpoint' => 'The OIDC IdP token endpoint used to configure your private workforce.
', 'OidcConfigForResponse$UserInfoEndpoint' => 'The OIDC IdP user information endpoint used to configure your private workforce.
', 'OidcConfigForResponse$LogoutEndpoint' => 'The OIDC IdP logout endpoint used to configure your private workforce.
', 'OidcConfigForResponse$JwksUri' => 'The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
', ], ], 'OidcMemberDefinition' => [ 'base' => 'A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups
, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups
, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId
, for at rest data encryption. You can turn OnlineStore
on or off by specifying the EnableOnlineStore
flag at General Assembly.
The default value is False
.
You can turn the OnlineStore
on or off by specifying True
for the EnableOnlineStore
flag in OnlineStoreConfig
.
You can also include an Amazon Web Services KMS key ID (KMSKeyId
) for at-rest encryption of the OnlineStore
.
The default value is False
.
The configuration for the OnlineStore
.
Updates the feature group online store configuration.
', 'refs' => [ 'UpdateFeatureGroupRequest$OnlineStoreConfig' => 'Updates the feature group online store configuration.
', ], ], 'OnlineStoreSecurityConfig' => [ 'base' => 'The security configuration for OnlineStore
.
Use to specify KMS Key ID (KMSKeyId
) for at-rest encryption of your OnlineStore
.
The size of the OnlineStore
in bytes.
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
The value of Name
equals Value
.
The value of Name
doesn\'t equal Value
.
The Name
property exists.
The Name
property does not exist.
The value of Name
is greater than Value
. Not supported for text properties.
The value of Name
is greater than or equal to Value
. Not supported for text properties.
The value of Name
is less than Value
. Not supported for text properties.
The value of Name
is less than or equal to Value
. Not supported for text properties.
The value of Name
is one of the comma delimited strings in Value
. Only supported for text properties.
The value of Name
contains the string Value
. Only supported for text properties.
A SearchExpression
can include the Contains
operator multiple times when the value of Name
is one of the following:
Experiment.DisplayName
Experiment.ExperimentName
Experiment.Tags
Trial.DisplayName
Trial.TrialName
Trial.Tags
TrialComponent.DisplayName
TrialComponent.TrialComponentName
TrialComponent.Tags
TrialComponent.InputArtifacts
TrialComponent.OutputArtifacts
A SearchExpression
can include only one Contains
operator for all other values of Name
. In these cases, if you include multiple Contains
operators in the SearchExpression
, the result is the following error message: "\'CONTAINS\' operator usage limit of 1 exceeded.
"
The maximum value of the metric.
', 'TrialComponentMetricSummary$Min' => 'The minimum value of the metric.
', 'TrialComponentMetricSummary$Last' => 'The most recent value of the metric.
', 'TrialComponentMetricSummary$Avg' => 'The average value of the metric.
', 'TrialComponentMetricSummary$StdDev' => 'The standard deviation of the metric.
', ], ], 'OptionalInteger' => [ 'base' => NULL, 'refs' => [ 'TrialComponentMetricSummary$Count' => 'The number of samples used to generate the metric.
', ], ], 'OptionalVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to the processing instance.
', 'HyperParameterTuningResourceConfig$VolumeSizeInGB' => 'The volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for InstanceConfigs
is also specified.
Some instance types have a fixed total local storage size. If you select one of these instances for training, VolumeSizeInGB
cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.
SageMaker supports only the General Purpose SSD (gp2) storage volume type.
The size, in GB, of the ML storage volume attached to the processing instance.
', ], ], 'OrderKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$SortOrder' => 'The sort order for results. The default is Descending
.
The sort order for results. The default is Descending
.
The sort order for results. The default is Descending
.
The sort order for results. The default is Descending
.
The model output compression type. Select None
to output an uncompressed model, recommended for large model outputs. Defaults to gzip.
Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice
and TargetPlatform
are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice
list, use TargetPlatform
to describe the platform of your edge device and CompilerOptions
if there are specific settings that are required or recommended to use for particular TargetPlatform.
Provides information about the output location for the compiled model and the target device the model runs on.
', 'DescribeCompilationJobResponse$OutputConfig' => 'Information about the output location for the compiled model and the target device that the model runs on.
', ], ], 'OutputDataConfig' => [ 'base' => 'Provides information about how to store model training results (model artifacts).
', 'refs' => [ 'CreateTrainingJobRequest$OutputDataConfig' => 'Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
', 'DescribeTrainingJobResponse$OutputDataConfig' => 'The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
', 'HyperParameterTrainingJobDefinition$OutputDataConfig' => 'Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
', 'TrainingJob$OutputDataConfig' => 'The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
', 'TrainingJobDefinition$OutputDataConfig' => 'the path to the S3 bucket where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
', ], ], 'OutputParameter' => [ 'base' => 'An output parameter of a pipeline step.
', 'refs' => [ 'OutputParameterList$member' => NULL, ], ], 'OutputParameterList' => [ 'base' => NULL, 'refs' => [ 'CallbackStepMetadata$OutputParameters' => 'A list of the output parameters of the callback step.
', 'LambdaStepMetadata$OutputParameters' => 'A list of the output parameters of the Lambda step.
', 'SendPipelineExecutionStepSuccessRequest$OutputParameters' => 'A list of the output parameters of the callback step.
', ], ], 'OwnershipSettings' => [ 'base' => 'The collection of ownership settings for a space.
', 'refs' => [ 'CreateSpaceRequest$OwnershipSettings' => 'A collection of ownership settings.
', 'DescribeSpaceResponse$OwnershipSettings' => 'The collection of ownership settings for a space.
', ], ], 'OwnershipSettingsSummary' => [ 'base' => 'Specifies summary information about the ownership settings.
', 'refs' => [ 'SpaceDetails$OwnershipSettingsSummary' => 'Specifies summary information about the ownership settings.
', ], ], 'PaginationToken' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$NextToken' => 'If the result of the previous ListEndpointConfig
request was truncated, the response includes a NextToken
. To retrieve the next set of endpoint configurations, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent request
', 'ListEndpointsInput$NextToken' => 'If the result of a ListEndpoints
request was truncated, the response includes a NextToken
. To retrieve the next set of endpoints, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
', 'ListInferenceComponentsInput$NextToken' => 'A token that you use to get the next set of results following a truncated response. If the response to the previous request was truncated, that response provides the value for this token.
', 'ListInferenceComponentsOutput$NextToken' => 'The token to use in a subsequent request to get the next set of results following a truncated response.
', 'ListModelsInput$NextToken' => 'If the response to a previous ListModels
request was truncated, the response includes a NextToken
. To retrieve the next set of models, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.
', ], ], 'ParallelismConfiguration' => [ 'base' => 'Configuration that controls the parallelism of the pipeline. By default, the parallelism configuration specified applies to all executions of the pipeline unless overridden.
', 'refs' => [ 'CreatePipelineRequest$ParallelismConfiguration' => 'This is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.
', 'DescribePipelineExecutionResponse$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline.
', 'DescribePipelineResponse$ParallelismConfiguration' => 'Lists the parallelism configuration applied to the pipeline.
', 'Pipeline$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline.
', 'PipelineExecution$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline execution.
', 'RetryPipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline.
', 'StartPipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
', 'UpdatePipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
', 'UpdatePipelineRequest$ParallelismConfiguration' => 'If specified, it applies to all executions of this pipeline by default.
', ], ], 'Parameter' => [ 'base' => 'Assigns a value to a named Pipeline parameter.
', 'refs' => [ 'ParameterList$member' => NULL, ], ], 'ParameterKey' => [ 'base' => NULL, 'refs' => [ 'AutoParameter$Name' => 'The name of the hyperparameter to optimize using Autotune.
', 'CategoricalParameterRange$Name' => 'The name of the categorical hyperparameter to tune.
', 'ContinuousParameterRange$Name' => 'The name of the continuous hyperparameter to tune.
', 'IntegerParameterRange$Name' => 'The name of the hyperparameter to search.
', ], ], 'ParameterList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineParametersForExecutionResponse$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', 'PipelineExecution$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', 'StartPipelineExecutionRequest$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', ], ], 'ParameterName' => [ 'base' => NULL, 'refs' => [ 'HyperParameterSpecification$Name' => 'The name of this hyperparameter. The name must be unique.
', ], ], 'ParameterRange' => [ 'base' => 'Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
', 'refs' => [ 'HyperParameterSpecification$Range' => 'The allowed range for this hyperparameter.
', ], ], 'ParameterRanges' => [ 'base' => 'Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for Array Members
refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can\'t exceed the maximum number specified.
The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
', ], ], 'ParameterType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterSpecification$Type' => 'The type of this hyperparameter. The valid types are Integer
, Continuous
, Categorical
, and FreeText
.
An example value of the hyperparameter to optimize using Autotune.
', 'ContinuousParameterRange$MinValue' => 'The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValue
for tuning.
The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue
value and this value for tuning.
The minimum floating-point value allowed.
', 'ContinuousParameterRangeSpecification$MaxValue' => 'The maximum floating-point value allowed.
', 'IntegerParameterRange$MinValue' => 'The minimum value of the hyperparameter to search.
', 'IntegerParameterRange$MaxValue' => 'The maximum value of the hyperparameter to search.
', 'IntegerParameterRangeSpecification$MinValue' => 'The minimum integer value allowed.
', 'IntegerParameterRangeSpecification$MaxValue' => 'The maximum integer value allowed.
', 'ParameterValues$member' => NULL, ], ], 'ParameterValues' => [ 'base' => NULL, 'refs' => [ 'CategoricalParameterRange$Values' => 'A list of the categories for the hyperparameter.
', 'CategoricalParameterRangeSpecification$Values' => 'The allowed categories for the hyperparameter.
', ], ], 'Parent' => [ 'base' => 'The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.
', 'refs' => [ 'Parents$member' => NULL, ], ], 'ParentHyperParameterTuningJob' => [ 'base' => 'A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
', 'refs' => [ 'ParentHyperParameterTuningJobs$member' => NULL, ], ], 'ParentHyperParameterTuningJobs' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningJobWarmStartConfig$ParentHyperParameterTuningJobs' => 'An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
', ], ], 'Parents' => [ 'base' => NULL, 'refs' => [ 'TrialComponent$Parents' => 'An array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.
', ], ], 'PendingDeploymentSummary' => [ 'base' => 'The summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.
', 'refs' => [ 'DescribeEndpointOutput$PendingDeploymentSummary' => 'Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.
', ], ], 'PendingProductionVariantSummary' => [ 'base' => 'The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the VariantStatus
, weight and capacity for a production variant associated with an endpoint.
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.
', 'PendingDeploymentSummary$ShadowProductionVariants' => 'An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants
for the in-progress deployment.
Percentage of devices in the fleet to deploy to the current stage.
', 'ShadowModelVariantConfig$SamplingPercentage' => 'The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant.
', ], ], 'Phase' => [ 'base' => 'Defines the traffic pattern.
', 'refs' => [ 'Phases$member' => NULL, ], ], 'Phases' => [ 'base' => NULL, 'refs' => [ 'TrafficPattern$Phases' => 'Defines the phases traffic specification.
', ], ], 'Pipeline' => [ 'base' => 'A SageMaker Model Building Pipeline instance.
', 'refs' => [ 'SearchRecord$Pipeline' => NULL, ], ], 'PipelineArn' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the created pipeline.
', 'DeletePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline to delete.
', 'DescribePipelineExecutionResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'DescribePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'Pipeline$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'PipelineExecution$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline that was executed.
', 'PipelineSummary$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'UpdatePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the updated pipeline.
', ], ], 'PipelineDefinition' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineDefinition' => 'The JSON pipeline definition of the pipeline.
', 'DescribePipelineDefinitionForExecutionResponse$PipelineDefinition' => 'The JSON pipeline definition.
', 'DescribePipelineResponse$PipelineDefinition' => 'The JSON pipeline definition.
', 'UpdatePipelineRequest$PipelineDefinition' => 'The JSON pipeline definition.
', ], ], 'PipelineDefinitionS3Location' => [ 'base' => 'The location of the pipeline definition stored in Amazon S3.
', 'refs' => [ 'CreatePipelineRequest$PipelineDefinitionS3Location' => 'The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
', 'UpdatePipelineRequest$PipelineDefinitionS3Location' => 'The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
', ], ], 'PipelineDescription' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineDescription' => 'A description of the pipeline.
', 'DescribePipelineResponse$PipelineDescription' => 'The description of the pipeline.
', 'Pipeline$PipelineDescription' => 'The description of the pipeline.
', 'PipelineSummary$PipelineDescription' => 'The description of the pipeline.
', 'UpdatePipelineRequest$PipelineDescription' => 'The description of the pipeline.
', ], ], 'PipelineExecution' => [ 'base' => 'An execution of a pipeline.
', 'refs' => [ 'SearchRecord$PipelineExecution' => NULL, ], ], 'PipelineExecutionArn' => [ 'base' => NULL, 'refs' => [ 'CacheHitResult$SourcePipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineDefinitionForExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'ListPipelineExecutionStepsRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'ListPipelineParametersForExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'PipelineExecution$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'RetryPipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'RetryPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'SelectiveExecutionConfig$SourcePipelineExecutionArn' => 'The ARN from a reference execution of the current pipeline. Used to copy input collaterals needed for the selected steps to run. The execution status of the pipeline can be either Failed
or Success
.
This field is required if the steps you specify for SelectedSteps
depend on output collaterals from any non-specified pipeline steps. For more information, see Selective Execution for Pipeline Steps.
The ARN from an execution of the current pipeline.
', 'SendPipelineExecutionStepFailureResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'SendPipelineExecutionStepSuccessResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StartPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StopPipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StopPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'UpdatePipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the updated pipeline execution.
', ], ], 'PipelineExecutionDescription' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'PipelineExecution$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'StartPipelineExecutionRequest$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionDescription' => 'The description of the pipeline execution.
', ], ], 'PipelineExecutionFailureReason' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$FailureReason' => 'If the execution failed, a message describing why.
', 'PipelineExecution$FailureReason' => 'If the execution failed, a message describing why.
', ], ], 'PipelineExecutionName' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'PipelineExecution$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'StartPipelineExecutionRequest$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', ], ], 'PipelineExecutionStatus' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionStatus' => 'The status of the pipeline execution.
', 'PipelineExecution$PipelineExecutionStatus' => 'The status of the pipeline status.
', 'PipelineExecutionSummary$PipelineExecutionStatus' => 'The status of the pipeline execution.
', ], ], 'PipelineExecutionStep' => [ 'base' => 'An execution of a step in a pipeline.
', 'refs' => [ 'PipelineExecutionStepList$member' => NULL, ], ], 'PipelineExecutionStepList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineExecutionStepsResponse$PipelineExecutionSteps' => 'A list of PipeLineExecutionStep
objects. Each PipeLineExecutionStep
consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.
Metadata for a step execution.
', 'refs' => [ 'PipelineExecutionStep$Metadata' => 'Metadata to run the pipeline step.
', ], ], 'PipelineExecutionSummary' => [ 'base' => 'A pipeline execution summary.
', 'refs' => [ 'PipelineExecutionSummaryList$member' => NULL, ], ], 'PipelineExecutionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineExecutionsResponse$PipelineExecutionSummaries' => 'Contains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.
', ], ], 'PipelineExperimentConfig' => [ 'base' => 'Specifies the names of the experiment and trial created by a pipeline.
', 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExperimentConfig' => NULL, 'PipelineExecution$PipelineExperimentConfig' => NULL, ], ], 'PipelineName' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineName' => 'The name of the pipeline.
', 'CreatePipelineRequest$PipelineDisplayName' => 'The display name of the pipeline.
', 'DeletePipelineRequest$PipelineName' => 'The name of the pipeline to delete.
', 'DescribePipelineResponse$PipelineName' => 'The name of the pipeline.
', 'DescribePipelineResponse$PipelineDisplayName' => 'The display name of the pipeline.
', 'ListPipelinesRequest$PipelineNamePrefix' => 'The prefix of the pipeline name.
', 'Pipeline$PipelineName' => 'The name of the pipeline.
', 'Pipeline$PipelineDisplayName' => 'The display name of the pipeline.
', 'PipelineSummary$PipelineName' => 'The name of the pipeline.
', 'PipelineSummary$PipelineDisplayName' => 'The display name of the pipeline.
', 'UpdatePipelineRequest$PipelineName' => 'The name of the pipeline to update.
', 'UpdatePipelineRequest$PipelineDisplayName' => 'The display name of the pipeline.
', ], ], 'PipelineNameOrArn' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline to describe.
', 'ListPipelineExecutionsRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline.
', 'StartPipelineExecutionRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline.
', ], ], 'PipelineParameterName' => [ 'base' => NULL, 'refs' => [ 'Parameter$Name' => 'The name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.
', ], ], 'PipelineStatus' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineResponse$PipelineStatus' => 'The status of the pipeline execution.
', 'Pipeline$PipelineStatus' => 'The status of the pipeline.
', ], ], 'PipelineSummary' => [ 'base' => 'A summary of a pipeline.
', 'refs' => [ 'PipelineSummaryList$member' => NULL, ], ], 'PipelineSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListPipelinesResponse$PipelineSummaries' => 'Contains a sorted list of PipelineSummary
objects matching the specified filters. Each PipelineSummary
consists of PipelineArn, PipelineName, ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and RoleArn. This list can be empty.
The platform identifier of the notebook instance runtime environment.
', 'DescribeNotebookInstanceOutput$PlatformIdentifier' => 'The platform identifier of the notebook instance runtime environment.
', ], ], 'PolicyString' => [ 'base' => NULL, 'refs' => [ 'GetModelPackageGroupPolicyOutput$ResourcePolicy' => 'The resource policy for the model group.
', 'PutModelPackageGroupPolicyInput$ResourcePolicy' => 'The resource policy for the model group.
', ], ], 'PredefinedMetricSpecification' => [ 'base' => 'A specification for a predefined metric.
', 'refs' => [ 'MetricSpecification$Predefined' => 'Information about a predefined metric.
', ], ], 'PresignedDomainUrl' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlResponse$AuthorizedUrl' => 'The presigned URL.
', ], ], 'ProbabilityThresholdAttribute' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$ProbabilityThresholdAttribute' => 'The threshold for the class probability to be evaluated as a positive result.
', 'EndpointInput$ProbabilityThresholdAttribute' => 'The threshold for the class probability to be evaluated as a positive result.
', ], ], 'ProblemType' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobRequest$ProblemType' => 'Defines the type of supervised learning problem available for the candidates. For more information, see Amazon SageMaker Autopilot problem types.
', 'DescribeAutoMLJobResponse$ProblemType' => 'Returns the job\'s problem type.
', 'ResolvedAttributes$ProblemType' => 'The problem type.
', 'TabularJobConfig$ProblemType' => 'The type of supervised learning problem available for the model candidates of the AutoML job V2. For more information, see Amazon SageMaker Autopilot problem types.
You must either specify the type of supervised learning problem in ProblemType
and provide the AutoMLJobObjective metric, or none at all.
The type of supervised learning problem available for the model candidates of the AutoML job V2 (Binary Classification, Multiclass Classification, Regression). For more information, see Amazon SageMaker Autopilot problem types.
', ], ], 'ProcessingClusterConfig' => [ 'base' => 'Configuration for the cluster used to run a processing job.
', 'refs' => [ 'ProcessingResources$ClusterConfig' => 'The configuration for the resources in a cluster used to run the processing job.
', ], ], 'ProcessingEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'MonitoringEnvironmentMap$key' => NULL, 'ProcessingEnvironmentMap$key' => NULL, ], ], 'ProcessingEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobRequest$Environment' => 'The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.
', 'DescribeProcessingJobResponse$Environment' => 'The environment variables set in the Docker container.
', 'ProcessingJob$Environment' => 'Sets the environment variables in the Docker container.
', ], ], 'ProcessingEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'MonitoringEnvironmentMap$value' => NULL, 'ProcessingEnvironmentMap$value' => NULL, ], ], 'ProcessingFeatureStoreOutput' => [ 'base' => 'Configuration for processing job outputs in Amazon SageMaker Feature Store.
', 'refs' => [ 'ProcessingOutput$FeatureStoreOutput' => 'Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when AppManaged
is specified.
The inputs for a processing job. The processing input must specify exactly one of either S3Input
or DatasetDefinition
types.
An array of inputs configuring the data to download into the processing container.
', 'DescribeProcessingJobResponse$ProcessingInputs' => 'The inputs for a processing job.
', 'ProcessingJob$ProcessingInputs' => 'List of input configurations for the processing job.
', ], ], 'ProcessingInstanceCount' => [ 'base' => NULL, 'refs' => [ 'MonitoringClusterConfig$InstanceCount' => 'The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
', 'ProcessingClusterConfig$InstanceCount' => 'The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
', ], ], 'ProcessingInstanceType' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$InstanceType' => 'The instance type to deploy a custom rule for debugging a training job.
', 'MonitoringClusterConfig$InstanceType' => 'The ML compute instance type for the processing job.
', 'ProcessingClusterConfig$InstanceType' => 'The ML compute instance type for the processing job.
', 'ProfilerRuleConfiguration$InstanceType' => 'The instance type to deploy a custom rule for profiling a training job.
', ], ], 'ProcessingJob' => [ 'base' => 'An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
', 'refs' => [ 'TrialComponentSourceDetail$ProcessingJob' => 'Information about a processing job that\'s the source of a trial component.
', ], ], 'ProcessingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobResponse$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'DebugRuleEvaluationStatus$RuleEvaluationJobArn' => 'The Amazon Resource Name (ARN) of the rule evaluation job.
', 'DescribeProcessingJobResponse$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'MonitoringExecutionSummary$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the monitoring job.
', 'ProcessingJob$ProcessingJobArn' => 'The ARN of the processing job.
', 'ProcessingJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'ProcessingJobSummary$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job..
', 'ProfilerRuleEvaluationStatus$RuleEvaluationJobArn' => 'The Amazon Resource Name (ARN) of the rule evaluation job.
', ], ], 'ProcessingJobName' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobRequest$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DataQualityBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the data quality monitoring job.
', 'DescribeProcessingJobRequest$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeProcessingJobResponse$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'ModelBiasBaselineConfig$BaseliningJobName' => 'The name of the baseline model bias job.
', 'ModelExplainabilityBaselineConfig$BaseliningJobName' => 'The name of the baseline model explainability job.
', 'ModelQualityBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the monitoring job.
', 'MonitoringBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the monitoring job.
', 'ProcessingJob$ProcessingJobName' => 'The name of the processing job.
', 'ProcessingJobSummary$ProcessingJobName' => 'The name of the processing job.
', 'StopProcessingJobRequest$ProcessingJobName' => 'The name of the processing job to stop.
', ], ], 'ProcessingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeProcessingJobResponse$ProcessingJobStatus' => 'Provides the status of a processing job.
', 'ListProcessingJobsRequest$StatusEquals' => 'A filter that retrieves only processing jobs with a specific status.
', 'ProcessingJob$ProcessingJobStatus' => 'The status of the processing job.
', 'ProcessingJobSummary$ProcessingJobStatus' => 'The status of the processing job.
', ], ], 'ProcessingJobStepMetadata' => [ 'base' => 'Metadata for a processing job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$ProcessingJob' => 'The Amazon Resource Name (ARN) of the processing job that was run by this step execution.
', ], ], 'ProcessingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListProcessingJobsResponse$ProcessingJobSummaries' => 'An array of ProcessingJobSummary
objects, each listing a processing job.
Summary of information about a processing job.
', 'refs' => [ 'ProcessingJobSummaries$member' => NULL, ], ], 'ProcessingLocalPath' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$LocalPath' => 'Path to the filesystem where the batch transform data is available to the container.
', 'DatasetDefinition$LocalPath' => 'The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath
is an absolute path to the input data. This is a required parameter when AppManaged
is False
(default).
Path to the filesystem where the endpoint data is available to the container.
', 'MonitoringS3Output$LocalPath' => 'The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
', 'ProcessingS3Input$LocalPath' => 'The local path in your container where you want Amazon SageMaker to write input data to. LocalPath
is an absolute path to the input data and must begin with /opt/ml/processing/
. LocalPath
is a required parameter when AppManaged
is False
(default).
The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath
is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container\'s entrypoint is invoked.
Specifies the maximum runtime in seconds.
', ], ], 'ProcessingOutput' => [ 'base' => 'Describes the results of a processing job. The processing output must specify exactly one of either S3Output
or FeatureStoreOutput
types.
Configuration for uploading output from the processing container.
', 'refs' => [ 'CreateProcessingJobRequest$ProcessingOutputConfig' => 'Output configuration for the processing job.
', 'DescribeProcessingJobResponse$ProcessingOutputConfig' => 'Output configuration for the processing job.
', 'ProcessingJob$ProcessingOutputConfig' => NULL, ], ], 'ProcessingOutputs' => [ 'base' => NULL, 'refs' => [ 'ProcessingOutputConfig$Outputs' => 'An array of outputs configuring the data to upload from the processing container.
', ], ], 'ProcessingResources' => [ 'base' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'refs' => [ 'CreateProcessingJobRequest$ProcessingResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'DescribeProcessingJobResponse$ProcessingResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'ProcessingJob$ProcessingResources' => NULL, ], ], 'ProcessingS3CompressionType' => [ 'base' => NULL, 'refs' => [ 'ProcessingS3Input$S3CompressionType' => 'Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip
can only be used when Pipe
mode is specified as the S3InputMode
. In Pipe
mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicated
Whether input data distributed in Amazon S3 is fully replicated or sharded by an Amazon S3 key. Defaults to FullyReplicated
Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated
, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
Whether you use an S3Prefix
or a ManifestFile
for the data type. If you choose S3Prefix
, S3Uri
identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile
, S3Uri
identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
Configuration for downloading input data from Amazon S3 into the processing container.
', 'refs' => [ 'ProcessingInput$S3Input' => 'Configuration for downloading input data from Amazon S3 into the processing container.
', ], ], 'ProcessingS3InputMode' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$S3InputMode' => 'Whether the Pipe
or File
is used as the input mode for transferring data for the monitoring job. Pipe
mode is recommended for large datasets. File
mode is useful for small files that fit in memory. Defaults to File
.
Whether the Pipe
or File
is used as the input mode for transferring data for the monitoring job. Pipe
mode is recommended for large datasets. File
mode is useful for small files that fit in memory. Defaults to File
.
Whether to use File
or Pipe
input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe
mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.
Configuration for uploading output data to Amazon S3 from the processing container.
', 'refs' => [ 'ProcessingOutput$S3Output' => 'Configuration for processing job outputs in Amazon S3.
', ], ], 'ProcessingS3UploadMode' => [ 'base' => NULL, 'refs' => [ 'MonitoringS3Output$S3UploadMode' => 'Whether to upload the results of the monitoring job continuously or after the job completes.
', 'ProcessingS3Output$S3UploadMode' => 'Whether to upload the results of the processing job continuously or after the job completes.
', ], ], 'ProcessingStoppingCondition' => [ 'base' => 'Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
', 'refs' => [ 'CreateProcessingJobRequest$StoppingCondition' => 'The time limit for how long the processing job is allowed to run.
', 'DescribeProcessingJobResponse$StoppingCondition' => 'The time limit for how long the processing job is allowed to run.
', 'ProcessingJob$StoppingCondition' => NULL, ], ], 'ProcessingVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'MonitoringClusterConfig$VolumeSizeInGB' => 'The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
', 'ProcessingClusterConfig$VolumeSizeInGB' => 'The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
Certain Nitro-based instances include local storage with a fixed total size, dependent on the instance type. When using these instances for processing, Amazon SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage. You can\'t request a VolumeSizeInGB
greater than the total size of the local instance storage.
For a list of instance types that support local instance storage, including the total size per instance type, see Instance Store Volumes.
Indicates CPU or GPU compatibility.
CPU
: The image version is compatible with CPU.
GPU
: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU
: The image version is compatible with CPU.
GPU
: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU
: The image version is compatible with CPU.
GPU
: The image version is compatible with GPU.
The product identifier of the algorithm.
', 'ModelPackageContainerDefinition$ProductId' => 'The Amazon Web Services Marketplace product ID of the model package.
', ], ], 'ProductListings' => [ 'base' => NULL, 'refs' => [ 'Workteam$ProductListingIds' => 'The Amazon Marketplace identifier for a vendor\'s work team.
', ], ], 'ProductionVariant' => [ 'base' => 'Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
', 'refs' => [ 'ProductionVariantList$member' => NULL, ], ], 'ProductionVariantAcceleratorType' => [ 'base' => NULL, 'refs' => [ 'PendingProductionVariantSummary$AcceleratorType' => 'The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'ProductionVariant$AcceleratorType' => 'The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
', ], ], 'ProductionVariantContainerStartupHealthCheckTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentStartupParameters$ContainerStartupHealthCheckTimeoutInSeconds' => 'The timeout value, in seconds, for your inference container to pass health check by Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
', 'ProductionVariant$ContainerStartupHealthCheckTimeoutInSeconds' => 'The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
', ], ], 'ProductionVariantCoreDumpConfig' => [ 'base' => 'Specifies configuration for a core dump from the model container when the process crashes.
', 'refs' => [ 'ProductionVariant$CoreDumpConfig' => 'Specifies configuration for a core dump from the model container when the process crashes.
', ], ], 'ProductionVariantInstanceType' => [ 'base' => NULL, 'refs' => [ 'EndpointInputConfiguration$InstanceType' => 'The instance types to use for the load test.
', 'EndpointOutputConfiguration$InstanceType' => 'The instance type recommended by Amazon SageMaker Inference Recommender.
', 'PendingProductionVariantSummary$InstanceType' => 'The type of instances associated with the variant.
', 'ProductionVariant$InstanceType' => 'The ML compute instance type.
', 'RealTimeInferenceRecommendation$InstanceType' => 'The recommended instance type for Real-Time Inference.
', 'RealtimeInferenceInstanceTypes$member' => NULL, ], ], 'ProductionVariantList' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigInput$ProductionVariants' => 'An array of ProductionVariant
objects, one for each model that you want to host at this endpoint.
An array of ProductionVariant
objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants
. If you use this field, you can only specify one variant for ProductionVariants
and one variant for ShadowProductionVariants
.
An array of ProductionVariant
objects, one for each model that you want to host at this endpoint.
An array of ProductionVariant
objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants
.
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
', 'refs' => [ 'PendingProductionVariantSummary$ManagedInstanceScaling' => 'Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
', 'ProductionVariant$ManagedInstanceScaling' => 'Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
', 'ProductionVariantSummary$ManagedInstanceScaling' => 'Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
', ], ], 'ProductionVariantModelDataDownloadTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentStartupParameters$ModelDataDownloadTimeoutInSeconds' => 'The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this inference component.
', 'ProductionVariant$ModelDataDownloadTimeoutInSeconds' => 'The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
', ], ], 'ProductionVariantRoutingConfig' => [ 'base' => 'Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
', 'refs' => [ 'PendingProductionVariantSummary$RoutingConfig' => 'Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
', 'ProductionVariant$RoutingConfig' => 'Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
', 'ProductionVariantSummary$RoutingConfig' => 'Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
', ], ], 'ProductionVariantSSMAccess' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$EnableSSMAccess' => ' You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint
.
Specifies the serverless configuration for an endpoint variant.
', 'refs' => [ 'EndpointInputConfiguration$ServerlessConfig' => NULL, 'EndpointOutputConfiguration$ServerlessConfig' => NULL, 'PendingProductionVariantSummary$CurrentServerlessConfig' => 'The serverless configuration for the endpoint.
', 'PendingProductionVariantSummary$DesiredServerlessConfig' => 'The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.
', 'ProductionVariant$ServerlessConfig' => 'The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
', 'ProductionVariantSummary$CurrentServerlessConfig' => 'The serverless configuration for the endpoint.
', 'ProductionVariantSummary$DesiredServerlessConfig' => 'The serverless configuration requested for the endpoint update.
', ], ], 'ProductionVariantServerlessUpdateConfig' => [ 'base' => 'Specifies the serverless update concurrency configuration for an endpoint variant.
', 'refs' => [ 'DesiredWeightAndCapacity$ServerlessUpdateConfig' => 'Specifies the serverless update concurrency configuration for an endpoint variant.
', ], ], 'ProductionVariantStatus' => [ 'base' => 'Describes the status of the production variant.
', 'refs' => [ 'ProductionVariantStatusList$member' => NULL, ], ], 'ProductionVariantStatusList' => [ 'base' => NULL, 'refs' => [ 'PendingProductionVariantSummary$VariantStatus' => 'The endpoint variant status which describes the current deployment stage status or operational status.
', 'ProductionVariantSummary$VariantStatus' => 'The endpoint variant status which describes the current deployment stage status or operational status.
', ], ], 'ProductionVariantSummary' => [ 'base' => 'Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities
API and the endpoint status is Updating
, you get different desired and current values.
An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
', 'DescribeEndpointOutput$ShadowProductionVariants' => 'An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants
.
A list of the production variants hosted on the endpoint. Each production variant is a model.
', 'Endpoint$ShadowProductionVariants' => 'A list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the production variant.
', ], ], 'ProductionVariantVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
', ], ], 'ProfilerConfig' => [ 'base' => 'Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
', 'refs' => [ 'CreateTrainingJobRequest$ProfilerConfig' => NULL, 'DescribeTrainingJobResponse$ProfilerConfig' => NULL, 'TrainingJob$ProfilerConfig' => NULL, ], ], 'ProfilerConfigForUpdate' => [ 'base' => 'Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and storage paths.
', 'refs' => [ 'UpdateTrainingJobRequest$ProfilerConfig' => 'Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
', ], ], 'ProfilerRuleConfiguration' => [ 'base' => 'Configuration information for profiling rules.
', 'refs' => [ 'ProfilerRuleConfigurations$member' => NULL, ], ], 'ProfilerRuleConfigurations' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', 'DescribeTrainingJobResponse$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', 'UpdateTrainingJobRequest$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', ], ], 'ProfilerRuleEvaluationStatus' => [ 'base' => 'Information about the status of the rule evaluation.
', 'refs' => [ 'ProfilerRuleEvaluationStatuses$member' => NULL, ], ], 'ProfilerRuleEvaluationStatuses' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$ProfilerRuleEvaluationStatuses' => 'Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
', ], ], 'ProfilingIntervalInMilliseconds' => [ 'base' => NULL, 'refs' => [ 'ProfilerConfig$ProfilingIntervalInMilliseconds' => 'A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
', 'ProfilerConfigForUpdate$ProfilingIntervalInMilliseconds' => 'A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
', ], ], 'ProfilingParameters' => [ 'base' => NULL, 'refs' => [ 'ProfilerConfig$ProfilingParameters' => 'Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig
, PythonProfilingConfig
, and DataLoaderProfilingConfig
. The following codes are configuration structures for the ProfilingParameters
parameter. To learn more about how to configure the ProfilingParameters
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig
, PythonProfilingConfig
, and DataLoaderProfilingConfig
. The following codes are configuration structures for the ProfilingParameters
parameter. To learn more about how to configure the ProfilingParameters
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Profiling status of a training job.
', ], ], 'ProgrammingLang' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ProgrammingLang' => 'The supported programming language and its version.
', 'DescribeImageVersionResponse$ProgrammingLang' => 'The supported programming language and its version.
', 'UpdateImageVersionRequest$ProgrammingLang' => 'The supported programming language and its version.
', ], ], 'Project' => [ 'base' => 'The properties of a project as returned by the Search API.
', 'refs' => [ 'SearchRecord$Project' => 'The properties of a project.
', ], ], 'ProjectArn' => [ 'base' => NULL, 'refs' => [ 'CreateProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'DescribeProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'Project$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'ProjectSummary$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'UpdateProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', ], ], 'ProjectEntityName' => [ 'base' => NULL, 'refs' => [ 'CreateProjectInput$ProjectName' => 'The name of the project.
', 'DeleteProjectInput$ProjectName' => 'The name of the project to delete.
', 'DescribeProjectInput$ProjectName' => 'The name of the project to describe.
', 'DescribeProjectOutput$ProjectName' => 'The name of the project.
', 'ListProjectsInput$NameContains' => 'A filter that returns the projects whose name contains a specified string.
', 'Project$ProjectName' => 'The name of the project.
', 'ProjectSummary$ProjectName' => 'The name of the project.
', 'UpdateProjectInput$ProjectName' => 'The name of the project.
', ], ], 'ProjectId' => [ 'base' => NULL, 'refs' => [ 'CreateProjectOutput$ProjectId' => 'The ID of the new project.
', 'DescribeProjectOutput$ProjectId' => 'The ID of the project.
', 'Project$ProjectId' => 'The ID of the project.
', 'ProjectSummary$ProjectId' => 'The ID of the project.
', ], ], 'ProjectSortBy' => [ 'base' => NULL, 'refs' => [ 'ListProjectsInput$SortBy' => 'The field by which to sort results. The default is CreationTime
.
The sort order for results. The default is Ascending
.
The status of the project.
', 'Project$ProjectStatus' => 'The status of the project.
', 'ProjectSummary$ProjectStatus' => 'The status of the project.
', ], ], 'ProjectSummary' => [ 'base' => 'Information about a project.
', 'refs' => [ 'ProjectSummaryList$member' => NULL, ], ], 'ProjectSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListProjectsOutput$ProjectSummaryList' => 'A list of summaries of projects.
', ], ], 'PropertyNameHint' => [ 'base' => NULL, 'refs' => [ 'PropertyNameQuery$PropertyNameHint' => 'Text that begins a property\'s name.
', ], ], 'PropertyNameQuery' => [ 'base' => 'Part of the SuggestionQuery
type. Specifies a hint for retrieving property names that begin with the specified text.
Defines a property name hint. Only property names that begin with the specified hint are included in the response.
', ], ], 'PropertyNameSuggestion' => [ 'base' => 'A property name returned from a GetSearchSuggestions
call that specifies a value in the PropertyNameQuery
field.
A list of property names for a Resource
that match a SuggestionQuery
.
The current status of the product.
AVAILABLE
- Stable state, ready to perform any operation. The most recent operation succeeded and completed.
UNDER_CHANGE
- Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations.
TAINTED
- Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version.
ERROR
- An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack.
PLAN_IN_PROGRESS
- Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
A key value pair used when you provision a project as a service catalog product. For information, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'ProvisioningParameters$member' => NULL, ], ], 'ProvisioningParameterKey' => [ 'base' => NULL, 'refs' => [ 'ProvisioningParameter$Key' => 'The key that identifies a provisioning parameter.
', ], ], 'ProvisioningParameterValue' => [ 'base' => NULL, 'refs' => [ 'ProvisioningParameter$Value' => 'The value of the provisioning parameter.
', ], ], 'ProvisioningParameters' => [ 'base' => NULL, 'refs' => [ 'ServiceCatalogProvisioningDetails$ProvisioningParameters' => 'A list of key value pairs that you specify when you provision a product.
', 'ServiceCatalogProvisioningUpdateDetails$ProvisioningParameters' => 'A list of key value pairs that you specify when you provision a product.
', ], ], 'PublicWorkforceTaskPrice' => [ 'base' => 'Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
0.012
0.024
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
0.840
0.960
1.080
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
2.400
2.280
2.160
2.040
1.920
1.800
1.680
1.560
1.440
1.320
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
The price that you pay for each task performed by an Amazon Mechanical Turk worker.
', ], ], 'PutModelPackageGroupPolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'PutModelPackageGroupPolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'QualityCheckStepMetadata' => [ 'base' => 'Container for the metadata for a Quality check step. For more information, see the topic on QualityCheck step in the Amazon SageMaker Developer Guide.
', 'refs' => [ 'PipelineExecutionStepMetadata$QualityCheck' => 'The configurations and outcomes of the check step execution. This includes:
The type of the check conducted.
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The Boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck
is set the same as CalculatedBaseline
.
A set of filters to narrow the set of lineage entities connected to the StartArn
(s) returned by the QueryLineage
API action.
A set of filtering parameters that allow you to specify which entities should be returned.
Properties - Key-value pairs to match on the lineage entities\' properties.
LineageTypes - A set of lineage entity types to match on. For example: TrialComponent
, Artifact
, or Context
.
CreatedBefore - Filter entities created before this date.
ModifiedBefore - Filter entities modified before this date.
ModifiedAfter - Filter entities modified after this date.
The maximum depth in lineage relationships from the StartArns
that are traversed. Depth is a measure of the number of Associations
from the StartArn
entity to the matched results.
Limits the number of vertices in the results. Use the NextToken
in a response to to retrieve the next page of results.
A list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.
', ], ], 'QueryLineageTypes' => [ 'base' => NULL, 'refs' => [ 'QueryFilters$LineageTypes' => 'Filter the lineage entities connected to the StartArn
(s) by the type of the lineage entity.
Filter the lineage entities connected to the StartArn
(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.
Filter the lineage entities connected to the StartArn
by type. For example: DataSet
, Model
, Endpoint
, or ModelDeployment
.
A collection of settings that apply to an RSessionGateway
app.
A collection of settings that configure the RSessionGateway
app.
Indicates whether the current user has access to the RStudioServerPro
app.
A collection of settings that configure user interaction with the RStudioServerPro
app.
A collection of settings that configure user interaction with the RStudioServerPro
app.
A collection of settings that configure the RStudioServerPro
Domain-level app.
A collection of settings that configure the RStudioServerPro
Domain-level app.
A collection of settings that update the current configuration for the RStudioServerPro
Domain-level app.
A collection of RStudioServerPro
Domain-level app settings to update. A single RStudioServerPro
application is created for a domain.
The level of permissions that the user has within the RStudioServerPro
app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.
A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.
', ], ], 'RealTimeInferenceConfig' => [ 'base' => 'The infrastructure configuration for deploying the model to a real-time inference endpoint.
', 'refs' => [ 'ModelInfrastructureConfig$RealTimeInferenceConfig' => 'The infrastructure configuration for deploying the model to real-time inference.
', ], ], 'RealTimeInferenceRecommendation' => [ 'base' => 'The recommended configuration to use for Real-Time Inference.
', 'refs' => [ 'RealTimeInferenceRecommendations$member' => NULL, ], ], 'RealTimeInferenceRecommendations' => [ 'base' => NULL, 'refs' => [ 'DeploymentRecommendation$RealTimeInferenceRecommendations' => 'A list of RealTimeInferenceRecommendation items.
', ], ], 'RealtimeInferenceInstanceTypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedRealtimeInferenceInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
', 'InferenceSpecification$SupportedRealtimeInferenceInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
This parameter is required for unversioned models, and optional for versioned models.
', ], ], 'RecommendationFailureReason' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInferenceBenchmark$FailureReason' => 'The reason why a benchmark failed.
', ], ], 'RecommendationJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobResponse$JobArn' => 'The Amazon Resource Name (ARN) of the recommendation job.
', 'DescribeInferenceRecommendationsJobResponse$JobArn' => 'The Amazon Resource Name (ARN) of the job.
', 'InferenceRecommendationsJob$JobArn' => 'The Amazon Resource Name (ARN) of the recommendation job.
', ], ], 'RecommendationJobCompilationJobName' => [ 'base' => NULL, 'refs' => [ 'ModelConfiguration$CompilationJobName' => 'The name of the compilation job used to create the recommended model artifacts.
', ], ], 'RecommendationJobCompiledOutputConfig' => [ 'base' => 'Provides information about the output configuration for the compiled model.
', 'refs' => [ 'RecommendationJobOutputConfig$CompiledOutputConfig' => 'Provides information about the output configuration for the compiled model.
', ], ], 'RecommendationJobContainerConfig' => [ 'base' => 'Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig
override the corresponding fields in the model package. Use ContainerConfig
if you want to specify these fields for the recommendation job but don\'t want to edit them in your model package.
Specifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig
override the corresponding fields in the model package.
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.
', ], ], 'RecommendationJobDescription' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobDescription' => 'Description of the recommendation job.
', 'DescribeInferenceRecommendationsJobResponse$JobDescription' => 'The job description that you provided when you initiated the job.
', 'InferenceRecommendationsJob$JobDescription' => 'The job description.
', ], ], 'RecommendationJobFrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$FrameworkVersion' => 'The framework version of the container image.
', ], ], 'RecommendationJobInferenceBenchmark' => [ 'base' => 'The details for a specific benchmark from an Inference Recommender job.
', 'refs' => [ 'InferenceRecommendationsJobStep$InferenceBenchmark' => 'The details for a specific benchmark.
', ], ], 'RecommendationJobInputConfig' => [ 'base' => 'The input configuration of the recommendation job.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$InputConfig' => 'Provides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.
', 'DescribeInferenceRecommendationsJobResponse$InputConfig' => 'Returns information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations you provided when you initiated the job.
', ], ], 'RecommendationJobName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobName' => 'A name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account. The job name is passed down to the resources created by the recommendation job. The names of resources (such as the model, endpoint configuration, endpoint, and compilation) that are prefixed with the job name are truncated at 40 characters.
', 'DescribeInferenceRecommendationsJobRequest$JobName' => 'The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeInferenceRecommendationsJobResponse$JobName' => 'The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'GetScalingConfigurationRecommendationRequest$InferenceRecommendationsJobName' => 'The name of a previously completed Inference Recommender job.
', 'GetScalingConfigurationRecommendationResponse$InferenceRecommendationsJobName' => 'The name of a previously completed Inference Recommender job.
', 'InferenceRecommendationsJob$JobName' => 'The name of the job.
', 'InferenceRecommendationsJobStep$JobName' => 'The name of the Inference Recommender job.
', 'ListInferenceRecommendationsJobStepsRequest$JobName' => 'The name for the Inference Recommender job.
', 'StopInferenceRecommendationsJobRequest$JobName' => 'The name of the job you want to stop.
', ], ], 'RecommendationJobOutputConfig' => [ 'base' => 'Provides information about the output configuration for the compiled model.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$OutputConfig' => 'Provides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.
', ], ], 'RecommendationJobPayloadConfig' => [ 'base' => 'The configuration for the payload for a recommendation job.
', 'refs' => [ 'RecommendationJobContainerConfig$PayloadConfig' => 'Specifies the SamplePayloadUrl
and all other sample payload-related fields.
Specifies the maximum number of jobs that can run in parallel and the maximum number of jobs that can run.
', 'refs' => [ 'RecommendationJobInputConfig$ResourceLimit' => 'Defines the resource limit of the job.
', ], ], 'RecommendationJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$Status' => 'The status of the job.
', 'InferenceRecommendationsJob$Status' => 'The status of the job.
', 'InferenceRecommendationsJobStep$Status' => 'The current status of the benchmark.
', 'ListInferenceRecommendationsJobStepsRequest$Status' => 'A filter to return benchmarks of a specified status. If this field is left empty, then all benchmarks are returned.
', 'ListInferenceRecommendationsJobsRequest$StatusEquals' => 'A filter that retrieves only inference recommendations jobs with a specific status.
', ], ], 'RecommendationJobStoppingConditions' => [ 'base' => 'Specifies conditions for stopping a job. When a job reaches a stopping condition limit, SageMaker ends the job.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$StoppingConditions' => 'A set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.
', 'DescribeInferenceRecommendationsJobResponse$StoppingConditions' => 'The stopping conditions that you provided when you initiated the job.
', ], ], 'RecommendationJobSupportedContentType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobSupportedContentTypes$member' => NULL, ], ], 'RecommendationJobSupportedContentTypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobPayloadConfig$SupportedContentTypes' => 'The supported MIME types for the input data.
', ], ], 'RecommendationJobSupportedEndpointType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedEndpointType' => 'The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
', ], ], 'RecommendationJobSupportedInstanceTypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
', ], ], 'RecommendationJobSupportedResponseMIMEType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobSupportedResponseMIMETypes$member' => NULL, ], ], 'RecommendationJobSupportedResponseMIMETypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', ], ], 'RecommendationJobType' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobType' => 'Defines the type of recommendation job. Specify Default
to initiate an instance recommendation and Advanced
to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT
) job.
The job type that you provided when you initiated the job.
', 'InferenceRecommendationsJob$JobType' => 'The recommendation job type.
', ], ], 'RecommendationJobVpcConfig' => [ 'base' => 'Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
', 'refs' => [ 'RecommendationJobInputConfig$VpcConfig' => 'Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
', ], ], 'RecommendationJobVpcSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobVpcSecurityGroupIds$member' => NULL, ], ], 'RecommendationJobVpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobVpcConfig$SecurityGroupIds' => 'The VPC security group IDs. IDs have the form of sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in the Subnets
field.
The ID of the subnets in the VPC to which you want to connect your model.
', ], ], 'RecommendationMetrics' => [ 'base' => 'The metrics of recommendations.
', 'refs' => [ 'InferenceRecommendation$Metrics' => 'The metrics used to decide what recommendation to make.
', 'RecommendationJobInferenceBenchmark$Metrics' => NULL, ], ], 'RecommendationStatus' => [ 'base' => NULL, 'refs' => [ 'DeploymentRecommendation$RecommendationStatus' => 'Status of the deployment recommendation. The status NOT_APPLICABLE
means that SageMaker is unable to provide a default recommendation for the model using the information provided. If the deployment status is IN_PROGRESS
, retry your API call after a few seconds to get a COMPLETED
deployment recommendation.
The type of the subtask.
BENCHMARK
: Evaluate the performance of your model on different instance types.
A filter to return details about the specified type of subtask.
BENCHMARK
: Evaluate the performance of your model on different instance types.
Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don\'t need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
', ], ], 'RedshiftClusterId' => [ 'base' => 'The Redshift cluster Identifier.
', 'refs' => [ 'RedshiftDatasetDefinition$ClusterId' => NULL, ], ], 'RedshiftDatabase' => [ 'base' => 'The name of the Redshift database used in Redshift query execution.
', 'refs' => [ 'RedshiftDatasetDefinition$Database' => NULL, ], ], 'RedshiftDatasetDefinition' => [ 'base' => 'Configuration for Redshift Dataset Definition input.
', 'refs' => [ 'DatasetDefinition$RedshiftDatasetDefinition' => NULL, ], ], 'RedshiftQueryString' => [ 'base' => 'The SQL query statements to be executed.
', 'refs' => [ 'RedshiftDatasetDefinition$QueryString' => NULL, ], ], 'RedshiftResultCompressionType' => [ 'base' => 'The compression used for Redshift query results.
', 'refs' => [ 'RedshiftDatasetDefinition$OutputCompression' => NULL, ], ], 'RedshiftResultFormat' => [ 'base' => 'The data storage format for Redshift query results.
', 'refs' => [ 'RedshiftDatasetDefinition$OutputFormat' => NULL, ], ], 'RedshiftUserName' => [ 'base' => 'The database user name used in Redshift query execution.
', 'refs' => [ 'RedshiftDatasetDefinition$DbUser' => NULL, ], ], 'RegisterDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'RegisterModelStepMetadata' => [ 'base' => 'Metadata for a register model job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$RegisterModel' => 'The Amazon Resource Name (ARN) of the model package that the model was registered to by this step execution.
', ], ], 'ReleaseNotes' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ReleaseNotes' => 'The maintainer description of the image version.
', 'DescribeImageVersionResponse$ReleaseNotes' => 'The maintainer description of the image version.
', 'UpdateImageVersionRequest$ReleaseNotes' => 'The maintainer description of the image version.
', ], ], 'RemoteDebugConfig' => [ 'base' => 'Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
', 'refs' => [ 'CreateTrainingJobRequest$RemoteDebugConfig' => 'Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
', 'DescribeTrainingJobResponse$RemoteDebugConfig' => 'Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
', ], ], 'RemoteDebugConfigForUpdate' => [ 'base' => 'Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
', 'refs' => [ 'UpdateTrainingJobRequest$RemoteDebugConfig' => 'Configuration for remote debugging while the training job is running. You can update the remote debugging configuration when the SecondaryStatus
of the job is Downloading
or Training
.To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
Contains input values for a task.
', 'refs' => [ 'RenderUiTemplateRequest$Task' => 'A RenderableTask
object containing a representative task to render.
A description of an error that occurred while rendering the template.
', 'refs' => [ 'RenderingErrorList$member' => NULL, ], ], 'RenderingErrorList' => [ 'base' => NULL, 'refs' => [ 'RenderUiTemplateResponse$Errors' => 'A list of one or more RenderingError
objects if any were encountered while rendering the template. If there were no errors, the list is empty.
Set this to one of the following values:
Platform
- The model image is hosted in Amazon ECR.
Vpc
- The model image is hosted in a private Docker registry in your VPC.
Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc
as the value for the RepositoryAccessMode
field of the ImageConfig
object that you passed to a call to CreateModel
and the private Docker registry where the model image is hosted requires authentication.
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc
as the value for the RepositoryAccessMode
field, and the private Docker registry where the model image is hosted requires authentication.
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
', ], ], 'RepositoryUrl' => [ 'base' => NULL, 'refs' => [ 'CodeRepository$RepositoryUrl' => 'The URL of the Git repository.
', ], ], 'ResolvedAttributes' => [ 'base' => 'The resolved attributes.
', 'refs' => [ 'DescribeAutoMLJobResponse$ResolvedAttributes' => 'Contains ProblemType
, AutoMLJobObjective
, and CompletionCriteria
. If you do not provide these values, they are inferred.
The Amazon Resource Name (ARN) of the resource that you want to tag.
', 'DeleteTagsInput$ResourceArn' => 'The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
', 'ListTagsInput$ResourceArn' => 'The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
', ], ], 'ResourceCatalog' => [ 'base' => ' A resource catalog containing all of the resources of a specific resource type within a resource owner account. For an example on sharing the Amazon SageMaker Feature Store DefaultFeatureGroupCatalog
, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.
The Amazon Resource Name (ARN) of the ResourceCatalog
.
A free form description of the ResourceCatalog
.
A list of the requested ResourceCatalog
s.
A string that partially matches one or more ResourceCatalog
s names. Filters ResourceCatalog
by name.
The name of the ResourceCatalog
.
The value on which the resource catalog list is sorted.
', ], ], 'ResourceCatalogSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListResourceCatalogsRequest$SortOrder' => 'The order in which the resource catalogs are listed.
', ], ], 'ResourceConfig' => [ 'base' => 'Describes the resources, including machine learning (ML) compute instances and ML storage volumes, to use for model training.
', 'refs' => [ 'CreateTrainingJobRequest$ResourceConfig' => 'The resources, including the ML compute instances and ML storage volumes, to use for model training.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File
as the TrainingInputMode
in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
', 'HyperParameterTrainingJobDefinition$ResourceConfig' => 'The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File
as the TrainingInputMode
in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig
instead.
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
', 'TrainingJobDefinition$ResourceConfig' => 'The resources, including the ML compute instances and ML storage volumes, to use for model training.
', ], ], 'ResourceConfigForUpdate' => [ 'base' => 'The ResourceConfig
to update KeepAlivePeriodInSeconds
. Other fields in the ResourceConfig
cannot be updated.
The training job ResourceConfig
to update warm pool retention length.
The ID of the Amazon Elastic File System (EFS) managed by this Domain.
', ], ], 'ResourceInUse' => [ 'base' => 'Resource being accessed is in use.
', 'refs' => [], ], 'ResourceLimitExceeded' => [ 'base' => 'You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
', 'refs' => [], ], 'ResourceLimits' => [ 'base' => 'Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
', 'refs' => [ 'HyperParameterTuningJobConfig$ResourceLimits' => 'The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$ResourceLimits' => 'The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
', ], ], 'ResourceNotFound' => [ 'base' => 'Resource being access is not found.
', 'refs' => [], ], 'ResourcePolicyString' => [ 'base' => NULL, 'refs' => [ 'GetLineageGroupPolicyResponse$ResourcePolicy' => 'The resource policy that gives access to the lineage group in another account.
', ], ], 'ResourcePropertyName' => [ 'base' => NULL, 'refs' => [ 'Filter$Name' => 'A resource property name. For example, TrainingJobName
. For valid property names, see SearchRecord. You must specify a valid property for the resource.
The name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig
.
A suggested property name based on what you entered in the search textbox in the SageMaker console.
', 'SearchRequest$SortBy' => 'The name of the resource property used to sort the SearchResults
. The default is LastModifiedTime
.
The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time.
Multiply ResourceRetainedBillableTimeInSeconds
by the number of instances (InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: ResourceRetainedBillableTimeInSeconds * InstanceCount
.
Specifies the ARN\'s of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
', 'refs' => [ 'AppDetails$ResourceSpec' => NULL, 'CodeEditorAppSettings$DefaultResourceSpec' => NULL, 'CreateAppRequest$ResourceSpec' => 'The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
The value of InstanceType
passed as part of the ResourceSpec
in the CreateApp
call overrides the value passed as part of the ResourceSpec
configured for the user profile or the domain. If InstanceType
is not specified in any of those three ResourceSpec
values for a KernelGateway
app, the CreateApp
call fails with a request validation error.
The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
', 'JupyterLabAppSettings$DefaultResourceSpec' => NULL, 'JupyterServerAppSettings$DefaultResourceSpec' => 'The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns
parameter, then this parameter is also required.
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
', ], ], 'ResourceType' => [ 'base' => NULL, 'refs' => [ 'GetSearchSuggestionsRequest$Resource' => 'The name of the SageMaker resource to search for.
', 'SearchRequest$Resource' => 'The name of the SageMaker resource to search for.
', ], ], 'ResponseMIMEType' => [ 'base' => NULL, 'refs' => [ 'ResponseMIMETypes$member' => NULL, ], ], 'ResponseMIMETypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', 'InferenceSpecification$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', ], ], 'RetentionPolicy' => [ 'base' => 'The retention policy for data stored on an Amazon Elastic File System (EFS) volume.
', 'refs' => [ 'DeleteDomainRequest$RetentionPolicy' => 'The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).
', ], ], 'RetentionType' => [ 'base' => NULL, 'refs' => [ 'RetentionPolicy$HomeEfsFileSystem' => 'The default is Retain
, which specifies to keep the data stored on the EFS volume.
Specify Delete
to delete the data stored on the EFS volume.
The retry strategy to use when a training job fails due to an InternalServerError
. RetryStrategy
is specified as part of the CreateTrainingJob
and CreateHyperParameterTuningJob
requests. You can add the StoppingCondition
parameter to the request to limit the training time for the complete job.
The number of times to retry the job when the job fails due to an InternalServerError
.
The number of times to retry the job when the job fails due to an InternalServerError
.
The number of times to retry the job when the job fails due to an InternalServerError
.
The number of times to retry the job when the job fails due to an InternalServerError
.
The IAM roles that SageMaker uses to run the training jobs.
', 'ClusterInstanceGroupDetails$ExecutionRole' => 'The execution role for the instance group to assume.
', 'ClusterInstanceGroupSpecification$ExecutionRole' => 'Specifies an IAM execution role to be assumed by the instance group.
', 'CreateAutoMLJobRequest$RoleArn' => 'The ARN of the role that is used to access the data.
', 'CreateAutoMLJobV2Request$RoleArn' => 'The ARN of the role that is used to access the data.
', 'CreateCompilationJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
During model compilation, Amazon SageMaker needs your permission to:
Read input data from an S3 bucket
Write model artifacts to an S3 bucket
Write logs to Amazon CloudWatch Logs
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole
permission. For more information, see Amazon SageMaker Roles.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateDeviceFleetRequest$RoleArn' => 'The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
', 'CreateEdgePackagingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.
', 'CreateEndpointConfigInput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform actions on your behalf. For more information, see SageMaker Roles.
To be able to pass this role to Amazon SageMaker, the caller of this action must have the iam:PassRole
permission.
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore
if an OfflineStoreConfig
is provided.
The Amazon Resource Name (ARN) of the role needed to call other services on your behalf. For example, arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298
.
The ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'CreateInferenceExperimentRequest$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'CreateInferenceRecommendationsJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'CreateLabelingJobRequest$RoleArn' => 'The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
', 'CreateModelBiasJobDefinitionRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateModelExplainabilityJobDefinitionRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateModelInput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateNotebookInstanceInput$RoleArn' => 'When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
The Amazon Resource Name (ARN) of the role used by the pipeline to access and create resources.
', 'CreateProcessingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateTrainingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
The ARN of the execution role for the space.
', 'DescribeAutoMLJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeAutoMLJobV2Response$RoleArn' => 'The ARN of the Identity and Access Management role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeCompilationJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to perform the model compilation job.
', 'DescribeDataQualityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeDeviceFleetResponse$RoleArn' => 'The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
', 'DescribeEdgePackagingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
', 'DescribeEndpointConfigOutput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you assigned to the endpoint configuration.
', 'DescribeFeatureGroupResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
', 'DescribeFlowDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) execution role for the flow definition.
', 'DescribeImageResponse$RoleArn' => 'The ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'DescribeInferenceExperimentResponse$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'DescribeInferenceRecommendationsJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role you provided when you initiated the job.
', 'DescribeLabelingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.
', 'DescribeModelBiasJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeModelExplainabilityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeModelOutput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
', 'DescribeModelQualityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeNotebookInstanceOutput$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role associated with the instance.
', 'DescribePipelineResponse$RoleArn' => 'The Amazon Resource Name (ARN) that the pipeline uses to execute.
', 'DescribeProcessingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeTrainingJobResponse$RoleArn' => 'The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
', 'FeatureGroup$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.
', 'HyperParameterTrainingJobDefinition$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
', 'InferenceExperimentSummary$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'InferenceRecommendationsJob$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'Model$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
', 'ModelPackageValidationSpecification$ValidationRole' => 'The IAM roles to be used for the validation of the model package.
', 'ModelRegisterSettings$CrossAccountModelRegisterRoleArn' => 'The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services account in which SageMaker model registry is set up.
', 'MonitoringJobDefinition$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'Pipeline$RoleArn' => 'The Amazon Resource Name (ARN) of the role that created the pipeline.
', 'PipelineSummary$RoleArn' => 'The Amazon Resource Name (ARN) that the pipeline used to execute.
', 'ProcessingJob$RoleArn' => 'The ARN of the role used to create the processing job.
', 'RStudioServerProDomainSettings$DomainExecutionRoleArn' => 'The ARN of the execution role for the RStudioServerPro
Domain-level app.
The execution role for the RStudioServerPro
Domain-level app.
The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
', 'RenderUiTemplateRequest$RoleArn' => 'The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.
', 'TimeSeriesForecastingSettings$AmazonForecastRoleArn' => 'The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default, Canvas uses the execution role specified in the UserProfile
that launches the Canvas application. If an execution role is not specified in the UserProfile
, Canvas uses the execution role specified in the Domain that owns the UserProfile
. To allow time series forecasting, this IAM role should have the AmazonSageMakerCanvasForecastAccess policy attached and forecast.amazonaws.com
added in the trust relationship as a service principal.
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
', 'UpdateDeviceFleetRequest$RoleArn' => 'The Amazon Resource Name (ARN) of the device.
', 'UpdateImageRequest$RoleArn' => 'The new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'UpdateNotebookInstanceInput$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
The Amazon Resource Name (ARN) that the pipeline uses to execute.
', 'UserSettings$ExecutionRole' => 'The execution role for the user.
', ], ], 'RollingUpdatePolicy' => [ 'base' => 'Specifies a rolling deployment strategy for updating a SageMaker endpoint.
', 'refs' => [ 'DeploymentConfig$RollingUpdatePolicy' => 'Specifies a rolling deployment strategy for updating a SageMaker endpoint.
', ], ], 'RootAccess' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$RootAccess' => 'Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled
.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Whether root access is enabled or disabled for users of the notebook instance.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled
.
If you set this to Disabled
, users don\'t have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.
Sets how the endpoint routes incoming traffic:
LEAST_OUTSTANDING_REQUESTS
: The endpoint routes requests to the specific instances that have more capacity to process them.
RANDOM
: The endpoint routes each request to a randomly chosen instance.
The name of the rule configuration. It must be unique relative to other rule configuration names.
', 'DebugRuleEvaluationStatus$RuleConfigurationName' => 'The name of the rule configuration.
', 'ProfilerRuleConfiguration$RuleConfigurationName' => 'The name of the rule configuration. It must be unique relative to other rule configuration names.
', 'ProfilerRuleEvaluationStatus$RuleConfigurationName' => 'The name of the rule configuration.
', ], ], 'RuleEvaluationStatus' => [ 'base' => NULL, 'refs' => [ 'DebugRuleEvaluationStatus$RuleEvaluationStatus' => 'Status of the rule evaluation.
', 'ProfilerRuleEvaluationStatus$RuleEvaluationStatus' => 'Status of the rule evaluation.
', ], ], 'RuleParameters' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$RuleParameters' => 'Runtime configuration for rule container.
', 'ProfilerRuleConfiguration$RuleParameters' => 'Runtime configuration for rule container.
', ], ], 'S3DataDistribution' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$S3DataDistributionType' => 'If you want SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify FullyReplicated
.
If you want SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify ShardedByS3Key
. If there are n ML compute instances launched for a training job, each instance gets approximately 1/n of the number of S3 objects. In this case, model training on each machine uses only the subset of training data.
Don\'t choose more ML compute instances for training than available S3 objects. If you do, some nodes won\'t get any data and you will pay for nodes that aren\'t getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances, you might choose ShardedByS3Key
. If the algorithm requires copying training data to the ML storage volume (when TrainingInputMode
is set to File
), this copies 1/n of the number of objects.
Describes the S3 data source.
Your input bucket must be in the same Amazon Web Services region as your training job.
', 'refs' => [ 'DataSource$S3DataSource' => 'The S3 location of the data source that is associated with a channel.
', ], ], 'S3DataType' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$S3DataType' => 'If you choose S3Prefix
, S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
If you choose ManifestFile
, S3Uri
identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
If you choose AugmentedManifestFile
, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile
can only be used if the Channel\'s input mode is Pipe
.
If you choose S3Prefix
, S3Uri
identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.
If you choose ManifestFile
, S3Uri
identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.
The following values are compatible: ManifestFile
, S3Prefix
The following value is not compatible: AugmentedManifestFile
Specifies the S3 location of ML model data to deploy.
', 'refs' => [ 'ModelDataSource$S3DataSource' => 'Specifies the S3 location of ML model data to deploy.
', ], ], 'S3ModelDataType' => [ 'base' => NULL, 'refs' => [ 'S3ModelDataSource$S3DataType' => 'Specifies the type of ML model data to deploy.
If you choose S3Prefix
, S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix as part of the ML model data to deploy. A valid key name prefix identified by S3Uri
always ends with a forward slash (/).
If you choose S3Object
, S3Uri
identifies an object that is the ML model data to deploy.
Specifies the S3 path of ML model data to deploy.
', ], ], 'S3OutputPath' => [ 'base' => NULL, 'refs' => [ 'HubS3StorageConfig$S3OutputPath' => 'The Amazon S3 bucket prefix for hosting hub content.
', ], ], 'S3StorageConfig' => [ 'base' => 'The Amazon Simple Storage (Amazon S3) location and and security configuration for OfflineStore
.
The Amazon Simple Storage (Amazon S3) location of OfflineStore
.
The uniform resource identifier (URI) used to identify an additional data source used in inference or training.
', 'AthenaDatasetDefinition$OutputS3Uri' => 'The location in Amazon S3 where Athena query results are stored.
', 'AutoMLCandidateGenerationConfig$FeatureSpecificationS3Uri' => 'A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames
(optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }
.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric
, categorical
, text
, and datetime
. In HPO mode, Autopilot can support numeric
, categorical
, text
, datetime
, and sequence
.
If only FeatureDataTypes
is provided, the column keys (col1
, col2
,..) should be a subset of the column names in the input data.
If both FeatureDataTypes
and FeatureAttributeNames
are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames
.
The key name FeatureAttributeNames
is fixed. The values listed in ["col1", "col2", ...]
are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
The Amazon S3 output path. Must be 128 characters or less.
', 'AutoMLS3DataSource$S3Uri' => 'The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.
', 'BatchDataCaptureConfig$DestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'CheckpointConfig$S3Uri' => 'Identifies the S3 path where you want SageMaker to store checkpoints. For example, s3://bucket-name/key-name-prefix
.
An Amazon S3 bucket path where your LifeCycle scripts are stored.
', 'CreateLabelingJobRequest$LabelCategoryConfigS3Uri' => 'The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to "labels"
, you must provide worker instructions in the label category configuration file using the "instructions"
parameter: "instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}
. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .
For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1
, label_2
,...
,label_n
with your label categories.
{
"document-version": "2018-11-28",
"labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]
}
Note the following about the label category configuration file:
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
Each label category must be unique, you cannot specify duplicate label categories.
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName
in the label category configuration. Use this parameter to enter the LabelAttributeName
of the labeling job you want to adjust or verify annotations of.
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.
', 'DataQualityAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'DataQualityAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'DebugHookConfig$S3OutputPath' => 'Path to Amazon S3 storage location for metrics and tensors.
', 'DebugRuleConfiguration$S3OutputPath' => 'Path to Amazon S3 storage location for rules.
', 'DescribeEdgePackagingJobResponse$ModelArtifact' => 'The Amazon Simple Storage (S3) URI where model artifacts ares stored.
', 'DescribeLabelingJobResponse$LabelCategoryConfigS3Uri' => 'The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:
Semantic segmentation labeling jobs using automated labeling: 20 labels
Box bounding labeling jobs (all): 10 labels
The file is a JSON structure in the following format:
{
"document-version": "2018-11-28"
"labels": [
{
"label": "label 1"
},
{
"label": "label 2"
},
...
{
"label": "label n"
}
]
}
The Amazon Simple Storage (S3) bucker URI.
', 'FileSource$S3Uri' => 'The Amazon S3 URI for the file source.
', 'FlowDefinitionOutputConfig$S3OutputPath' => 'The Amazon S3 path where the object containing human output will be made available.
To learn more about the format of Amazon A2I output data, see Amazon A2I Output Data.
', 'InferenceRecommendationsJob$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'InputConfig$S3Uri' => 'The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'LabelingJobOutput$OutputDatasetS3Uri' => 'The Amazon S3 bucket location of the manifest file for labeled data.
', 'LabelingJobOutputConfig$S3OutputPath' => 'The Amazon S3 location to write output data.
', 'LabelingJobS3DataSource$ManifestS3Uri' => 'The Amazon S3 location of the manifest file that describes the input data objects.
The input manifest file referenced in ManifestS3Uri
must contain one of the following keys: source-ref
or source
. The value of the keys are interpreted as follows:
source-ref
: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.
source
: The source of the object is the value. Use this value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.
', 'MetricsSource$S3Uri' => 'The S3 URI for the metrics source.
', 'ModelArtifacts$S3ModelArtifacts' => 'The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz
.
JSON formatted S3 file that defines bias parameters. For more information on this JSON configuration file, see Configure bias parameters.
', 'ModelCardExportArtifacts$S3ExportArtifacts' => 'The Amazon S3 URI of the exported model artifacts.
', 'ModelCardExportOutputConfig$S3OutputPath' => 'The Amazon S3 output path to export your model card PDF.
', 'ModelExplainabilityAppSpecification$ConfigUri' => 'JSON formatted Amazon S3 file that defines explainability parameters. For more information on this JSON configuration file, see Configure model explainability parameters.
', 'ModelQualityAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'ModelQualityAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'MonitoringAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'MonitoringAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'MonitoringConstraintsResource$S3Uri' => 'The Amazon S3 URI for the constraints resource.
', 'MonitoringStatisticsResource$S3Uri' => 'The Amazon S3 URI for the statistics resource.
', 'OutputConfig$S3OutputLocation' => 'Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix
.
Identifies the S3 path where you want SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix
.
The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
', 'ProcessingS3Output$S3Uri' => 'A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
', 'ProfilerConfig$S3OutputPath' => 'Path to Amazon S3 storage location for system and framework metrics.
', 'ProfilerConfigForUpdate$S3OutputPath' => 'Path to Amazon S3 storage location for system and framework metrics.
', 'ProfilerRuleConfiguration$S3OutputPath' => 'Path to Amazon S3 storage location for rules.
', 'RecommendationJobCompiledOutputConfig$S3OutputUri' => 'Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.
', 'RecommendationJobPayloadConfig$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'RedshiftDatasetDefinition$OutputS3Uri' => 'The location in Amazon S3 where the Redshift query results are stored.
', 'S3DataSource$S3Uri' => 'Depending on the value specified for the S3DataType
, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix
A manifest might look like this: s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of S3Uri
. Note that the prefix must be a valid non-empty S3Uri
that precludes users from specifying a manifest whose individual S3Uri
is sourced from different S3 buckets.
The following code example shows a valid manifest format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
This JSON is equivalent to the following S3Uri
list:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uri
in this manifest is the input data for the channel for this data source. The object that each S3Uri
points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
', 'S3StorageConfig$S3Uri' => 'The S3 URI, or location in Amazon S3, of OfflineStore
.
S3 URIs have a format similar to the following: s3://example-bucket/prefix/
.
The S3 path where offline records are written.
', 'SharingSettings$S3OutputPath' => 'When NotebookOutputOption
is Allowed
, the Amazon S3 bucket used to store the shared notebook snapshots.
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job V2. You can input FeatureAttributeNames
(optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }
.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric
, categorical
, text
, and datetime
. In HPO mode, Autopilot can support numeric
, categorical
, text
, datetime
, and sequence
.
If only FeatureDataTypes
is provided, the column keys (col1
, col2
,..) should be a subset of the column names in the input data.
If both FeatureDataTypes
and FeatureAttributeNames
are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames
.
The key name FeatureAttributeNames
is fixed. The values listed in ["col1", "col2", ...]
are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
Path to Amazon S3 storage location for TensorBoard output.
', 'TimeSeriesForecastingJobConfig$FeatureSpecificationS3Uri' => 'A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig
. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig
. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig
.
You can input FeatureAttributeNames
(optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }
.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
Autopilot supports the following data types: numeric
, categorical
, text
, and datetime
.
These column keys must not include any column set in TimeSeriesConfig
.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example, s3://bucket-name/key-name-prefix
.
For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out
suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at s3://bucket-name/input-name-prefix/dataset01/data.csv
, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out
. Batch transform doesn\'t upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out
file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.
Depending on the value specified for the S3DataType
, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix
.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
The preceding JSON matches the following S3Uris
:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris
in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris
points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
', 'WorkspaceSettings$S3ArtifactPath' => 'The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users must log out and log back in to apply the new location.
', ], ], 'SageMakerImageVersionAlias' => [ 'base' => NULL, 'refs' => [ 'DeleteImageVersionRequest$Alias' => 'The alias of the image to delete.
', 'DescribeImageVersionRequest$Alias' => 'The alias of the image version.
', 'ListAliasesRequest$Alias' => 'The alias of the image version.
', 'SageMakerImageVersionAliases$member' => NULL, 'UpdateImageVersionRequest$Alias' => 'The alias of the image version.
', ], ], 'SageMakerImageVersionAliases' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$Aliases' => 'A list of aliases created with the image version.
', 'ListAliasesResponse$SageMakerImageVersionAliases' => 'A list of SageMaker image version aliases.
', 'UpdateImageVersionRequest$AliasesToAdd' => 'A list of aliases to add.
', 'UpdateImageVersionRequest$AliasesToDelete' => 'A list of aliases to delete.
', ], ], 'SagemakerServicecatalogStatus' => [ 'base' => NULL, 'refs' => [ 'GetSagemakerServicecatalogPortfolioStatusOutput$Status' => 'Whether Service Catalog is enabled or disabled in SageMaker.
', ], ], 'SampleWeightAttributeName' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$SampleWeightAttributeName' => 'If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
', 'TabularJobConfig$SampleWeightAttributeName' => 'If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
', ], ], 'SamplingPercentage' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$InitialSamplingPercentage' => 'The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints with high traffic.
', 'DataCaptureConfigSummary$CurrentSamplingPercentage' => 'The percentage of requests being captured by your Endpoint.
', ], ], 'ScalingPolicies' => [ 'base' => NULL, 'refs' => [ 'DynamicScalingConfiguration$ScalingPolicies' => 'An object of the scaling policies for each metric.
', ], ], 'ScalingPolicy' => [ 'base' => 'An object containing a recommended scaling policy.
', 'refs' => [ 'ScalingPolicies$member' => NULL, ], ], 'ScalingPolicyMetric' => [ 'base' => 'The metric for a scaling policy.
', 'refs' => [ 'GetScalingConfigurationRecommendationResponse$Metric' => 'An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job.
', ], ], 'ScalingPolicyObjective' => [ 'base' => 'An object where you specify the anticipated traffic pattern for an endpoint.
', 'refs' => [ 'GetScalingConfigurationRecommendationRequest$ScalingPolicyObjective' => 'An object where you specify the anticipated traffic pattern for an endpoint.
', 'GetScalingConfigurationRecommendationResponse$ScalingPolicyObjective' => 'An object representing the anticipated traffic pattern for an endpoint that you specified in the request.
', ], ], 'ScheduleConfig' => [ 'base' => 'Configuration details about the monitoring schedule.
', 'refs' => [ 'MonitoringScheduleConfig$ScheduleConfig' => 'Configures the monitoring schedule.
', ], ], 'ScheduleExpression' => [ 'base' => NULL, 'refs' => [ 'ScheduleConfig$ScheduleExpression' => 'A cron expression that describes details about the monitoring schedule.
The supported cron expressions are:
If you want to set the job to start every hour, use the following:
Hourly: cron(0 * ? * * *)
If you want to start the job daily:
cron(0 [00-23] ? * * *)
If you want to run the job one time, immediately, use the following keyword:
NOW
For example, the following are valid cron expressions:
Daily at noon UTC: cron(0 12 ? * * *)
Daily at midnight UTC: cron(0 0 ? * * *)
To support running every 6, 12 hours, the following are also supported:
cron(0 [00-23]/[01-24] ? * * *)
For example, the following are valid cron expressions:
Every 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)
Every two hours starting at midnight: cron(0 0/2 ? * * *)
Even though the cron expression is set to start at 5PM UTC, note that there could be a delay of 0-20 minutes from the actual requested time to run the execution.
We recommend that if you would like a daily schedule, you do not provide this parameter. Amazon SageMaker will pick a time for running every day.
You can also specify the keyword NOW
to run the monitoring job immediately, one time, without recurring.
The status of an monitoring job.
', 'ListMonitoringSchedulesRequest$StatusEquals' => 'A filter that returns only monitoring schedules modified before a specified time.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleStatus' => 'The status of the monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleStatus' => 'The status of the monitoring schedule. This can be one of the following values.
PENDING
- The schedule is pending being created.
FAILED
- The schedule failed.
SCHEDULED
- The schedule was successfully created.
STOPPED
- The schedule was stopped.
The status of the monitoring schedule.
', ], ], 'SearchExpression' => [ 'base' => 'A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression
can contain up to twenty elements.
A SearchExpression
contains the following components:
A list of Filter
objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter
objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions.
A list of SearchExpression
objects. A search expression object can be nested in a list of search expression objects.
A Boolean operator: And
or Or
.
A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions
, NestedFilters
, and Filters
that can be included in a SearchExpression
object is 50.
A list of search expression objects.
', ], ], 'SearchRecord' => [ 'base' => 'A single resource returned as part of the Search API response.
', 'refs' => [ 'SearchResultsList$member' => NULL, ], ], 'SearchRequest' => [ 'base' => NULL, 'refs' => [], ], 'SearchResponse' => [ 'base' => NULL, 'refs' => [], ], 'SearchResultsList' => [ 'base' => NULL, 'refs' => [ 'SearchResponse$Results' => 'A list of SearchRecord
objects.
How SearchResults
are ordered. Valid values are Ascending
or Descending
. The default is Descending
.
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage
under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting
- Starting the training job.
Downloading
- An optional stage for algorithms that support File
training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training
- Training is in progress.
Interrupted
- The job stopped because the managed spot training instances were interrupted.
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
Completed
- The training job has completed.
Failed
- The training job has failed. The reason for the failure is returned in the FailureReason
field of DescribeTrainingJobResponse
.
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime.
MaxWaitTimeExceeded
- The job stopped because it exceeded the maximum allowed wait time.
Stopped
- The training job has stopped.
Stopping
- Stopping the training job.
Valid values for SecondaryStatus
are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTraining
DownloadingTrainingImage
Contains a secondary status information from a training job.
Status might be one of the following secondary statuses:
Starting
- Starting the training job.
Downloading
- An optional stage for algorithms that support File
training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training
- Training is in progress.
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
Completed
- The training job has completed.
Failed
- The training job has failed. The reason for the failure is returned in the FailureReason
field of DescribeTrainingJobResponse
.
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime.
Stopped
- The training job has stopped.
Stopping
- Stopping the training job.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage
under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting
- Starting the training job.
Downloading
- An optional stage for algorithms that support File
training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training
- Training is in progress.
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
Completed
- The training job has completed.
Failed
- The training job has failed. The reason for the failure is returned in the FailureReason
field of DescribeTrainingJobResponse
.
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime.
Stopped
- The training job has stopped.
Stopping
- Stopping the training job.
Valid values for SecondaryStatus
are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
An array element of SecondaryStatusTransitions
for DescribeTrainingJob. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job\'s secondary status.
A history of all of the secondary statuses that the training job has transitioned through.
', 'TrainingJob$SecondaryStatusTransitions' => 'A history of all of the secondary statuses that the training job has transitioned through.
', ], ], 'SecretArn' => [ 'base' => NULL, 'refs' => [ 'GitConfig$SecretArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT
and must be in the following format:
{"username": UserName, "password": Password}
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT
and must be in the following format:
{"username": UserName, "password": Password}
The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your identity provider, such as the client ID and secret, authorization URL, and token URL.
', ], ], 'SecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'DescribeDomainResponse$SecurityGroupIdForDomainBoundary' => 'The ID of the security group that authorizes traffic between the RSessionGateway
apps and the RStudioServerPro
app.
The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', 'DefaultSpaceSettings$SecurityGroups' => 'The security group IDs for the Amazon Virtual Private Cloud that the space uses for communication.
', 'DescribeNotebookInstanceOutput$SecurityGroups' => 'The IDs of the VPC security groups.
', 'UserSettings$SecurityGroups' => 'The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
Optional when the CreateDomain.AppNetworkAccessType
parameter is set to PublicInternetOnly
.
Required when the CreateDomain.AppNetworkAccessType
parameter is set to VpcOnly
, unless specified as part of the DefaultUserSettings
for the domain.
Amazon SageMaker adds a security group to allow NFS traffic from Amazon SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
', ], ], 'Seed' => [ 'base' => NULL, 'refs' => [ 'ShuffleConfig$Seed' => 'Determines the shuffling order in ShuffleConfig
value.
A step selected to run in selective execution mode.
', 'refs' => [ 'SelectedStepList$member' => NULL, ], ], 'SelectedStepList' => [ 'base' => NULL, 'refs' => [ 'SelectiveExecutionConfig$SelectedSteps' => 'A list of pipeline steps to run. All step(s) in all path(s) between two selected steps should be included.
', ], ], 'SelectiveExecutionConfig' => [ 'base' => 'The selective execution configuration applied to the pipeline run.
', 'refs' => [ 'DescribePipelineExecutionResponse$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', 'PipelineExecution$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', 'StartPipelineExecutionRequest$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', ], ], 'SelectiveExecutionResult' => [ 'base' => 'The ARN from an execution of the current pipeline.
', 'refs' => [ 'PipelineExecutionStep$SelectiveExecutionResult' => 'The ARN from an execution of the current pipeline from which results are reused for this step.
', ], ], 'SendPipelineExecutionStepFailureRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepFailureResponse' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepSuccessRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepSuccessResponse' => [ 'base' => NULL, 'refs' => [], ], 'ServerlessMaxConcurrency' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$MaxConcurrency' => 'The maximum number of concurrent invocations your serverless endpoint can process.
', 'ProductionVariantServerlessUpdateConfig$MaxConcurrency' => 'The updated maximum number of concurrent invocations your serverless endpoint can process.
', ], ], 'ServerlessMemorySizeInMB' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$MemorySizeInMB' => 'The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
', ], ], 'ServerlessProvisionedConcurrency' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$ProvisionedConcurrency' => 'The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency
.
This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
The updated amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency
.
The ID of the provisioned product.
', 'ServiceCatalogProvisioningDetails$ProductId' => 'The ID of the product to provision.
', 'ServiceCatalogProvisioningDetails$ProvisioningArtifactId' => 'The ID of the provisioning artifact.
', 'ServiceCatalogProvisioningDetails$PathId' => 'The path identifier of the product. This value is optional if the product has a default path, and required if the product has more than one path.
', 'ServiceCatalogProvisioningUpdateDetails$ProvisioningArtifactId' => 'The ID of the provisioning artifact.
', ], ], 'ServiceCatalogProvisionedProductDetails' => [ 'base' => 'Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'DescribeProjectOutput$ServiceCatalogProvisionedProductDetails' => 'Information about a provisioned service catalog product.
', 'Project$ServiceCatalogProvisionedProductDetails' => NULL, ], ], 'ServiceCatalogProvisioningDetails' => [ 'base' => 'Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'CreateProjectInput$ServiceCatalogProvisioningDetails' => 'The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don\'t provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
', 'DescribeProjectOutput$ServiceCatalogProvisioningDetails' => 'Information used to provision a service catalog product. For information, see What is Amazon Web Services Service Catalog.
', 'Project$ServiceCatalogProvisioningDetails' => NULL, ], ], 'ServiceCatalogProvisioningUpdateDetails' => [ 'base' => 'Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'UpdateProjectInput$ServiceCatalogProvisioningUpdateDetails' => 'The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don\'t provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
', ], ], 'SessionExpirationDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlRequest$SessionExpirationDurationInSeconds' => 'The session expiration duration in seconds. This value defaults to 43200.
', 'CreatePresignedNotebookInstanceUrlInput$SessionExpirationDurationInSeconds' => 'The duration of the session, in seconds. The default is 12 hours.
', ], ], 'ShadowModeConfig' => [ 'base' => ' The configuration of ShadowMode
inference experiment type, which specifies a production variant to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode
inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode
inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode
inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The name and sampling percentage of a shadow variant.
', 'refs' => [ 'ShadowModelVariantConfigList$member' => NULL, ], ], 'ShadowModelVariantConfigList' => [ 'base' => NULL, 'refs' => [ 'ShadowModeConfig$ShadowModelVariants' => 'List of shadow variant configurations.
', ], ], 'SharingSettings' => [ 'base' => 'Specifies options for sharing Amazon SageMaker Studio notebooks. These settings are specified as part of DefaultUserSettings
when the CreateDomain
API is called, and as part of UserSettings
when the CreateUserProfile
API is called. When SharingSettings
is not specified, notebook sharing isn\'t allowed.
Specifies options for sharing Amazon SageMaker Studio notebooks.
', ], ], 'SharingType' => [ 'base' => NULL, 'refs' => [ 'SpaceSharingSettings$SharingType' => 'Specifies the sharing type of the space.
', 'SpaceSharingSettingsSummary$SharingType' => 'Specifies the sharing type of the space.
', ], ], 'ShuffleConfig' => [ 'base' => 'A configuration for a shuffle option for input data in a channel. If you use S3Prefix
for S3DataType
, the results of the S3 key prefix matches are shuffled. If you use ManifestFile
, the order of the S3 object references in the ManifestFile
is shuffled. If you use AugmentedManifestFile
, the order of the JSON lines in the AugmentedManifestFile
is shuffled. The shuffling order is determined using the Seed
value.
For Pipe input mode, when ShuffleConfig
is specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig
is combined with S3DataDistributionType
of ShardedByS3Key
, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
A configuration for a shuffle option for input data in a channel. If you use S3Prefix
for S3DataType
, this shuffles the results of the S3 key prefix matches. If you use ManifestFile
, the order of the S3 object references in the ManifestFile
is shuffled. If you use AugmentedManifestFile
, the order of the JSON lines in the AugmentedManifestFile
is shuffled. The shuffling order is determined using the Seed
value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType
of ShardedByS3Key
, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
The ARN of the application managed by SageMaker in IAM Identity Center. This value is only returned for domains created after October 1, 2023.
', ], ], 'SingleSignOnUserIdentifier' => [ 'base' => NULL, 'refs' => [ 'CreateUserProfileRequest$SingleSignOnUserIdentifier' => 'A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain\'s AuthMode is IAM Identity Center, this field is required. If the Domain\'s AuthMode is not IAM Identity Center, this field cannot be specified.
', 'DescribeUserProfileResponse$SingleSignOnUserIdentifier' => 'The IAM Identity Center user identifier.
', ], ], 'SkipModelValidation' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$SkipModelValidation' => 'Indicates if you want to skip model validation.
', 'DescribeModelPackageOutput$SkipModelValidation' => 'Indicates if you want to skip model validation.
', 'ModelPackage$SkipModelValidation' => 'Indicates if you want to skip model validation.
', ], ], 'SnsTopicArn' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceNotificationConfig$SuccessTopic' => 'Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
', 'AsyncInferenceNotificationConfig$ErrorTopic' => 'Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
', 'LabelingJobOutputConfig$SnsTopicArn' => 'An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn
if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.
If you provide an SnsTopicArn
in OutputConfig
, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.
To learn more, see Receive Output Data from a Streaming Labeling Job.
', 'LabelingJobSnsDataSource$SnsTopicArn' => 'The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.
', ], ], 'SortActionsBy' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime
.
The property used to sort results. The default value is CreationTime
.
The property used to sort results. The default value is CreationTime
.
The field to sort results by. The default is CreationTime
.
The field to sort results by. The default is CreationTime
.
The field to sort results by. The default is CreationTime
.
The field to sort results by. The default is CreationTime
.
The property used to sort results. The default value is CreationTime
.
The property used to sort results. The default value is CreationTime
.
The column by which to sort the listed inference experiments.
', ], ], 'SortLineageGroupsBy' => [ 'base' => NULL, 'refs' => [ 'ListLineageGroupsRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime
.
The sort order. The default value is Descending
.
The sort order for the results. The default is Ascending
.
The sort order. The default value is Descending
.
The sort order for the results. The default is Ascending.
', 'ListArtifactsRequest$SortOrder' => 'The sort order. The default value is Descending
.
The sort order. The default value is Descending
.
The sort order for results. The default value is Ascending
.
The sort order for results. The default value is Ascending
.
The sort order for results. The default is Ascending
.
The sort order. The default value is Descending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
What direction to sort in.
', 'ListEdgeDeploymentPlansRequest$SortOrder' => 'The direction of the sorting (ascending or descending).
', 'ListEdgePackagingJobsRequest$SortOrder' => 'What direction to sort by.
', 'ListExperimentsRequest$SortOrder' => 'The sort order. The default value is Descending
.
An optional value that specifies whether you want the results sorted in Ascending
or Descending
order.
Sort hub content versions by ascending or descending order.
', 'ListHubContentsRequest$SortOrder' => 'Sort hubs by ascending or descending order.
', 'ListHubsRequest$SortOrder' => 'Sort hubs by ascending or descending order.
', 'ListHumanTaskUisRequest$SortOrder' => 'An optional value that specifies whether you want the results sorted in Ascending
or Descending
order.
The sort order for results. The default is Ascending
.
The direction of sorting (ascending or descending).
', 'ListInferenceRecommendationsJobsRequest$SortOrder' => 'The sort order for the results.
', 'ListLabelingJobsForWorkteamRequest$SortOrder' => 'The sort order for results. The default is Ascending
.
The sort order for results. The default is Ascending
.
The sort order for the results. The default is Ascending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
The sort order for results. The default is Ascending
.
The sort order for the results. The default is Ascending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
The sort order, whether Ascending
or Descending
, of the alert history. The default is Descending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
The field by which to sort results. The default is CreatedTime
.
The sort order for results.
', 'ListPipelinesRequest$SortOrder' => 'The sort order for results.
', 'ListProcessingJobsRequest$SortOrder' => 'The sort order for results. The default is Ascending
.
The sort order for the results. The default is Ascending
.
The sort order. The default value is Descending.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$SortOrder' => 'The sort order for results. The default is Ascending
.
The sort order for results. The default is Ascending
.
The sort order for results. The default is Descending
.
The sort order. The default value is Descending
.
The sort order. The default value is Descending
.
The sort order for the results. The default is Ascending.
', 'ListWorkforcesRequest$SortOrder' => 'Sort workforces in ascending or descending order.
', 'ListWorkteamsRequest$SortOrder' => 'The sort order for results. The default is Ascending
.
The field by which to sort results. The default is CreatedTime
.
The field by which to sort results. The default is CreatedTime
.
The property used to sort results. The default value is CreationTime
.
The property used to sort results. The default value is CreationTime
.
Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
', 'refs' => [ 'SourceAlgorithmList$member' => NULL, ], ], 'SourceAlgorithmList' => [ 'base' => NULL, 'refs' => [ 'SourceAlgorithmSpecification$SourceAlgorithms' => 'A list of the algorithms that were used to create a model package.
', ], ], 'SourceAlgorithmSpecification' => [ 'base' => 'A list of algorithms that were used to create a model package.
', 'refs' => [ 'CreateModelPackageInput$SourceAlgorithmSpecification' => 'Details about the algorithm that was used to create the model package.
', 'DescribeModelPackageOutput$SourceAlgorithmSpecification' => 'Details about the algorithm that was used to create the model package.
', 'ModelPackage$SourceAlgorithmSpecification' => 'A list of algorithms that were used to create a model package.
', ], ], 'SourceIpConfig' => [ 'base' => 'A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to login to their worker portal from an IP address within this range. By default, a workforce isn\'t restricted to specific IP addresses.
', 'refs' => [ 'CreateWorkforceRequest$SourceIpConfig' => NULL, 'UpdateWorkforceRequest$SourceIpConfig' => 'A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce.
Maximum: Ten CIDR values
', 'Workforce$SourceIpConfig' => 'A list of one to ten IP address ranges (CIDRs) to be added to the workforce allow list. By default, a workforce isn\'t restricted to specific IP addresses.
', ], ], 'SourceType' => [ 'base' => NULL, 'refs' => [ 'ExperimentSource$SourceType' => 'The source type.
', 'TrialComponentSource$SourceType' => 'The source job type.
', 'TrialSource$SourceType' => 'The source job type.
', ], ], 'SourceUri' => [ 'base' => NULL, 'refs' => [ 'ActionSource$SourceUri' => 'The URI of the source.
', 'ArtifactSource$SourceUri' => 'The URI of the source.
', 'ContextSource$SourceUri' => 'The URI of the source.
', 'ListActionsRequest$SourceUri' => 'A filter that returns only actions with the specified source URI.
', 'ListArtifactsRequest$SourceUri' => 'A filter that returns only artifacts with the specified source URI.
', 'ListContextsRequest$SourceUri' => 'A filter that returns only contexts with the specified source URI.
', ], ], 'SpaceArn' => [ 'base' => NULL, 'refs' => [ 'CreateSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', 'DescribeSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', 'UpdateSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', ], ], 'SpaceCodeEditorAppSettings' => [ 'base' => 'The application settings for a Code Editor space.
', 'refs' => [ 'SpaceSettings$CodeEditorAppSettings' => 'The Code Editor application settings.
', ], ], 'SpaceDetails' => [ 'base' => 'The space\'s details.
', 'refs' => [ 'SpaceList$member' => NULL, ], ], 'SpaceEbsVolumeSizeInGb' => [ 'base' => NULL, 'refs' => [ 'DefaultEbsStorageSettings$DefaultEbsVolumeSizeInGb' => 'The default size of the EBS storage volume for a private space.
', 'DefaultEbsStorageSettings$MaximumEbsVolumeSizeInGb' => 'The maximum size of the EBS storage volume for a private space.
', 'EbsStorageSettings$EbsVolumeSizeInGb' => 'The size of an EBS storage volume for a private space.
', ], ], 'SpaceJupyterLabAppSettings' => [ 'base' => 'The settings for the JupyterLab application within a space.
', 'refs' => [ 'SpaceSettings$JupyterLabAppSettings' => 'The settings for the JupyterLab application.
', ], ], 'SpaceList' => [ 'base' => NULL, 'refs' => [ 'ListSpacesResponse$Spaces' => 'The list of spaces.
', ], ], 'SpaceName' => [ 'base' => NULL, 'refs' => [ 'AppDetails$SpaceName' => 'The name of the space.
', 'CreateAppRequest$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName
must be set.
The name of the space.
', 'CreateSpaceRequest$SpaceName' => 'The name of the space.
', 'DeleteAppRequest$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName
must be set.
The name of the space.
', 'DescribeAppRequest$SpaceName' => 'The name of the space.
', 'DescribeAppResponse$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName
must be set.
The name of the space.
', 'DescribeSpaceResponse$SpaceName' => 'The name of the space.
', 'ListAppsRequest$SpaceNameEquals' => 'A parameter to search by space name. If UserProfileNameEquals
is set, then this value cannot be set.
A parameter by which to filter the results.
', 'SpaceDetails$SpaceName' => 'The name of the space.
', 'UpdateSpaceRequest$SpaceName' => 'The name of the space.
', ], ], 'SpaceSettings' => [ 'base' => 'A collection of space settings.
', 'refs' => [ 'CreateSpaceRequest$SpaceSettings' => 'A collection of space settings.
', 'DescribeSpaceResponse$SpaceSettings' => 'A collection of space settings.
', 'UpdateSpaceRequest$SpaceSettings' => 'A collection of space settings.
', ], ], 'SpaceSettingsSummary' => [ 'base' => 'Specifies summary information about the space settings.
', 'refs' => [ 'SpaceDetails$SpaceSettingsSummary' => 'Specifies summary information about the space settings.
', ], ], 'SpaceSharingSettings' => [ 'base' => 'A collection of space sharing settings.
', 'refs' => [ 'CreateSpaceRequest$SpaceSharingSettings' => 'A collection of space sharing settings.
', 'DescribeSpaceResponse$SpaceSharingSettings' => 'The collection of space sharing settings for a space.
', ], ], 'SpaceSharingSettingsSummary' => [ 'base' => 'Specifies summary information about the space sharing settings.
', 'refs' => [ 'SpaceDetails$SpaceSharingSettingsSummary' => 'Specifies summary information about the space sharing settings.
', ], ], 'SpaceSortKey' => [ 'base' => NULL, 'refs' => [ 'ListSpacesRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime
.
The status.
', 'SpaceDetails$Status' => 'The status.
', ], ], 'SpaceStorageSettings' => [ 'base' => 'The storage settings for a private space.
', 'refs' => [ 'SpaceSettings$SpaceStorageSettings' => 'The storage settings for a private space.
', 'SpaceSettingsSummary$SpaceStorageSettings' => 'The storage settings for a private space.
', ], ], 'SpawnRate' => [ 'base' => NULL, 'refs' => [ 'Phase$SpawnRate' => 'Specified how many new users to spawn in a minute.
', ], ], 'SplitType' => [ 'base' => NULL, 'refs' => [ 'TransformInput$SplitType' => 'The method to use to split the transform job\'s data files into smaller batches. Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for SplitType
is None
, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter to Line
to split records on a newline character boundary. SplitType
also supports a number of record-oriented binary data formats. Currently, the supported record formats are:
RecordIO
TFRecord
When splitting is enabled, the size of a mini-batch depends on the values of the BatchStrategy
and MaxPayloadInMB
parameters. When the value of BatchStrategy
is MultiRecord
, Amazon SageMaker sends the maximum number of records in each request, up to the MaxPayloadInMB
limit. If the value of BatchStrategy
is SingleRecord
, Amazon SageMaker sends individual records in each request.
Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of BatchStrategy
is set to SingleRecord
. Padding is not removed if the value of BatchStrategy
is set to MultiRecord
.
For more information about RecordIO
, see Create a Dataset Using RecordIO in the MXNet documentation. For more information about TFRecord
, see Consuming TFRecord data in the TensorFlow documentation.
The general status of the current stage.
', ], ], 'Stairs' => [ 'base' => 'Defines the stairs traffic pattern for an Inference Recommender load test. This pattern type consists of multiple steps where the number of users increases at each step.
Specify either the stairs or phases traffic pattern.
', 'refs' => [ 'TrafficPattern$Stairs' => 'Defines the stairs traffic pattern.
', ], ], 'StartEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'StartMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'StartPipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartPipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'Statistic' => [ 'base' => NULL, 'refs' => [ 'CustomizedMetricSpecification$Statistic' => 'The statistic of the customized metric.
', ], ], 'StatusDetails' => [ 'base' => NULL, 'refs' => [ 'DebugRuleEvaluationStatus$StatusDetails' => 'Details from the rule evaluation.
', 'ProfilerRuleEvaluationStatus$StatusDetails' => 'Details from the rule evaluation.
', ], ], 'StatusMessage' => [ 'base' => NULL, 'refs' => [ 'SecondaryStatusTransition$StatusMessage' => 'A detailed description of the progress within a secondary status.
SageMaker provides secondary statuses and status messages that apply to each of them:
Starting the training job.
Launching requested ML instances.
Insufficient capacity error from EC2 while launching instances, retrying!
Launched instance was unhealthy, replacing it!
Preparing the instances for training.
Training image download completed. Training in progress.
Status messages are subject to change. Therefore, we recommend not including them in code that programmatically initiates actions. For examples, don\'t use status messages in if statements.
To have an overview of your training job\'s progress, view TrainingJobStatus
and SecondaryStatus
in DescribeTrainingJob, and StatusMessage
together. For example, at the start of a training job, you might see the following:
TrainingJobStatus
- InProgress
SecondaryStatus
- Training
StatusMessage
- Downloading the training image
The description of the step.
', ], ], 'StepDisplayName' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepDisplayName' => 'The display name of the step.
', ], ], 'StepName' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepName' => 'The name of the step that is executed.
', ], ], 'StepStatus' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepStatus' => 'The status of the step execution.
', ], ], 'StopAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'StopPipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopPipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StoppingCondition' => [ 'base' => 'Specifies a limit to how long a model training job or model compilation job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training or compilation job. Use this API to cap model training costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel
.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
', 'CreateTrainingJobRequest$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
', 'DescribeTrainingJobResponse$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
', 'TrainingJob$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.
', ], ], 'StorageType' => [ 'base' => NULL, 'refs' => [ 'OnlineStoreConfig$StorageType' => 'Option for different tiers of low latency storage for real-time data retrieval.
Standard
: A managed low latency data store for feature groups.
InMemory
: A managed data store for feature groups that supports very low latency retrieval.
if the overall status is Failed
, the reason for the failure.
The attributes of the input data that are the input features.
', 'BatchTransformInput$InferenceAttribute' => 'The attribute of the input data that represents the ground truth label.
', 'BatchTransformInput$ProbabilityAttribute' => 'In a classification problem, the attribute that represents the class probability.
', 'ClusterInstanceStatusDetails$Message' => 'The message from an instance in a SageMaker HyperPod cluster.
', 'ClusterNodeDetails$InstanceId' => 'The ID of the instance.
', 'ClusterNodeSummary$InstanceId' => 'The ID of the instance.
', 'CreateModelPackageInput$Domain' => 'The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
', 'CreateModelPackageInput$Task' => 'The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION"
| "OBJECT_DETECTION"
| "TEXT_GENERATION"
|"IMAGE_SEGMENTATION"
| "FILL_MASK"
| "CLASSIFICATION"
| "REGRESSION"
| "OTHER"
.
Specify "OTHER" if none of the tasks listed fit your use case.
', 'CustomizedMetricSpecification$MetricName' => 'The name of the customized metric.
', 'CustomizedMetricSpecification$Namespace' => 'The namespace of the customized metric.
', 'DescribeClusterResponse$FailureMessage' => 'The failure message of the SageMaker HyperPod cluster.
', 'DescribeEdgePackagingJobResponse$EdgePackagingJobStatusMessage' => 'Returns a message describing the job status and error messages.
', 'DescribeEdgePackagingJobResponse$ModelSignature' => 'The signature document of files in the model artifact.
', 'DescribeModelPackageOutput$Domain' => 'The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.
', 'DescribeModelPackageOutput$Task' => 'The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.
', 'DescribeModelPackageOutput$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).
', 'DeviceDeploymentSummary$DeviceDeploymentStatusMessage' => 'The detailed error message for the deployoment status result.
', 'EdgeDeploymentStatus$EdgeDeploymentStatusMessage' => 'A detailed message about deployment status in current stage.
', 'EdgeOutputConfig$PresetDeploymentConfig' => 'The configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are:
ComponentName
(optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job.
ComponentDescription
(optional) - Description of the component.
ComponentVersion
(optional) - The version of the component.
Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the semantic version specification.
PlatformOS
(optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.
PlatformArchitecture
(optional) - The processor architecture for the platform.
Supported architectures Windows include: Windows32_x86, Windows64_x64.
Supported architectures for Linux include: Linux x86_64, Linux ARMV8.
Returns a message describing the status of the deployed resource.
', 'EndpointInput$FeaturesAttribute' => 'The attributes of the input data that are the input features.
', 'EndpointInput$InferenceAttribute' => 'The attribute of the input data that represents the ground truth label.
', 'EndpointInput$ProbabilityAttribute' => 'In a classification problem, the attribute that represents the class probability.
', 'EndpointOutputConfiguration$EndpointName' => 'The name of the endpoint made during a recommendation job.
', 'EndpointOutputConfiguration$VariantName' => 'The name of the production variant (deployed model) made during a recommendation job.
', 'EnvironmentParameter$Key' => 'The environment key suggested by the Amazon SageMaker Inference Recommender.
', 'EnvironmentParameter$ValueType' => 'The value type suggested by the Amazon SageMaker Inference Recommender.
', 'EnvironmentParameter$Value' => 'The value suggested by the Amazon SageMaker Inference Recommender.
', 'GetScalingConfigurationRecommendationRequest$RecommendationId' => 'The recommendation ID of a previously completed inference recommendation. This ID should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName
field.
Specify either this field or the EndpointName
field.
The recommendation ID of a previously completed inference recommendation.
', 'IamIdentity$Arn' => 'The Amazon Resource Name (ARN) of the IAM identity.
', 'IamIdentity$PrincipalId' => 'The ID of the principal that assumes the IAM identity.
', 'IamIdentity$SourceIdentity' => 'The person or application which assumes the IAM identity.
', 'InferenceRecommendation$RecommendationId' => 'The recommendation ID which uniquely identifies each recommendation.
', 'ListProcessingJobsRequest$NameContains' => 'A string in the processing job name. This filter returns only processing jobs whose name contains the specified string.
', 'ModelCard$ModelId' => 'The unique name (ID) of the model.
', 'ModelCard$RiskRating' => 'The risk rating of the model. Different organizations might have different criteria for model card risk ratings. For more information, see Risk ratings.
', 'ModelCard$ModelPackageGroupName' => 'The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry.
', 'ModelDashboardModelCard$ModelId' => 'For models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.
', 'ModelDashboardModelCard$RiskRating' => 'A model card\'s risk rating. Can be low, medium, or high.
', 'ModelMetadataSummary$Domain' => 'The machine learning domain of the model.
', 'ModelMetadataSummary$Framework' => 'The machine learning framework of the model.
', 'ModelMetadataSummary$Task' => 'The machine learning task of the model.
', 'ModelMetadataSummary$Model' => 'The name of the model.
', 'ModelMetadataSummary$FrameworkVersion' => 'The framework version of the model.
', 'ModelPackage$Domain' => 'The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
', 'ModelPackage$Task' => 'The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
', 'ModelPackage$SamplePayloadUrl' => 'The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'ModelPackageContainerDefinition$Framework' => 'The machine learning framework of the model package container image.
', 'ModelPackageContainerDefinition$NearestModelName' => 'The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata
.
if the overall status is Failed
, the reason for the failure.
The metric type. You can only apply SageMaker metric types to SageMaker endpoints.
', 'ProcessingInput$InputName' => 'The name for the processing job input.
', 'ProcessingOutput$OutputName' => 'The name for the processing job output.
', 'ProductListings$member' => NULL, 'RStudioServerProDomainSettings$RStudioConnectUrl' => 'A URL pointing to an RStudio Connect server.
', 'RStudioServerProDomainSettings$RStudioPackageManagerUrl' => 'A URL pointing to an RStudio Package Manager server.
', 'RStudioServerProDomainSettingsForUpdate$RStudioConnectUrl' => 'A URL pointing to an RStudio Connect server.
', 'RStudioServerProDomainSettingsForUpdate$RStudioPackageManagerUrl' => 'A URL pointing to an RStudio Package Manager server.
', 'RealTimeInferenceRecommendation$RecommendationId' => 'The recommendation ID which uniquely identifies each recommendation.
', 'RecommendationJobContainerConfig$Domain' => 'The machine learning domain of the model and its components.
Valid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING
The machine learning task that the model accomplishes.
Valid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION | REGRESSION | OTHER
The machine learning framework of the container image.
Valid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN
The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
Valid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn | densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet
A Liquid template that renders the HTML for the worker UI.
', 'RenderingError$Code' => 'A unique identifier for a specific class of errors.
', 'RenderingError$Message' => 'A human-readable message describing the error.
', 'ScheduleConfig$DataAnalysisStartTime' => 'Sets the start time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression
parameter. Specify this offset in ISO 8601 duration format. For example, if you want to monitor the five hours of data in your dataset that precede the start of each monitoring job, you would specify: "-PT5H"
.
The start time that you specify must not precede the end time that you specify by more than 24 hours. You specify the end time with the DataAnalysisEndTime
parameter.
If you set ScheduleExpression
to NOW
, this parameter is required.
Sets the end time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression
parameter. Specify this offset in ISO 8601 duration format. For example, if you want to end the window one hour before the start of each monitoring job, you would specify: "-PT1H"
.
The end time that you specify must not follow the start time that you specify by more than 24 hours. You specify the start time with the DataAnalysisStartTime
parameter.
If you set ScheduleExpression
to NOW
, this parameter is required.
The name of the vendor in the Amazon Marketplace.
', 'SubscribedWorkteam$ListingId' => 'Marketplace product listing ID.
', 'UserContext$UserProfileArn' => 'The Amazon Resource Name (ARN) of the user\'s profile.
', 'UserContext$UserProfileName' => 'The name of the user\'s profile.
', 'UserContext$DomainId' => 'The domain associated with the user.
', 'Workforce$SubDomain' => 'The subdomain for your OIDC Identity Provider.
', 'Workteam$SubDomain' => 'The URI of the labeling job\'s user interface. Workers open this URI to start labeling your data objects.
', ], ], 'String1024' => [ 'base' => NULL, 'refs' => [ 'ClarifyCheckStepMetadata$BaselineUsedForDriftCheckConstraints' => 'The Amazon S3 URI of baseline constraints file to be used for the drift check.
', 'ClarifyCheckStepMetadata$CalculatedBaselineConstraints' => 'The Amazon S3 URI of the newly calculated baseline constraints file.
', 'ClarifyCheckStepMetadata$ViolationReport' => 'The Amazon S3 URI of the violation report if violations are detected.
', 'CreateDomainResponse$Url' => 'The URL to the created domain.
', 'DescribeDomainResponse$Url' => 'The domain\'s URL.
', 'DescribeSpaceResponse$Url' => 'Returns the URL of the space. If the space is created with Amazon Web Services IAM Identity Center (Successor to Amazon Web Services Single Sign-On) authentication, users can navigate to the URL after appending the respective redirect parameter for the application type to be federated through Amazon Web Services IAM Identity Center.
The following application types are supported:
Studio Classic: &redirect=JupyterServer
JupyterLab: &redirect=JupyterLab
Code Editor, based on Code-OSS, Visual Studio Code - Open Source: &redirect=CodeEditor
The domain\'s URL.
', 'EMRStepMetadata$LogFilePath' => 'The path to the log file where the cluster step\'s failure root cause is recorded.
', 'OutputParameter$Value' => 'The value of the output parameter.
', 'Parameter$Value' => 'The literal value for the parameter.
', 'QualityCheckStepMetadata$BaselineUsedForDriftCheckStatistics' => 'The Amazon S3 URI of the baseline statistics file used for the drift check.
', 'QualityCheckStepMetadata$BaselineUsedForDriftCheckConstraints' => 'The Amazon S3 URI of the baseline constraints file used for the drift check.
', 'QualityCheckStepMetadata$CalculatedBaselineStatistics' => 'The Amazon S3 URI of the newly calculated baseline statistics file.
', 'QualityCheckStepMetadata$CalculatedBaselineConstraints' => 'The Amazon S3 URI of the newly calculated baseline constraints file.
', 'QualityCheckStepMetadata$ViolationReport' => 'The Amazon S3 URI of violation report if violations are detected.
', ], ], 'String128' => [ 'base' => NULL, 'refs' => [ 'CategoricalParameterRangeValues$member' => NULL, ], ], 'String200' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$Description' => 'A description of the work team.
', 'SubscribedWorkteam$MarketplaceTitle' => 'The title of the service provided by the vendor in the Amazon Marketplace.
', 'SubscribedWorkteam$MarketplaceDescription' => 'The description of the vendor from the Amazon Marketplace.
', 'UpdateWorkteamRequest$Description' => 'An updated description for the work team.
', 'Workteam$Description' => 'A description of the work team.
', ], ], 'String256' => [ 'base' => NULL, 'refs' => [ 'ActionSource$SourceType' => 'The type of the source.
', 'ActionSource$SourceId' => 'The ID of the source.
', 'ArtifactSourceType$Value' => 'The ID.
', 'ArtifactSummary$ArtifactType' => 'The type of the artifact.
', 'AssociationSummary$SourceType' => 'The source type.
', 'AssociationSummary$DestinationType' => 'The destination type.
', 'CallbackStepMetadata$SqsQueueUrl' => 'The URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the callback step.
', 'ClarifyCheckStepMetadata$CheckType' => 'The type of the Clarify Check step
', 'ClarifyCheckStepMetadata$ModelPackageGroupName' => 'The model package group name.
', 'ClarifyCheckStepMetadata$CheckJobArn' => 'The Amazon Resource Name (ARN) of the check processing job that was run by this step\'s execution.
', 'ContextSource$SourceType' => 'The type of the source.
', 'ContextSource$SourceId' => 'The ID of the source.
', 'ContextSummary$ContextType' => 'The type of the context.
', 'CreateActionRequest$ActionType' => 'The action type.
', 'CreateArtifactRequest$ArtifactType' => 'The artifact type.
', 'CreateContextRequest$ContextType' => 'The context type.
', 'CreateUserProfileRequest$SingleSignOnUserValue' => 'The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain\'s AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain\'s AuthMode is not IAM Identity Center, this field cannot be specified.
', 'CustomImageContainerEnvironmentVariables$value' => NULL, 'DescribeActionResponse$ActionType' => 'The type of the action.
', 'DescribeArtifactResponse$ArtifactType' => 'The type of the artifact.
', 'DescribeContextResponse$ContextType' => 'The type of the context.
', 'DescribeDomainResponse$SingleSignOnManagedApplicationInstanceId' => 'The IAM Identity Center managed application instance ID.
', 'DescribeUserProfileResponse$SingleSignOnUserValue' => 'The IAM Identity Center user value.
', 'EMRStepMetadata$ClusterId' => 'The identifier of the EMR cluster.
', 'EMRStepMetadata$StepId' => 'The identifier of the EMR cluster step.
', 'EMRStepMetadata$StepName' => 'The name of the EMR cluster step.
', 'LambdaStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution.
', 'ListActionsRequest$ActionType' => 'A filter that returns only actions of the specified type.
', 'ListArtifactsRequest$ArtifactType' => 'A filter that returns only artifacts of the specified type.
', 'ListAssociationsRequest$SourceType' => 'A filter that returns only associations with the specified source type.
', 'ListAssociationsRequest$DestinationType' => 'A filter that returns only associations with the specified destination type.
', 'ListContextsRequest$ContextType' => 'A filter that returns only contexts of the specified type.
', 'ListTrialComponentsRequest$SourceArn' => 'A filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify SourceArn
, you can\'t filter by ExperimentName
or TrialName
.
The value to filter the model metadata.
', 'ModelStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the created model.
', 'OutputParameter$Name' => 'The name of the output parameter.
', 'QualityCheckStepMetadata$CheckType' => 'The type of the Quality check step.
', 'QualityCheckStepMetadata$ModelPackageGroupName' => 'The model package group name.
', 'QualityCheckStepMetadata$CheckJobArn' => 'The Amazon Resource Name (ARN) of the Quality check processing job that was run by this step execution.
', 'QueryProperties$key' => NULL, 'QueryProperties$value' => NULL, 'RegisterModelStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the model package.
', 'SelectedStep$StepName' => 'The name of the pipeline step.
', 'SendPipelineExecutionStepFailureRequest$FailureReason' => 'A message describing why the step failed.
', ], ], 'String3072' => [ 'base' => NULL, 'refs' => [ 'FailStepMetadata$ErrorMessage' => 'A message that you define and then is processed and rendered by the Fail step when the error occurs.
', 'PipelineExecutionSummary$PipelineExecutionFailureReason' => 'A message generated by SageMaker Pipelines describing why the pipeline execution failed.
', ], ], 'String40' => [ 'base' => NULL, 'refs' => [ 'QueryTypes$member' => NULL, 'Vertex$Type' => 'The type of the lineage entity resource. For example: DataSet
, Model
, Endpoint
, etc...
The type of the action.
', 'CategoricalParameter$Name' => 'The Name of the environment variable.
', 'ModelLatencyThreshold$Percentile' => 'The model latency percentile threshold. Acceptable values are P95
and P99
. For custom load tests, specify the value as P95
.
Limits the number of vertices in the request. Use the NextToken
in a response to to retrieve the next page of results.
Limits the number of vertices in the response. Use the NextToken
in a response to to retrieve the next page of results.
The string value of a categorical hyperparameter. If you specify a value for this parameter, you can\'t specify the NumberValue
parameter.
The App type that the Lifecycle Configuration is attached to.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigAppType' => 'The App type that the Lifecycle Configuration is attached to.
', 'ListStudioLifecycleConfigsRequest$AppTypeEquals' => 'A parameter to search for the App Type to which the Lifecycle Configuration is attached.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigAppType' => 'The App type to which the Lifecycle Configuration is attached.
', ], ], 'StudioLifecycleConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigResponse$StudioLifecycleConfigArn' => 'The ARN of your created Lifecycle Configuration.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigArn' => 'The ARN of the Lifecycle Configuration to describe.
', 'LifecycleConfigArns$member' => NULL, 'ResourceSpec$LifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the Lifecycle Configuration.
', ], ], 'StudioLifecycleConfigContent' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigRequest$StudioLifecycleConfigContent' => 'The content of your Amazon SageMaker Studio Lifecycle Configuration script. This content must be base64 encoded.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigContent' => 'The content of your Amazon SageMaker Studio Lifecycle Configuration script.
', ], ], 'StudioLifecycleConfigDetails' => [ 'base' => 'Details of the Amazon SageMaker Studio Lifecycle Configuration.
', 'refs' => [ 'StudioLifecycleConfigsList$member' => NULL, ], ], 'StudioLifecycleConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration to create.
', 'DeleteStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration to delete.
', 'DescribeStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration to describe.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration that is described.
', 'ListStudioLifecycleConfigsRequest$NameContains' => 'A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration.
', ], ], 'StudioLifecycleConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListStudioLifecycleConfigsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime.
', ], ], 'StudioLifecycleConfigsList' => [ 'base' => NULL, 'refs' => [ 'ListStudioLifecycleConfigsResponse$StudioLifecycleConfigs' => 'A list of Lifecycle Configurations and their properties.
', ], ], 'StudioWebPortal' => [ 'base' => NULL, 'refs' => [ 'UserSettings$StudioWebPortal' => 'Whether the user can access Studio. If this value is set to DISABLED
, the user cannot access Studio, even if that is the default experience for the domain.
The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
', 'DescribeNotebookInstanceOutput$SubnetId' => 'The ID of the VPC subnet.
', 'Subnets$member' => NULL, ], ], 'Subnets' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$SubnetIds' => 'The VPC subnets that the domain uses for communication.
', 'DescribeDomainResponse$SubnetIds' => 'The VPC subnets that the domain uses for communication.
', 'UpdateDomainRequest$SubnetIds' => 'The VPC subnets that Studio uses for communication.
If removing subnets, ensure there are no apps in the InService
, Pending
, or Deleting
state.
The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.
', ], ], 'SubscribedWorkteam' => [ 'base' => 'Describes a work team of a vendor that does the a labelling job.
', 'refs' => [ 'DescribeSubscribedWorkteamResponse$SubscribedWorkteam' => 'A Workteam
instance that contains information about the work team.
An array of Workteam
objects, each describing a work team.
Returns true
if the work team was successfully deleted; otherwise, returns false
.
Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
', 'refs' => [ 'GetSearchSuggestionsRequest$SuggestionQuery' => 'Limits the property names that are included in the response.
', ], ], 'TableFormat' => [ 'base' => NULL, 'refs' => [ 'OfflineStoreConfig$TableFormat' => 'Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
', ], ], 'TableName' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$TableName' => 'The name of the Glue table.
', ], ], 'TabularJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the tabular problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TabularJobConfig' => 'Settings used to configure an AutoML job V2 for the tabular problem type (regression, classification).
', ], ], 'TabularResolvedAttributes' => [ 'base' => 'The resolved attributes specific to the tabular problem type.
', 'refs' => [ 'AutoMLProblemTypeResolvedAttributes$TabularResolvedAttributes' => 'The resolved attributes for the tabular problem type.
', ], ], 'Tag' => [ 'base' => 'A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
', 'refs' => [ 'TagList$member' => NULL, ], ], 'TagKey' => [ 'base' => NULL, 'refs' => [ 'Tag$Key' => 'The tag key. Tag keys must be unique per resource.
', 'TagKeyList$member' => NULL, ], ], 'TagKeyList' => [ 'base' => NULL, 'refs' => [ 'DeleteTagsInput$TagKeys' => 'An array or one or more tag keys to delete.
', ], ], 'TagList' => [ 'base' => NULL, 'refs' => [ 'AddTagsInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'AddTagsOutput$Tags' => 'A list of tags associated with the SageMaker resource.
', 'CreateActionRequest$Tags' => 'A list of tags to apply to the action.
', 'CreateAlgorithmInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateAppImageConfigRequest$Tags' => 'A list of tags to apply to the AppImageConfig.
', 'CreateAppRequest$Tags' => 'Each tag consists of a key and an optional value. Tag keys must be unique per resource.
', 'CreateArtifactRequest$Tags' => 'A list of tags to apply to the artifact.
', 'CreateAutoMLJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
', 'CreateAutoMLJobV2Request$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
', 'CreateClusterRequest$Tags' => 'Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can add tags to your cluster in the same way you add them in other Amazon Web Services services that support tagging. To learn more about tagging Amazon Web Services resources in general, see Tagging Amazon Web Services Resources User Guide.
', 'CreateCodeRepositoryInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateCompilationJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateContextRequest$Tags' => 'A list of tags to apply to the context.
', 'CreateDataQualityJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateDeviceFleetRequest$Tags' => 'Creates tags for the specified fleet.
', 'CreateDomainRequest$Tags' => 'Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search
API.
Tags that you specify for the Domain are also added to all Apps that the Domain launches.
', 'CreateEdgeDeploymentPlanRequest$Tags' => 'List of tags with which to tag the edge deployment plan.
', 'CreateEdgePackagingJobRequest$Tags' => 'Creates tags for the packaging job.
', 'CreateEndpointConfigInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateEndpointInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateExperimentRequest$Tags' => 'A list of tags to associate with the experiment. You can use Search API to search on the tags.
', 'CreateFeatureGroupRequest$Tags' => 'Tags used to identify Features
in each FeatureGroup
.
An array of key-value pairs that contain metadata to help you categorize and organize a flow definition. Each tag consists of a key and a value, both of which you define.
', 'CreateHubRequest$Tags' => 'Any tags to associate with the hub.
', 'CreateHumanTaskUiRequest$Tags' => 'An array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define.
', 'CreateHyperParameterTuningJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
', 'CreateImageRequest$Tags' => 'A list of tags to apply to the image.
', 'CreateInferenceComponentInput$Tags' => 'A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference.
', 'CreateInferenceExperimentRequest$Tags' => 'Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
', 'CreateInferenceRecommendationsJobRequest$Tags' => 'The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.
', 'CreateLabelingJobRequest$Tags' => 'An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelBiasJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelCardRequest$Tags' => 'Key-value pairs used to manage metadata for model cards.
', 'CreateModelExplainabilityJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateModelPackageGroupInput$Tags' => 'A list of key value pairs associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'CreateModelPackageInput$Tags' => 'A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply ModelPackageGroupName
, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply a tag
argument.
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateMonitoringScheduleRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateNotebookInstanceInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreatePipelineRequest$Tags' => 'A list of tags to apply to the created pipeline.
', 'CreateProcessingJobRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateProjectInput$Tags' => 'An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'CreateSpaceRequest$Tags' => 'Tags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search
API.
Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
', 'CreateTrainingJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateTransformJobRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateTrialComponentRequest$Tags' => 'A list of tags to associate with the component. You can use Search API to search on the tags.
', 'CreateTrialRequest$Tags' => 'A list of tags to associate with the trial. You can use Search API to search on the tags.
', 'CreateUserProfileRequest$Tags' => 'Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.
', 'CreateWorkforceRequest$Tags' => 'An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.
', 'CreateWorkteamRequest$Tags' => 'An array of key-value pairs.
For more information, see Resource Tag and Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'DescribeLabelingJobResponse$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'Endpoint$Tags' => 'A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'Experiment$Tags' => 'The list of tags that are associated with the experiment. You can use Search API to search on the tags.
', 'FeatureGroup$Tags' => 'Tags used to define a FeatureGroup
.
The tags associated with a hyperparameter tuning job. For more information see Tagging Amazon Web Services resources.
', 'ImportHubContentRequest$Tags' => 'Any tags associated with the hub content.
', 'ListTagsOutput$Tags' => 'An array of Tag
objects, each with a tag key and a value.
A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'ModelCard$Tags' => 'Key-value pairs used to manage metadata for the model card.
', 'ModelDashboardModelCard$Tags' => 'The tags associated with a model card.
', 'ModelPackage$Tags' => 'A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'ModelPackageGroup$Tags' => 'A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'MonitoringSchedule$Tags' => 'A list of the tags associated with the monitoring schedlue. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'Pipeline$Tags' => 'A list of tags that apply to the pipeline.
', 'ProcessingJob$Tags' => 'An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'Project$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'RegisterDevicesRequest$Tags' => 'The tags associated with devices.
', 'TrainingJob$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'TransformJob$Tags' => 'A list of tags associated with the transform job.
', 'Trial$Tags' => 'The list of tags that are associated with the trial. You can use Search API to search on the tags.
', 'TrialComponent$Tags' => 'The list of tags that are associated with the component. You can use Search API to search on the tags.
', 'UpdateProjectInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see Amazon Web Services Service Catalog Tag Update Constraints.
', ], ], 'TagValue' => [ 'base' => NULL, 'refs' => [ 'Tag$Value' => 'The tag value.
', ], ], 'TargetAttributeName' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$TargetAttributeName' => 'The name of the target variable in supervised learning, usually represented by \'y\'.
', 'TabularJobConfig$TargetAttributeName' => 'The name of the target variable in supervised learning, usually represented by \'y\'.
', 'TimeSeriesConfig$TargetAttributeName' => 'The name of the column representing the target variable that you want to predict for each item in your dataset. The data type of the target variable must be numerical.
', ], ], 'TargetDevice' => [ 'base' => NULL, 'refs' => [ 'CompilationJobSummary$CompilationTargetDevice' => 'The type of device that the model will run on after the compilation job has completed.
', 'OutputConfig$TargetDevice' => 'Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform
.
Currently ml_trn1
is available only in US East (N. Virginia) Region, and ml_inf2
is available only in US East (Ohio) Region.
The name of the column used to provide the class labels. It should not be same as the content column.
', ], ], 'TargetObjectiveMetricValue' => [ 'base' => NULL, 'refs' => [ 'TuningJobCompletionCriteria$TargetObjectiveMetricValue' => 'The value of the objective metric.
', ], ], 'TargetPlatform' => [ 'base' => 'Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice
.
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice
.
The following examples show how to configure the TargetPlatform
and CompilerOptions
JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"},
"CompilerOptions": {\'mattr\': [\'+neon\']}
Jetson TX2
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"},
"CompilerOptions": {\'gpu-code\': \'sm_62\', \'trt-ver\': \'6.0.1\', \'cuda-ver\': \'10.0\'}
EC2 m5.2xlarge instance OS
"TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"},
"CompilerOptions": {\'mcpu\': \'skylake-avx512\'}
RK3399
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}
ARMv7 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},
"CompilerOptions": {\'ANDROID_PLATFORM\': 25, \'mattr\': [\'+neon\']}
ARMv8 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"},
"CompilerOptions": {\'ANDROID_PLATFORM\': 29}
The type of accelerator that the model will run on after the compilation job has completed.
', 'TargetPlatform$Accelerator' => 'Specifies a target platform accelerator (optional).
NVIDIA
: Nvidia graphics processing unit. It also requires gpu-code
, trt-ver
, cuda-ver
compiler options
MALI
: ARM Mali graphics processor
INTEL_GRAPHICS
: Integrated Intel graphics
The type of architecture that the model will run on after the compilation job has completed.
', 'TargetPlatform$Arch' => 'Specifies a target platform architecture.
X86_64
: 64-bit version of the x86 instruction set.
X86
: 32-bit version of the x86 instruction set.
ARM64
: ARMv8 64-bit CPU.
ARM_EABIHF
: ARMv7 32-bit, Hard Float.
ARM_EABI
: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.
The type of OS that the model will run on after the compilation job has completed.
', 'TargetPlatform$Os' => 'Specifies a target platform OS.
LINUX
: Linux-based operating systems.
ANDROID
: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM
compiler option. For example, "CompilerOptions": {\'ANDROID_PLATFORM\': 28}
A target tracking scaling policy. Includes support for predefined or customized metrics.
When using the PutScalingPolicy API, this parameter is required when you are creating a policy with the policy type TargetTrackingScaling
.
A target tracking scaling policy. Includes support for predefined or customized metrics.
', ], ], 'TaskAvailabilityLifetimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$TaskAvailabilityLifetimeInSeconds' => 'The length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.
If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).
If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
The variant\'s capacity.
', 'PendingProductionVariantSummary$CurrentInstanceCount' => 'The number of instances associated with the variant.
', 'PendingProductionVariantSummary$DesiredInstanceCount' => 'The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
', 'ProductionVariantSummary$CurrentInstanceCount' => 'The number of instances associated with the variant.
', 'ProductionVariantSummary$DesiredInstanceCount' => 'The number of instances requested in the UpdateEndpointWeightsAndCapacities
request.
The number of instances of the type specified by InstanceType
.
A description of the task for your human workers.
', ], ], 'TaskInput' => [ 'base' => NULL, 'refs' => [ 'RenderableTask$Input' => 'A JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable task.input
. For example, if you define a variable task.input.text
in your template, you can supply the variable in the JSON object as "text": "sample text"
.
Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.
', ], ], 'TaskTimeLimitInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$TaskTimeLimitInSeconds' => 'The amount of time that a worker has to complete a task.
If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).
If you create a labeling job using a built-in task type the maximum for this parameter depends on the task type you use:
For image and text labeling jobs, the maximum is 8 hours (28,800 seconds).
For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
A title for the task for your human workers.
', ], ], 'TemplateContent' => [ 'base' => NULL, 'refs' => [ 'UiTemplate$Content' => 'The content of the Liquid template for the worker user interface.
', ], ], 'TemplateContentSha256' => [ 'base' => NULL, 'refs' => [ 'UiTemplateInfo$ContentSha256' => 'The SHA-256 digest of the contents of the template.
', ], ], 'TemplateUrl' => [ 'base' => NULL, 'refs' => [ 'UiTemplateInfo$Url' => 'The URL for the user interface template.
', ], ], 'TensorBoardAppSettings' => [ 'base' => 'The TensorBoard app settings.
', 'refs' => [ 'UserSettings$TensorBoardAppSettings' => 'The TensorBoard app settings.
', ], ], 'TensorBoardOutputConfig' => [ 'base' => 'Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.
', 'refs' => [ 'CreateTrainingJobRequest$TensorBoardOutputConfig' => NULL, 'DescribeTrainingJobResponse$TensorBoardOutputConfig' => NULL, 'TrainingJob$TensorBoardOutputConfig' => NULL, ], ], 'TenthFractionsOfACent' => [ 'base' => NULL, 'refs' => [ 'USD$TenthFractionsOfACent' => 'Fractions of a cent, in tenths.
', ], ], 'TerminationWaitInSeconds' => [ 'base' => NULL, 'refs' => [ 'BlueGreenUpdatePolicy$TerminationWaitInSeconds' => 'Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0.
', ], ], 'TextClassificationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the text classification problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TextClassificationJobConfig' => 'Settings used to configure an AutoML job V2 for the text classification problem type.
', ], ], 'TextGenerationHyperParameterKey' => [ 'base' => NULL, 'refs' => [ 'TextGenerationHyperParameters$key' => NULL, ], ], 'TextGenerationHyperParameterValue' => [ 'base' => NULL, 'refs' => [ 'TextGenerationHyperParameters$value' => NULL, ], ], 'TextGenerationHyperParameters' => [ 'base' => NULL, 'refs' => [ 'TextGenerationJobConfig$TextGenerationHyperParameters' => 'The hyperparameters used to configure and optimize the learning process of the base model. You can set any combination of the following hyperparameters for all base models. For more information on each supported hyperparameter, see Optimize the learning process of your text generation models with hyperparameters.
"epochCount"
: The number of times the model goes through the entire training dataset. Its value should be a string containing an integer value within the range of "1" to "10".
"batchSize"
: The number of data samples used in each iteration of training. Its value should be a string containing an integer value within the range of "1" to "64".
"learningRate"
: The step size at which a model\'s parameters are updated during training. Its value should be a string containing a floating-point value within the range of "0" to "1".
"learningRateWarmupSteps"
: The number of training steps during which the learning rate gradually increases before reaching its target or maximum value. Its value should be a string containing an integer value within the range of "0" to "250".
Here is an example where all four hyperparameters are configured.
{ "epochCount":"5", "learningRate":"0.5", "batchSize": "32", "learningRateWarmupSteps": "10" }
The collection of settings used by an AutoML job V2 for the text generation problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
Settings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning) problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
The resolved attributes specific to the text generation problem type.
', 'refs' => [ 'AutoMLProblemTypeResolvedAttributes$TextGenerationResolvedAttributes' => 'The resolved attributes for the text generation problem type.
', ], ], 'ThingName' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$IotThingName' => 'The Amazon Web Services Internet of Things (IoT) object thing name associated with the device.
', 'Device$IotThingName' => 'Amazon Web Services Internet of Things (IoT) object name.
', 'DeviceSummary$IotThingName' => 'The Amazon Web Services Internet of Things (IoT) object thing name associated with the device..
', ], ], 'ThroughputConfig' => [ 'base' => 'Used to set feature group throughput configuration. There are two modes: ON_DEMAND
and PROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use the Standard
tier online store.
Active throughput configuration of the feature group. Used to set feature group throughput configuration. There are two modes: ON_DEMAND
and PROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use the Standard
tier online store.
The new throughput configuration for the feature group. You can switch between on-demand and provisioned modes or update the read / write capacity of provisioned feature groups. You can switch a feature group to on-demand only once in a 24 hour period.
', 'refs' => [ 'UpdateFeatureGroupRequest$ThroughputConfig' => NULL, ], ], 'ThroughputMode' => [ 'base' => NULL, 'refs' => [ 'ThroughputConfig$ThroughputMode' => 'The mode used for your feature group throughput: ON_DEMAND
or PROVISIONED
.
The mode used for your feature group throughput: ON_DEMAND
or PROVISIONED
.
Target throughput mode of the feature group. Throughput update is an asynchronous operation, and the outcome should be monitored by polling LastUpdateStatus
field in DescribeFeatureGroup
response. You cannot update a feature group\'s throughput while another update is in progress.
The collection of components that defines the time-series.
', 'refs' => [ 'TimeSeriesForecastingJobConfig$TimeSeriesConfig' => 'The collection of components that defines the time-series.
', ], ], 'TimeSeriesForecastingJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TimeSeriesForecastingJobConfig' => 'Settings used to configure an AutoML job V2 for the time-series forecasting problem type.
', ], ], 'TimeSeriesForecastingSettings' => [ 'base' => 'Time series forecast settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$TimeSeriesForecastingSettings' => 'Time series forecast settings for the SageMaker Canvas application.
', ], ], 'TimeSeriesTransformations' => [ 'base' => 'Transformations allowed on the dataset. Supported transformations are Filling
and Aggregation
. Filling
specifies how to add values to missing values in the dataset. Aggregation
defines how to aggregate data that does not align with forecast frequency.
The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
', ], ], 'Timestamp' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$CreationTime' => 'When the action was created.
', 'ActionSummary$LastModifiedTime' => 'When the action was last modified.
', 'AppImageConfigDetails$CreationTime' => 'When the AppImageConfig was created.
', 'AppImageConfigDetails$LastModifiedTime' => 'When the AppImageConfig was last modified.
', 'ArtifactSummary$CreationTime' => 'When the artifact was created.
', 'ArtifactSummary$LastModifiedTime' => 'When the artifact was last modified.
', 'AssociationSummary$CreationTime' => 'When the association was created.
', 'AutoMLCandidate$CreationTime' => 'The creation time.
', 'AutoMLCandidate$EndTime' => 'The end time.
', 'AutoMLCandidate$LastModifiedTime' => 'The last modified time.
', 'AutoMLJobSummary$CreationTime' => 'When the AutoML job was created.
', 'AutoMLJobSummary$EndTime' => 'The end time of an AutoML job.
', 'AutoMLJobSummary$LastModifiedTime' => 'When the AutoML job was last modified.
', 'ClusterNodeDetails$LaunchTime' => 'The time when the instance is launched.
', 'ClusterNodeSummary$LaunchTime' => 'The time when the instance is launched.
', 'ClusterSummary$CreationTime' => 'The time when the SageMaker HyperPod cluster is created.
', 'CompilationJobSummary$CompilationStartTime' => 'The time when the model compilation job started.
', 'CompilationJobSummary$CompilationEndTime' => 'The time when the model compilation job completed.
', 'ContextSummary$CreationTime' => 'When the context was created.
', 'ContextSummary$LastModifiedTime' => 'When the context was last modified.
', 'CreateTrialComponentRequest$StartTime' => 'When the component started.
', 'CreateTrialComponentRequest$EndTime' => 'When the component ended.
', 'DebugRuleEvaluationStatus$LastModifiedTime' => 'Timestamp when the rule evaluation status was last modified.
', 'DeployedImage$ResolutionTime' => 'The date and time when the image path for the model resolved to the ResolvedImage
When the action was created.
', 'DescribeActionResponse$LastModifiedTime' => 'When the action was last modified.
', 'DescribeAppImageConfigResponse$CreationTime' => 'When the AppImageConfig was created.
', 'DescribeAppImageConfigResponse$LastModifiedTime' => 'When the AppImageConfig was last modified.
', 'DescribeAppResponse$LastHealthCheckTimestamp' => 'The timestamp of the last health check.
', 'DescribeAppResponse$LastUserActivityTimestamp' => 'The timestamp of the last user\'s activity. LastUserActivityTimestamp
is also updated when SageMaker performs health checks without user activity. As a result, this value is set to the same value as LastHealthCheckTimestamp
.
The creation time.
', 'DescribeArtifactResponse$CreationTime' => 'When the artifact was created.
', 'DescribeArtifactResponse$LastModifiedTime' => 'When the artifact was last modified.
', 'DescribeAutoMLJobResponse$CreationTime' => 'Returns the creation time of the AutoML job.
', 'DescribeAutoMLJobResponse$EndTime' => 'Returns the end time of the AutoML job.
', 'DescribeAutoMLJobResponse$LastModifiedTime' => 'Returns the job\'s last modified time.
', 'DescribeAutoMLJobV2Response$CreationTime' => 'Returns the creation time of the AutoML job V2.
', 'DescribeAutoMLJobV2Response$EndTime' => 'Returns the end time of the AutoML job V2.
', 'DescribeAutoMLJobV2Response$LastModifiedTime' => 'Returns the job\'s last modified time.
', 'DescribeClusterResponse$CreationTime' => 'The time when the SageMaker Cluster is created.
', 'DescribeCompilationJobResponse$CompilationStartTime' => 'The time when the model compilation job started the CompilationJob
instances.
You are billed for the time between this timestamp and the timestamp in the CompilationEndTime
field. In Amazon CloudWatch Logs, the start time might be later than this time. That\'s because it takes time to download the compilation job, which depends on the size of the compilation job container.
The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job\'s model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker detected that the job failed.
', 'DescribeContextResponse$CreationTime' => 'When the context was created.
', 'DescribeContextResponse$LastModifiedTime' => 'When the context was last modified.
', 'DescribeDataQualityJobDefinitionResponse$CreationTime' => 'The time that the data quality monitoring job definition was created.
', 'DescribeDeviceFleetResponse$CreationTime' => 'Timestamp of when the device fleet was created.
', 'DescribeDeviceFleetResponse$LastModifiedTime' => 'Timestamp of when the device fleet was last updated.
', 'DescribeDeviceResponse$RegistrationTime' => 'The timestamp of the last registration or de-reregistration.
', 'DescribeDeviceResponse$LatestHeartbeat' => 'The last heartbeat received from the device.
', 'DescribeEdgeDeploymentPlanResponse$CreationTime' => 'The time when the edge deployment plan was created.
', 'DescribeEdgeDeploymentPlanResponse$LastModifiedTime' => 'The time when the edge deployment plan was last updated.
', 'DescribeEdgePackagingJobResponse$CreationTime' => 'The timestamp of when the packaging job was created.
', 'DescribeEdgePackagingJobResponse$LastModifiedTime' => 'The timestamp of when the job was last updated.
', 'DescribeEndpointConfigOutput$CreationTime' => 'A timestamp that shows when the endpoint configuration was created.
', 'DescribeEndpointOutput$CreationTime' => 'A timestamp that shows when the endpoint was created.
', 'DescribeEndpointOutput$LastModifiedTime' => 'A timestamp that shows when the endpoint was last modified.
', 'DescribeExperimentResponse$CreationTime' => 'When the experiment was created.
', 'DescribeExperimentResponse$LastModifiedTime' => 'When the experiment was last modified.
', 'DescribeFlowDefinitionResponse$CreationTime' => 'The timestamp when the flow definition was created.
', 'DescribeHubContentResponse$CreationTime' => 'The date and time that hub content was created.
', 'DescribeHubResponse$CreationTime' => 'The date and time that the hub was created.
', 'DescribeHubResponse$LastModifiedTime' => 'The date and time that the hub was last modified.
', 'DescribeHumanTaskUiResponse$CreationTime' => 'The timestamp when the human task user interface was created.
', 'DescribeHyperParameterTuningJobResponse$CreationTime' => 'The date and time that the tuning job started.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningEndTime' => 'The date and time that the tuning job ended.
', 'DescribeHyperParameterTuningJobResponse$LastModifiedTime' => 'The date and time that the status of the tuning job was modified.
', 'DescribeImageResponse$CreationTime' => 'When the image was created.
', 'DescribeImageResponse$LastModifiedTime' => 'When the image was last modified.
', 'DescribeImageVersionResponse$CreationTime' => 'When the version was created.
', 'DescribeImageVersionResponse$LastModifiedTime' => 'When the version was last modified.
', 'DescribeInferenceComponentOutput$CreationTime' => 'The time when the inference component was created.
', 'DescribeInferenceComponentOutput$LastModifiedTime' => 'The time when the inference component was last updated.
', 'DescribeInferenceExperimentResponse$CreationTime' => 'The timestamp at which you created the inference experiment.
', 'DescribeInferenceExperimentResponse$CompletionTime' => 'The timestamp at which the inference experiment was completed.
', 'DescribeInferenceExperimentResponse$LastModifiedTime' => 'The timestamp at which you last modified the inference experiment.
', 'DescribeInferenceRecommendationsJobResponse$CompletionTime' => 'A timestamp that shows when the job completed.
', 'DescribeLabelingJobResponse$CreationTime' => 'The date and time that the labeling job was created.
', 'DescribeLabelingJobResponse$LastModifiedTime' => 'The date and time that the labeling job was last updated.
', 'DescribeLineageGroupResponse$CreationTime' => 'The creation time of lineage group.
', 'DescribeLineageGroupResponse$LastModifiedTime' => 'The last modified time of the lineage group.
', 'DescribeModelBiasJobDefinitionResponse$CreationTime' => 'The time at which the model bias job was created.
', 'DescribeModelCardExportJobResponse$CreatedAt' => 'The date and time that the model export job was created.
', 'DescribeModelCardExportJobResponse$LastModifiedAt' => 'The date and time that the model export job was last modified.
', 'DescribeModelCardResponse$CreationTime' => 'The date and time the model card was created.
', 'DescribeModelCardResponse$LastModifiedTime' => 'The date and time the model card was last modified.
', 'DescribeModelExplainabilityJobDefinitionResponse$CreationTime' => 'The time at which the model explainability job was created.
', 'DescribeModelOutput$CreationTime' => 'A timestamp that shows when the model was created.
', 'DescribeModelPackageOutput$LastModifiedTime' => 'The last time that the model package was modified.
', 'DescribeModelQualityJobDefinitionResponse$CreationTime' => 'The time at which the model quality job was created.
', 'DescribeMonitoringScheduleResponse$CreationTime' => 'The time at which the monitoring job was created.
', 'DescribeMonitoringScheduleResponse$LastModifiedTime' => 'The time at which the monitoring job was last modified.
', 'DescribePipelineDefinitionForExecutionResponse$CreationTime' => 'The time when the pipeline was created.
', 'DescribePipelineExecutionResponse$CreationTime' => 'The time when the pipeline execution was created.
', 'DescribePipelineExecutionResponse$LastModifiedTime' => 'The time when the pipeline execution was modified last.
', 'DescribePipelineResponse$CreationTime' => 'The time when the pipeline was created.
', 'DescribePipelineResponse$LastModifiedTime' => 'The time when the pipeline was last modified.
', 'DescribePipelineResponse$LastRunTime' => 'The time when the pipeline was last run.
', 'DescribeProcessingJobResponse$ProcessingEndTime' => 'The time at which the processing job completed.
', 'DescribeProcessingJobResponse$ProcessingStartTime' => 'The time at which the processing job started.
', 'DescribeProcessingJobResponse$LastModifiedTime' => 'The time at which the processing job was last modified.
', 'DescribeProcessingJobResponse$CreationTime' => 'The time at which the processing job was created.
', 'DescribeProjectOutput$CreationTime' => 'The time when the project was created.
', 'DescribeProjectOutput$LastModifiedTime' => 'The timestamp when project was last modified.
', 'DescribeStudioLifecycleConfigResponse$CreationTime' => 'The creation time of the Amazon SageMaker Studio Lifecycle Configuration.
', 'DescribeStudioLifecycleConfigResponse$LastModifiedTime' => 'This value is equivalent to CreationTime because Amazon SageMaker Studio Lifecycle Configurations are immutable.
', 'DescribeTrainingJobResponse$CreationTime' => 'A timestamp that indicates when the training job was created.
', 'DescribeTrainingJobResponse$TrainingStartTime' => 'Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime
. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last modified.
', 'DescribeTransformJobResponse$CreationTime' => 'A timestamp that shows when the transform Job was created.
', 'DescribeTransformJobResponse$TransformStartTime' => 'Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime
.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime
.
When the component started.
', 'DescribeTrialComponentResponse$EndTime' => 'When the component ended.
', 'DescribeTrialComponentResponse$CreationTime' => 'When the component was created.
', 'DescribeTrialComponentResponse$LastModifiedTime' => 'When the component was last modified.
', 'DescribeTrialResponse$CreationTime' => 'When the trial was created.
', 'DescribeTrialResponse$LastModifiedTime' => 'When the trial was last modified.
', 'DeviceDeploymentSummary$DeploymentStartTime' => 'The time when the deployment on the device started.
', 'DeviceFleetSummary$CreationTime' => 'Timestamp of when the device fleet was created.
', 'DeviceFleetSummary$LastModifiedTime' => 'Timestamp of when the device fleet was last updated.
', 'DeviceSummary$RegistrationTime' => 'The timestamp of the last registration or de-reregistration.
', 'DeviceSummary$LatestHeartbeat' => 'The last heartbeat received from the device.
', 'EdgeDeploymentPlanSummary$CreationTime' => 'The time when the edge deployment plan was created.
', 'EdgeDeploymentPlanSummary$LastModifiedTime' => 'The time when the edge deployment plan was last updated.
', 'EdgeDeploymentStatus$EdgeDeploymentStageStartTime' => 'The time when the deployment API started.
', 'EdgeModel$LatestSampleTime' => 'The timestamp of the last data sample taken.
', 'EdgeModel$LatestInference' => 'The timestamp of the last inference that was made.
', 'EdgePackagingJobSummary$CreationTime' => 'The timestamp of when the job was created.
', 'EdgePackagingJobSummary$LastModifiedTime' => 'The timestamp of when the edge packaging job was last updated.
', 'Endpoint$CreationTime' => 'The time that the endpoint was created.
', 'Endpoint$LastModifiedTime' => 'The last time the endpoint was modified.
', 'EndpointConfigSummary$CreationTime' => 'A timestamp that shows when the endpoint configuration was created.
', 'EndpointSummary$CreationTime' => 'A timestamp that shows when the endpoint was created.
', 'EndpointSummary$LastModifiedTime' => 'A timestamp that shows when the endpoint was last modified.
', 'Experiment$CreationTime' => 'When the experiment was created.
', 'Experiment$LastModifiedTime' => 'When the experiment was last modified.
', 'ExperimentSummary$CreationTime' => 'When the experiment was created.
', 'ExperimentSummary$LastModifiedTime' => 'When the experiment was last modified.
', 'FeatureGroupSummary$CreationTime' => 'A timestamp indicating the time of creation time of the FeatureGroup
.
The timestamp when SageMaker created the flow definition.
', 'GetDeviceFleetReportResponse$ReportGenerated' => 'Timestamp of when the report was generated.
', 'HubContentInfo$CreationTime' => 'The date and time that the hub content was created.
', 'HubInfo$CreationTime' => 'The date and time that the hub was created.
', 'HubInfo$LastModifiedTime' => 'The date and time that the hub was last modified.
', 'HumanTaskUiSummary$CreationTime' => 'A timestamp when SageMaker created the human task user interface.
', 'HyperParameterTrainingJobSummary$CreationTime' => 'The date and time that the training job was created.
', 'HyperParameterTrainingJobSummary$TrainingStartTime' => 'The date and time that the training job started.
', 'HyperParameterTrainingJobSummary$TrainingEndTime' => 'Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
The time in timestamp format that AMT detected model convergence, as defined by a lack of significant improvement over time based on criteria developed over a wide range of diverse benchmarking tests.
', 'HyperParameterTuningJobSearchEntity$CreationTime' => 'The time that a hyperparameter tuning job was created.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningEndTime' => 'The time that a hyperparameter tuning job ended.
', 'HyperParameterTuningJobSearchEntity$LastModifiedTime' => 'The time that a hyperparameter tuning job was last modified.
', 'HyperParameterTuningJobSummary$CreationTime' => 'The date and time that the tuning job was created.
', 'HyperParameterTuningJobSummary$HyperParameterTuningEndTime' => 'The date and time that the tuning job ended.
', 'HyperParameterTuningJobSummary$LastModifiedTime' => 'The date and time that the tuning job was modified.
', 'Image$CreationTime' => 'When the image was created.
', 'Image$LastModifiedTime' => 'When the image was last modified.
', 'ImageVersion$CreationTime' => 'When the version was created.
', 'ImageVersion$LastModifiedTime' => 'When the version was last modified.
', 'InferenceComponentSummary$CreationTime' => 'The time when the inference component was created.
', 'InferenceComponentSummary$LastModifiedTime' => 'The time when the inference component was last updated.
', 'InferenceExperimentSchedule$StartTime' => 'The timestamp at which the inference experiment started or will start.
', 'InferenceExperimentSchedule$EndTime' => 'The timestamp at which the inference experiment ended or will end.
', 'InferenceExperimentSummary$CreationTime' => 'The timestamp at which the inference experiment was created.
', 'InferenceExperimentSummary$CompletionTime' => 'The timestamp at which the inference experiment was completed.
', 'InferenceExperimentSummary$LastModifiedTime' => 'The timestamp when you last modified the inference experiment.
', 'InferenceRecommendationsJob$CompletionTime' => 'A timestamp that shows when the job completed.
', 'LabelingJobForWorkteamSummary$CreationTime' => 'The date and time that the labeling job was created.
', 'LabelingJobSummary$CreationTime' => 'The date and time that the job was created (timestamp).
', 'LabelingJobSummary$LastModifiedTime' => 'The date and time that the job was last modified (timestamp).
', 'LineageGroupSummary$CreationTime' => 'The creation time of the lineage group summary.
', 'LineageGroupSummary$LastModifiedTime' => 'The last modified time of the lineage group summary.
', 'ListActionsRequest$CreatedAfter' => 'A filter that returns only actions created on or after the specified time.
', 'ListActionsRequest$CreatedBefore' => 'A filter that returns only actions created on or before the specified time.
', 'ListAppImageConfigsRequest$CreationTimeBefore' => 'A filter that returns only AppImageConfigs created on or before the specified time.
', 'ListAppImageConfigsRequest$CreationTimeAfter' => 'A filter that returns only AppImageConfigs created on or after the specified time.
', 'ListAppImageConfigsRequest$ModifiedTimeBefore' => 'A filter that returns only AppImageConfigs modified on or before the specified time.
', 'ListAppImageConfigsRequest$ModifiedTimeAfter' => 'A filter that returns only AppImageConfigs modified on or after the specified time.
', 'ListArtifactsRequest$CreatedAfter' => 'A filter that returns only artifacts created on or after the specified time.
', 'ListArtifactsRequest$CreatedBefore' => 'A filter that returns only artifacts created on or before the specified time.
', 'ListAssociationsRequest$CreatedAfter' => 'A filter that returns only associations created on or after the specified time.
', 'ListAssociationsRequest$CreatedBefore' => 'A filter that returns only associations created on or before the specified time.
', 'ListAutoMLJobsRequest$CreationTimeAfter' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$CreationTimeBefore' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$LastModifiedTimeAfter' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$LastModifiedTimeBefore' => 'Request a list of jobs, using a filter for time.
', 'ListClusterNodesRequest$CreationTimeAfter' => 'A filter that returns nodes in a SageMaker HyperPod cluster created after the specified time. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
YYYY-MM-DDThh:mm:ss.sssTZD
(UTC), for example, 2014-10-01T20:30:00.000Z
YYYY-MM-DDThh:mm:ss.sssTZD
(with offset), for example, 2014-10-01T12:30:00.000-08:00
YYYY-MM-DD
, for example, 2014-10-01
Unix time in seconds, for example, 1412195400
. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
', 'ListClusterNodesRequest$CreationTimeBefore' => 'A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for CreationTimeAfter
. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
Set a start time for the time range during which you want to list SageMaker HyperPod clusters. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
YYYY-MM-DDThh:mm:ss.sssTZD
(UTC), for example, 2014-10-01T20:30:00.000Z
YYYY-MM-DDThh:mm:ss.sssTZD
(with offset), for example, 2014-10-01T12:30:00.000-08:00
YYYY-MM-DD
, for example, 2014-10-01
Unix time in seconds, for example, 1412195400
. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
', 'ListClustersRequest$CreationTimeBefore' => 'Set an end time for the time range during which you want to list SageMaker HyperPod clusters. A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for CreationTimeAfter
. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
A filter that returns only Git repositories that were last modified after the specified time.
', 'ListCodeRepositoriesInput$LastModifiedTimeBefore' => 'A filter that returns only Git repositories that were last modified before the specified time.
', 'ListContextsRequest$CreatedAfter' => 'A filter that returns only contexts created on or after the specified time.
', 'ListContextsRequest$CreatedBefore' => 'A filter that returns only contexts created on or before the specified time.
', 'ListDataQualityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only data quality monitoring job definitions created before the specified time.
', 'ListDataQualityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only data quality monitoring job definitions created after the specified time.
', 'ListDeviceFleetsRequest$CreationTimeAfter' => 'Filter fleets where packaging job was created after specified time.
', 'ListDeviceFleetsRequest$CreationTimeBefore' => 'Filter fleets where the edge packaging job was created before specified time.
', 'ListDeviceFleetsRequest$LastModifiedTimeAfter' => 'Select fleets where the job was updated after X
', 'ListDeviceFleetsRequest$LastModifiedTimeBefore' => 'Select fleets where the job was updated before X
', 'ListDevicesRequest$LatestHeartbeatAfter' => 'Select fleets where the job was updated after X
', 'ListEdgeDeploymentPlansRequest$CreationTimeAfter' => 'Selects edge deployment plans created after this time.
', 'ListEdgeDeploymentPlansRequest$CreationTimeBefore' => 'Selects edge deployment plans created before this time.
', 'ListEdgeDeploymentPlansRequest$LastModifiedTimeAfter' => 'Selects edge deployment plans that were last updated after this time.
', 'ListEdgeDeploymentPlansRequest$LastModifiedTimeBefore' => 'Selects edge deployment plans that were last updated before this time.
', 'ListEdgePackagingJobsRequest$CreationTimeAfter' => 'Select jobs where the job was created after specified time.
', 'ListEdgePackagingJobsRequest$CreationTimeBefore' => 'Select jobs where the job was created before specified time.
', 'ListEdgePackagingJobsRequest$LastModifiedTimeAfter' => 'Select jobs where the job was updated after specified time.
', 'ListEdgePackagingJobsRequest$LastModifiedTimeBefore' => 'Select jobs where the job was updated before specified time.
', 'ListEndpointConfigsInput$CreationTimeBefore' => 'A filter that returns only endpoint configurations created before the specified time (timestamp).
', 'ListEndpointConfigsInput$CreationTimeAfter' => 'A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).
', 'ListEndpointsInput$CreationTimeBefore' => 'A filter that returns only endpoints that were created before the specified time (timestamp).
', 'ListEndpointsInput$CreationTimeAfter' => 'A filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).
', 'ListEndpointsInput$LastModifiedTimeBefore' => 'A filter that returns only endpoints that were modified before the specified timestamp.
', 'ListEndpointsInput$LastModifiedTimeAfter' => 'A filter that returns only endpoints that were modified after the specified timestamp.
', 'ListExperimentsRequest$CreatedAfter' => 'A filter that returns only experiments created after the specified time.
', 'ListExperimentsRequest$CreatedBefore' => 'A filter that returns only experiments created before the specified time.
', 'ListFlowDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only flow definitions with a creation time greater than or equal to the specified timestamp.
', 'ListFlowDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only flow definitions that were created before the specified timestamp.
', 'ListHubContentVersionsRequest$CreationTimeBefore' => 'Only list hub content versions that were created before the time specified.
', 'ListHubContentVersionsRequest$CreationTimeAfter' => 'Only list hub content versions that were created after the time specified.
', 'ListHubContentsRequest$CreationTimeBefore' => 'Only list hub content that was created before the time specified.
', 'ListHubContentsRequest$CreationTimeAfter' => 'Only list hub content that was created after the time specified.
', 'ListHubsRequest$CreationTimeBefore' => 'Only list hubs that were created before the time specified.
', 'ListHubsRequest$CreationTimeAfter' => 'Only list hubs that were created after the time specified.
', 'ListHubsRequest$LastModifiedTimeBefore' => 'Only list hubs that were last modified before the time specified.
', 'ListHubsRequest$LastModifiedTimeAfter' => 'Only list hubs that were last modified after the time specified.
', 'ListHumanTaskUisRequest$CreationTimeAfter' => 'A filter that returns only human task user interfaces with a creation time greater than or equal to the specified timestamp.
', 'ListHumanTaskUisRequest$CreationTimeBefore' => 'A filter that returns only human task user interfaces that were created before the specified timestamp.
', 'ListHyperParameterTuningJobsRequest$CreationTimeAfter' => 'A filter that returns only tuning jobs that were created after the specified time.
', 'ListHyperParameterTuningJobsRequest$CreationTimeBefore' => 'A filter that returns only tuning jobs that were created before the specified time.
', 'ListHyperParameterTuningJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only tuning jobs that were modified after the specified time.
', 'ListHyperParameterTuningJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only tuning jobs that were modified before the specified time.
', 'ListImageVersionsRequest$CreationTimeAfter' => 'A filter that returns only versions created on or after the specified time.
', 'ListImageVersionsRequest$CreationTimeBefore' => 'A filter that returns only versions created on or before the specified time.
', 'ListImageVersionsRequest$LastModifiedTimeAfter' => 'A filter that returns only versions modified on or after the specified time.
', 'ListImageVersionsRequest$LastModifiedTimeBefore' => 'A filter that returns only versions modified on or before the specified time.
', 'ListImagesRequest$CreationTimeAfter' => 'A filter that returns only images created on or after the specified time.
', 'ListImagesRequest$CreationTimeBefore' => 'A filter that returns only images created on or before the specified time.
', 'ListImagesRequest$LastModifiedTimeAfter' => 'A filter that returns only images modified on or after the specified time.
', 'ListImagesRequest$LastModifiedTimeBefore' => 'A filter that returns only images modified on or before the specified time.
', 'ListInferenceComponentsInput$CreationTimeBefore' => 'Filters the results to only those inference components that were created before the specified time.
', 'ListInferenceComponentsInput$CreationTimeAfter' => 'Filters the results to only those inference components that were created after the specified time.
', 'ListInferenceComponentsInput$LastModifiedTimeBefore' => 'Filters the results to only those inference components that were updated before the specified time.
', 'ListInferenceComponentsInput$LastModifiedTimeAfter' => 'Filters the results to only those inference components that were updated after the specified time.
', 'ListInferenceExperimentsRequest$CreationTimeAfter' => 'Selects inference experiments which were created after this timestamp.
', 'ListInferenceExperimentsRequest$CreationTimeBefore' => 'Selects inference experiments which were created before this timestamp.
', 'ListInferenceExperimentsRequest$LastModifiedTimeAfter' => 'Selects inference experiments which were last modified after this timestamp.
', 'ListInferenceExperimentsRequest$LastModifiedTimeBefore' => 'Selects inference experiments which were last modified before this timestamp.
', 'ListLabelingJobsForWorkteamRequest$CreationTimeAfter' => 'A filter that returns only labeling jobs created after the specified time (timestamp).
', 'ListLabelingJobsForWorkteamRequest$CreationTimeBefore' => 'A filter that returns only labeling jobs created before the specified time (timestamp).
', 'ListLabelingJobsRequest$CreationTimeAfter' => 'A filter that returns only labeling jobs created after the specified time (timestamp).
', 'ListLabelingJobsRequest$CreationTimeBefore' => 'A filter that returns only labeling jobs created before the specified time (timestamp).
', 'ListLabelingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only labeling jobs modified after the specified time (timestamp).
', 'ListLabelingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only labeling jobs modified before the specified time (timestamp).
', 'ListLineageGroupsRequest$CreatedAfter' => 'A timestamp to filter against lineage groups created after a certain point in time.
', 'ListLineageGroupsRequest$CreatedBefore' => 'A timestamp to filter against lineage groups created before a certain point in time.
', 'ListModelBiasJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model bias jobs created before a specified time.
', 'ListModelBiasJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model bias jobs created after a specified time.
', 'ListModelCardExportJobsRequest$CreationTimeAfter' => 'Only list model card export jobs that were created after the time specified.
', 'ListModelCardExportJobsRequest$CreationTimeBefore' => 'Only list model card export jobs that were created before the time specified.
', 'ListModelCardVersionsRequest$CreationTimeAfter' => 'Only list model card versions that were created after the time specified.
', 'ListModelCardVersionsRequest$CreationTimeBefore' => 'Only list model card versions that were created before the time specified.
', 'ListModelCardsRequest$CreationTimeAfter' => 'Only list model cards that were created after the time specified.
', 'ListModelCardsRequest$CreationTimeBefore' => 'Only list model cards that were created before the time specified.
', 'ListModelExplainabilityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model explainability jobs created before a specified time.
', 'ListModelExplainabilityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model explainability jobs created after a specified time.
', 'ListModelQualityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model quality monitoring job definitions created before the specified time.
', 'ListModelQualityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model quality monitoring job definitions created after the specified time.
', 'ListModelsInput$CreationTimeBefore' => 'A filter that returns only models created before the specified time (timestamp).
', 'ListModelsInput$CreationTimeAfter' => 'A filter that returns only models with a creation time greater than or equal to the specified time (timestamp).
', 'ListMonitoringAlertHistoryRequest$CreationTimeBefore' => 'A filter that returns only alerts created on or before the specified time.
', 'ListMonitoringAlertHistoryRequest$CreationTimeAfter' => 'A filter that returns only alerts created on or after the specified time.
', 'ListMonitoringExecutionsRequest$ScheduledTimeBefore' => 'Filter for jobs scheduled before a specified time.
', 'ListMonitoringExecutionsRequest$ScheduledTimeAfter' => 'Filter for jobs scheduled after a specified time.
', 'ListMonitoringExecutionsRequest$CreationTimeBefore' => 'A filter that returns only jobs created before a specified time.
', 'ListMonitoringExecutionsRequest$CreationTimeAfter' => 'A filter that returns only jobs created after a specified time.
', 'ListMonitoringExecutionsRequest$LastModifiedTimeBefore' => 'A filter that returns only jobs modified after a specified time.
', 'ListMonitoringExecutionsRequest$LastModifiedTimeAfter' => 'A filter that returns only jobs modified before a specified time.
', 'ListMonitoringSchedulesRequest$CreationTimeBefore' => 'A filter that returns only monitoring schedules created before a specified time.
', 'ListMonitoringSchedulesRequest$CreationTimeAfter' => 'A filter that returns only monitoring schedules created after a specified time.
', 'ListMonitoringSchedulesRequest$LastModifiedTimeBefore' => 'A filter that returns only monitoring schedules modified before a specified time.
', 'ListMonitoringSchedulesRequest$LastModifiedTimeAfter' => 'A filter that returns only monitoring schedules modified after a specified time.
', 'ListPipelineExecutionsRequest$CreatedAfter' => 'A filter that returns the pipeline executions that were created after a specified time.
', 'ListPipelineExecutionsRequest$CreatedBefore' => 'A filter that returns the pipeline executions that were created before a specified time.
', 'ListPipelinesRequest$CreatedAfter' => 'A filter that returns the pipelines that were created after a specified time.
', 'ListPipelinesRequest$CreatedBefore' => 'A filter that returns the pipelines that were created before a specified time.
', 'ListProcessingJobsRequest$CreationTimeAfter' => 'A filter that returns only processing jobs created after the specified time.
', 'ListProcessingJobsRequest$CreationTimeBefore' => 'A filter that returns only processing jobs created after the specified time.
', 'ListProcessingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only processing jobs modified after the specified time.
', 'ListProcessingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only processing jobs modified before the specified time.
', 'ListProjectsInput$CreationTimeAfter' => 'A filter that returns the projects that were created after a specified time.
', 'ListProjectsInput$CreationTimeBefore' => 'A filter that returns the projects that were created before a specified time.
', 'ListResourceCatalogsRequest$CreationTimeAfter' => ' Use this parameter to search for ResourceCatalog
s created after a specific date and time.
Use this parameter to search for ResourceCatalog
s created before a specific date and time.
A filter that returns only Lifecycle Configurations created on or before the specified time.
', 'ListStudioLifecycleConfigsRequest$CreationTimeAfter' => 'A filter that returns only Lifecycle Configurations created on or after the specified time.
', 'ListStudioLifecycleConfigsRequest$ModifiedTimeBefore' => 'A filter that returns only Lifecycle Configurations modified before the specified time.
', 'ListStudioLifecycleConfigsRequest$ModifiedTimeAfter' => 'A filter that returns only Lifecycle Configurations modified after the specified time.
', 'ListTrainingJobsRequest$CreationTimeAfter' => 'A filter that returns only training jobs created after the specified time (timestamp).
', 'ListTrainingJobsRequest$CreationTimeBefore' => 'A filter that returns only training jobs created before the specified time (timestamp).
', 'ListTrainingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only training jobs modified after the specified time (timestamp).
', 'ListTrainingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only training jobs modified before the specified time (timestamp).
', 'ListTransformJobsRequest$CreationTimeAfter' => 'A filter that returns only transform jobs created after the specified time.
', 'ListTransformJobsRequest$CreationTimeBefore' => 'A filter that returns only transform jobs created before the specified time.
', 'ListTransformJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only transform jobs modified after the specified time.
', 'ListTransformJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only transform jobs modified before the specified time.
', 'ListTrialComponentsRequest$CreatedAfter' => 'A filter that returns only components created after the specified time.
', 'ListTrialComponentsRequest$CreatedBefore' => 'A filter that returns only components created before the specified time.
', 'ListTrialsRequest$CreatedAfter' => 'A filter that returns only trials created after the specified time.
', 'ListTrialsRequest$CreatedBefore' => 'A filter that returns only trials created before the specified time.
', 'MetricData$Timestamp' => 'The date and time that the algorithm emitted the metric.
', 'Model$CreationTime' => 'A timestamp that indicates when the model was created.
', 'ModelCard$CreationTime' => 'The date and time that the model card was created.
', 'ModelCard$LastModifiedTime' => 'The date and time that the model card was last modified.
', 'ModelCardExportJobSummary$CreatedAt' => 'The date and time that the model card export job was created.
', 'ModelCardExportJobSummary$LastModifiedAt' => 'The date and time that the model card export job was last modified..
', 'ModelCardSummary$CreationTime' => 'The date and time that the model card was created.
', 'ModelCardSummary$LastModifiedTime' => 'The date and time that the model card was last modified.
', 'ModelCardVersionSummary$CreationTime' => 'The date and time that the model card version was created.
', 'ModelCardVersionSummary$LastModifiedTime' => 'The time date and time that the model card version was last modified.
', 'ModelDashboardEndpoint$CreationTime' => 'A timestamp that indicates when the endpoint was created.
', 'ModelDashboardEndpoint$LastModifiedTime' => 'The last time the endpoint was modified.
', 'ModelDashboardModelCard$CreationTime' => 'A timestamp that indicates when the model card was created.
', 'ModelDashboardModelCard$LastModifiedTime' => 'A timestamp that indicates when the model card was last updated.
', 'ModelDashboardMonitoringSchedule$CreationTime' => 'A timestamp that indicates when the monitoring schedule was created.
', 'ModelDashboardMonitoringSchedule$LastModifiedTime' => 'A timestamp that indicates when the monitoring schedule was last updated.
', 'ModelPackage$LastModifiedTime' => 'The last time the model package was modified.
', 'ModelSummary$CreationTime' => 'A timestamp that indicates when the model was created.
', 'MonitoringAlertHistorySummary$CreationTime' => 'A timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert
to OK
, or from OK
to InAlert
.
A timestamp that indicates when a monitor alert was created.
', 'MonitoringAlertSummary$LastModifiedTime' => 'A timestamp that indicates when a monitor alert was last updated.
', 'MonitoringExecutionSummary$ScheduledTime' => 'The time the monitoring job was scheduled.
', 'MonitoringExecutionSummary$CreationTime' => 'The time at which the monitoring job was created.
', 'MonitoringExecutionSummary$LastModifiedTime' => 'A timestamp that indicates the last time the monitoring job was modified.
', 'MonitoringJobDefinitionSummary$CreationTime' => 'The time that the monitoring job was created.
', 'MonitoringSchedule$CreationTime' => 'The time that the monitoring schedule was created.
', 'MonitoringSchedule$LastModifiedTime' => 'The last time the monitoring schedule was changed.
', 'MonitoringScheduleSummary$CreationTime' => 'The creation time of the monitoring schedule.
', 'MonitoringScheduleSummary$LastModifiedTime' => 'The last time the monitoring schedule was modified.
', 'PendingDeploymentSummary$StartTime' => 'The start time of the deployment.
', 'Pipeline$CreationTime' => 'The creation time of the pipeline.
', 'Pipeline$LastModifiedTime' => 'The time that the pipeline was last modified.
', 'Pipeline$LastRunTime' => 'The time when the pipeline was last run.
', 'PipelineExecution$CreationTime' => 'The creation time of the pipeline execution.
', 'PipelineExecution$LastModifiedTime' => 'The time that the pipeline execution was last modified.
', 'PipelineExecutionStep$StartTime' => 'The time that the step started executing.
', 'PipelineExecutionStep$EndTime' => 'The time that the step stopped executing.
', 'PipelineExecutionSummary$StartTime' => 'The start time of the pipeline execution.
', 'PipelineSummary$CreationTime' => 'The creation time of the pipeline.
', 'PipelineSummary$LastModifiedTime' => 'The time that the pipeline was last modified.
', 'PipelineSummary$LastExecutionTime' => 'The last time that a pipeline execution began.
', 'ProcessingJob$ProcessingEndTime' => 'The time that the processing job ended.
', 'ProcessingJob$ProcessingStartTime' => 'The time that the processing job started.
', 'ProcessingJob$LastModifiedTime' => 'The time the processing job was last modified.
', 'ProcessingJob$CreationTime' => 'The time the processing job was created.
', 'ProcessingJobSummary$CreationTime' => 'The time at which the processing job was created.
', 'ProcessingJobSummary$ProcessingEndTime' => 'The time at which the processing job completed.
', 'ProcessingJobSummary$LastModifiedTime' => 'A timestamp that indicates the last time the processing job was modified.
', 'ProductionVariantStatus$StartTime' => 'The start time of the current status change.
', 'ProfilerRuleEvaluationStatus$LastModifiedTime' => 'Timestamp when the rule evaluation status was last modified.
', 'Project$CreationTime' => 'A timestamp specifying when the project was created.
', 'Project$LastModifiedTime' => 'A timestamp container for when the project was last modified.
', 'ProjectSummary$CreationTime' => 'The time that the project was created.
', 'QueryFilters$CreatedBefore' => 'Filter the lineage entities connected to the StartArn
(s) by created date.
Filter the lineage entities connected to the StartArn
(s) after the create date.
Filter the lineage entities connected to the StartArn
(s) before the last modified date.
Filter the lineage entities connected to the StartArn
(s) after the last modified date.
The time the ResourceCatalog
was created.
A timestamp that shows when the training job transitioned to the current secondary status state.
', 'SecondaryStatusTransition$EndTime' => 'A timestamp that shows when the training job transitioned out of this secondary status state into another secondary status state or when the training job has ended.
', 'StudioLifecycleConfigDetails$CreationTime' => 'The creation time of the Amazon SageMaker Studio Lifecycle Configuration.
', 'StudioLifecycleConfigDetails$LastModifiedTime' => 'This value is equivalent to CreationTime because Amazon SageMaker Studio Lifecycle Configurations are immutable.
', 'TrainingJob$CreationTime' => 'A timestamp that indicates when the training job was created.
', 'TrainingJob$TrainingStartTime' => 'Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime
. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last modified.
', 'TrainingJobSummary$CreationTime' => 'A timestamp that shows when the training job was created.
', 'TrainingJobSummary$TrainingEndTime' => 'A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses (Completed
, Failed
, or Stopped
).
Timestamp when the training job was last modified.
', 'TransformJob$CreationTime' => 'A timestamp that shows when the transform Job was created.
', 'TransformJob$TransformStartTime' => 'Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime
.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime
.
A timestamp that shows when the transform Job was created.
', 'TransformJobSummary$TransformEndTime' => 'Indicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.
', 'TransformJobSummary$LastModifiedTime' => 'Indicates when the transform job was last modified.
', 'Trial$CreationTime' => 'When the trial was created.
', 'Trial$LastModifiedTime' => 'Who last modified the trial.
', 'TrialComponent$StartTime' => 'When the component started.
', 'TrialComponent$EndTime' => 'When the component ended.
', 'TrialComponent$CreationTime' => 'When the component was created.
', 'TrialComponent$LastModifiedTime' => 'When the component was last modified.
', 'TrialComponentMetricSummary$TimeStamp' => 'When the metric was last updated.
', 'TrialComponentSimpleSummary$CreationTime' => 'When the component was created.
', 'TrialComponentSummary$StartTime' => 'When the component started.
', 'TrialComponentSummary$EndTime' => 'When the component ended.
', 'TrialComponentSummary$CreationTime' => 'When the component was created.
', 'TrialComponentSummary$LastModifiedTime' => 'When the component was last modified.
', 'TrialSummary$CreationTime' => 'When the trial was created.
', 'TrialSummary$LastModifiedTime' => 'When the trial was last modified.
', 'UpdateTrialComponentRequest$StartTime' => 'When the component started.
', 'UpdateTrialComponentRequest$EndTime' => 'When the component ended.
', 'Workforce$LastUpdatedDate' => 'The most recent date that UpdateWorkforce was used to successfully add one or more IP address ranges (CIDRs) to a private workforce\'s allow list.
', 'Workforce$CreateDate' => 'The date that the workforce is created.
', 'Workteam$CreateDate' => 'The date and time that the work team was created (timestamp).
', 'Workteam$LastUpdatedDate' => 'The date and time that the work team was last updated (timestamp).
', ], ], 'TimestampAttributeName' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$TimestampAttributeName' => 'The name of the column indicating a point in time at which the target value of a given item is recorded.
', ], ], 'TrafficDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'Phase$DurationInSeconds' => 'Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600. This value should not exceed JobDurationInSeconds
.
Defines how long each traffic step should be.
', ], ], 'TrafficPattern' => [ 'base' => 'Defines the traffic pattern of the load test.
', 'refs' => [ 'RecommendationJobInputConfig$TrafficPattern' => 'Specifies the traffic pattern of the job.
', ], ], 'TrafficRoutingConfig' => [ 'base' => 'Defines the traffic routing strategy during an endpoint deployment to shift traffic from the old fleet to the new fleet.
', 'refs' => [ 'BlueGreenUpdatePolicy$TrafficRoutingConfiguration' => 'Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment.
', ], ], 'TrafficRoutingConfigType' => [ 'base' => NULL, 'refs' => [ 'TrafficRoutingConfig$Type' => 'Traffic routing strategy type.
ALL_AT_ONCE
: Endpoint traffic shifts to the new fleet in a single step.
CANARY
: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic.
LINEAR
: Endpoint traffic shifts to the new fleet in n steps of a configurable size.
Defines the traffic patterns. Choose either PHASES
or STAIRS
.
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
', ], ], 'TrainingContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$ContainerEntrypoint' => 'The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information.
', ], ], 'TrainingContainerEntrypointString' => [ 'base' => NULL, 'refs' => [ 'TrainingContainerEntrypoint$member' => NULL, ], ], 'TrainingEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'TrainingEnvironmentMap$key' => NULL, ], ], 'TrainingEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$Environment' => 'The environment variables to set in the Docker container.
', 'DescribeTrainingJobResponse$Environment' => 'The environment variables to set in the Docker container.
', 'TrainingJob$Environment' => 'The environment variables to set in the Docker container.
', ], ], 'TrainingEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'TrainingEnvironmentMap$value' => NULL, ], ], 'TrainingImageConfig' => [ 'base' => 'The configuration to use an image from a private Docker registry for a training job.
', 'refs' => [ 'AlgorithmSpecification$TrainingImageConfig' => 'The configuration to use an image from a private Docker registry for a training job.
', ], ], 'TrainingInputMode' => [ 'base' => 'The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports Pipe
mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
File mode
If an algorithm supports File
mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won\'t be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports FastFile
mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.
FastFile
mode works best when the data is read sequentially. Augmented manifest files aren\'t supported. The startup time is lower when there are fewer files in the S3 bucket provided.
(Optional) The input mode to use for the data channel in a training job. If you don\'t set a value for InputMode
, SageMaker uses the value set for TrainingInputMode
. Use this parameter to override the TrainingInputMode
setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job\'s general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File
input mode. To stream data directly from Amazon S3 to the container, choose Pipe
input mode.
To use a model for incremental training, choose File
input model.
The number of instances of the type specified by InstanceType
. Choose an instance count larger than 1 for distributed training algorithms. See Step 2: Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
The number of compute instances of type InstanceType
to use. For distributed training, select a value greater than 1.
Specifies the number of instances of the instance group.
', 'ResourceConfig$InstanceCount' => 'The number of ML compute instances to use. For distributed training, provide a value greater than 1.
', ], ], 'TrainingInstanceType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningInstanceConfig$InstanceType' => 'The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type descriptions.
', 'HyperParameterTuningResourceConfig$InstanceType' => 'The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.
', 'InstanceGroup$InstanceType' => 'Specifies the instance type of the instance group.
', 'ResourceConfig$InstanceType' => 'The ML compute instance type.
SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting December 9th, 2022.
Amazon EC2 P4de instances (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, which accelerate the speed of training ML models that need to be trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker supports ML training jobs on P4de instances (ml.p4de.24xlarge
) to reduce model training time. The ml.p4de.24xlarge
instances are available in the following Amazon Web Services Regions.
US East (N. Virginia) (us-east-1)
US West (Oregon) (us-west-2)
To request quota limit increase and start using P4de instances, contact the SageMaker Training service team through your account team.
A list of the instance types that this algorithm can use for training.
', ], ], 'TrainingJob' => [ 'base' => 'Contains information about a training job.
', 'refs' => [ 'SearchRecord$TrainingJob' => 'The properties of a training job.
', 'TrialComponentSourceDetail$TrainingJob' => 'Information about a training job that\'s the source of a trial component.
', ], ], 'TrainingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'DescribeProcessingJobResponse$TrainingJobArn' => 'The ARN of a training job associated with this processing job.
', 'DescribeTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'HyperParameterTrainingJobSummary$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'ProcessingJob$TrainingJobArn' => 'The ARN of the training job associated with this processing job.
', 'TrainingJob$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'TrainingJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the training job that was run by this step execution.
', 'TrainingJobSummary$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'UpdateTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', ], ], 'TrainingJobDefinition' => [ 'base' => 'Defines the input needed to run a training job using the algorithm.
', 'refs' => [ 'AlgorithmValidationProfile$TrainingJobDefinition' => 'The TrainingJobDefinition
object that describes the training job that SageMaker runs to validate your algorithm.
Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband
strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType
must be OFF
to use Hyperband
. This parameter can take on one of the following values (the default value is OFF
):
Training jobs launched by the hyperparameter tuning job do not use early stopping.
SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.
The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
', 'DescribeTrainingJobRequest$TrainingJobName' => 'The name of the training job.
', 'DescribeTrainingJobResponse$TrainingJobName' => 'Name of the model training job.
', 'HyperParameterTrainingJobSummary$TrainingJobName' => 'The name of the training job.
', 'StopTrainingJobRequest$TrainingJobName' => 'The name of the training job to stop.
', 'TrainingJob$TrainingJobName' => 'The name of the training job.
', 'TrainingJobSummary$TrainingJobName' => 'The name of the training job that you want a summary for.
', 'UpdateTrainingJobRequest$TrainingJobName' => 'The name of a training job to update the Debugger profiling configuration.
', 'WarmPoolStatus$ReusedByJob' => 'The name of the matching training job that reused the warm pool.
', ], ], 'TrainingJobSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsForHyperParameterTuningJobRequest$SortBy' => 'The field to sort results by. The default is Name
.
If the value of this field is FinalObjectiveMetricValue
, any training jobs that did not return an objective metric are not listed.
The status of the training job.
SageMaker provides the following training job statuses:
InProgress
- The training is in progress.
Completed
- The training job has completed.
Failed
- The training job has failed. To see the reason for the failure, see the FailureReason
field in the response to a DescribeTrainingJobResponse
call.
Stopping
- The training job is stopping.
Stopped
- The training job has stopped.
For more detailed information, see SecondaryStatus
.
The status of the training job.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$StatusEquals' => 'A filter that returns only training jobs with the specified status.
', 'ListTrainingJobsRequest$StatusEquals' => 'A filter that retrieves only training jobs with a specific status.
', 'TrainingJob$TrainingJobStatus' => 'The status of the training job.
Training job statuses are:
InProgress
- The training is in progress.
Completed
- The training job has completed.
Failed
- The training job has failed. To see the reason for the failure, see the FailureReason
field in the response to a DescribeTrainingJobResponse
call.
Stopping
- The training job is stopping.
Stopped
- The training job has stopped.
For more detailed information, see SecondaryStatus
.
The status of the training job.
', ], ], 'TrainingJobStatusCounter' => [ 'base' => NULL, 'refs' => [ 'TrainingJobStatusCounters$Completed' => 'The number of completed training jobs launched by the hyperparameter tuning job.
', 'TrainingJobStatusCounters$InProgress' => 'The number of in-progress training jobs launched by a hyperparameter tuning job.
', 'TrainingJobStatusCounters$RetryableError' => 'The number of training jobs that failed, but can be retried. A failed training job can be retried only if it failed because an internal service error occurred.
', 'TrainingJobStatusCounters$NonRetryableError' => 'The number of training jobs that failed and can\'t be retried. A failed training job can\'t be retried if it failed because a client error occurred.
', 'TrainingJobStatusCounters$Stopped' => 'The number of training jobs launched by a hyperparameter tuning job that were manually stopped.
', ], ], 'TrainingJobStatusCounters' => [ 'base' => 'The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$TrainingJobStatusCounters' => 'The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.
', 'HyperParameterTuningJobSearchEntity$TrainingJobStatusCounters' => NULL, 'HyperParameterTuningJobSummary$TrainingJobStatusCounters' => 'The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
', ], ], 'TrainingJobStepMetadata' => [ 'base' => 'Metadata for a training job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TrainingJob' => 'The Amazon Resource Name (ARN) of the training job that was run by this step execution.
', ], ], 'TrainingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsResponse$TrainingJobSummaries' => 'An array of TrainingJobSummary
objects, each listing a training job.
Provides summary information about a training job.
', 'refs' => [ 'TrainingJobSummaries$member' => NULL, ], ], 'TrainingRepositoryAccessMode' => [ 'base' => NULL, 'refs' => [ 'TrainingImageConfig$TrainingRepositoryAccessMode' => 'The method that your training job will use to gain access to the images in your private Docker registry. For access to an image in a private Docker registry, set to Vpc
.
An object containing authentication information for a private Docker registry.
', 'refs' => [ 'TrainingImageConfig$TrainingRepositoryAuthConfig' => 'An object containing authentication information for a private Docker registry containing your training images.
', ], ], 'TrainingRepositoryCredentialsProviderArn' => [ 'base' => NULL, 'refs' => [ 'TrainingRepositoryAuthConfig$TrainingRepositoryCredentialsProviderArn' => 'The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access credentials to your private Docker registry.
', ], ], 'TrainingSpecification' => [ 'base' => 'Defines how the algorithm is used for a training job.
', 'refs' => [ 'CreateAlgorithmInput$TrainingSpecification' => 'Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support train
, validation
, and test
channels.
Details about training jobs run by this algorithm.
', ], ], 'TrainingTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$TrainingTimeInSeconds' => 'The training time in seconds.
', 'TrainingJob$TrainingTimeInSeconds' => 'The training time in seconds.
', ], ], 'TransformDataSource' => [ 'base' => 'Describes the location of the channel data.
', 'refs' => [ 'TransformInput$DataSource' => 'Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
', ], ], 'TransformEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'TransformEnvironmentMap$key' => NULL, ], ], 'TransformEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'DescribeTransformJobResponse$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'TransformJob$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'TransformJobDefinition$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', ], ], 'TransformEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'TransformEnvironmentMap$value' => NULL, ], ], 'TransformInput' => [ 'base' => 'Describes the input source of a transform job and the way the transform job consumes it.
', 'refs' => [ 'CreateTransformJobRequest$TransformInput' => 'Describes the input source and the way the transform job consumes it.
', 'DescribeTransformJobResponse$TransformInput' => 'Describes the dataset to be transformed and the Amazon S3 location where it is stored.
', 'TransformJob$TransformInput' => NULL, 'TransformJobDefinition$TransformInput' => 'A description of the input source and the way the transform job consumes it.
', ], ], 'TransformInstanceCount' => [ 'base' => NULL, 'refs' => [ 'TransformResources$InstanceCount' => 'The number of ML compute instances to use in the transform job. The default value is 1
, and the maximum is 100
. For distributed transform jobs, specify a value greater than 1
.
The ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or ml.m5.large
instance types.
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
', 'InferenceSpecification$SupportedTransformInstanceTypes' => 'A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
This parameter is required for unversioned models, and optional for versioned models.
', ], ], 'TransformJob' => [ 'base' => 'A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
', 'refs' => [ 'ModelDashboardModel$LastBatchTransformJob' => NULL, 'TrialComponentSourceDetail$TransformJob' => 'Information about a transform job that\'s the source of a trial component.
', ], ], 'TransformJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobResponse$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'DescribeTransformJobResponse$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'TransformJob$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'TransformJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
', 'TransformJobSummary$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', ], ], 'TransformJobDefinition' => [ 'base' => 'Defines the input needed to run a transform job using the inference specification specified in the algorithm.
', 'refs' => [ 'AlgorithmValidationProfile$TransformJobDefinition' => 'The TransformJobDefinition
object that describes the transform job that SageMaker runs to validate your algorithm.
The TransformJobDefinition
object that describes the transform job used for the validation of the model package.
The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
', 'DescribeTransformJobRequest$TransformJobName' => 'The name of the transform job that you want to view details of.
', 'DescribeTransformJobResponse$TransformJobName' => 'The name of the transform job.
', 'StopTransformJobRequest$TransformJobName' => 'The name of the batch transform job to stop.
', 'TransformJob$TransformJobName' => 'The name of the transform job.
', 'TransformJobSummary$TransformJobName' => 'The name of the transform job.
', ], ], 'TransformJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeTransformJobResponse$TransformJobStatus' => 'The status of the transform job. If the transform job failed, the reason is returned in the FailureReason
field.
A filter that retrieves only transform jobs with a specific status.
', 'TransformJob$TransformJobStatus' => 'The status of the transform job.
Transform job statuses are:
InProgress
- The job is in progress.
Completed
- The job has completed.
Failed
- The transform job has failed. To see the reason for the failure, see the FailureReason
field in the response to a DescribeTransformJob
call.
Stopping
- The transform job is stopping.
Stopped
- The transform job has stopped.
The status of the transform job.
', ], ], 'TransformJobStepMetadata' => [ 'base' => 'Metadata for a transform job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TransformJob' => 'The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
', ], ], 'TransformJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTransformJobsResponse$TransformJobSummaries' => 'An array of TransformJobSummary
objects.
Provides a summary of a transform job. Multiple TransformJobSummary
objects are returned as a list after in response to a ListTransformJobs call.
Describes the results of a transform job.
', 'refs' => [ 'CreateTransformJobRequest$TransformOutput' => 'Describes the results of the transform job.
', 'DescribeTransformJobResponse$TransformOutput' => 'Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
', 'TransformJob$TransformOutput' => NULL, 'TransformJobDefinition$TransformOutput' => 'Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
', ], ], 'TransformResources' => [ 'base' => 'Describes the resources, including ML instance types and ML instance count, to use for transform job.
', 'refs' => [ 'CreateTransformJobRequest$TransformResources' => 'Describes the resources, including ML instance types and ML instance count, to use for the transform job.
', 'DescribeTransformJobResponse$TransformResources' => 'Describes the resources, including ML instance types and ML instance count, to use for the transform job.
', 'TransformJob$TransformResources' => NULL, 'TransformJobDefinition$TransformResources' => 'Identifies the ML compute instances for the transform job.
', ], ], 'TransformS3DataSource' => [ 'base' => 'Describes the S3 data source.
', 'refs' => [ 'TransformDataSource$S3DataSource' => 'The S3 location of the data source that is associated with a channel.
', ], ], 'TransformationAttributeName' => [ 'base' => NULL, 'refs' => [ 'AggregationTransformations$key' => NULL, 'FillingTransformations$key' => NULL, ], ], 'Trial' => [ 'base' => 'The properties of a trial as returned by the Search API.
', 'refs' => [ 'SearchRecord$Trial' => 'The properties of a trial.
', ], ], 'TrialArn' => [ 'base' => NULL, 'refs' => [ 'AssociateTrialComponentResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'CreateTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'DeleteTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial that is being deleted.
', 'DescribeTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'DisassociateTrialComponentResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'Trial$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'TrialSummary$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'UpdateTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', ], ], 'TrialComponent' => [ 'base' => 'The properties of a trial component as returned by the Search API.
', 'refs' => [ 'SearchRecord$TrialComponent' => 'The properties of a trial component.
', ], ], 'TrialComponentArn' => [ 'base' => NULL, 'refs' => [ 'AssociateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'CreateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'DeleteTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the component is being deleted.
', 'DescribeTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'DisassociateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponent$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponentSimpleSummary$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponentSummary$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'UpdateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', ], ], 'TrialComponentArtifact' => [ 'base' => 'Represents an input or output artifact of a trial component. You specify TrialComponentArtifact
as part of the InputArtifacts
and OutputArtifacts
parameters in the CreateTrialComponent request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
', 'refs' => [ 'TrialComponentArtifacts$value' => NULL, ], ], 'TrialComponentArtifactValue' => [ 'base' => NULL, 'refs' => [ 'TrialComponentArtifact$Value' => 'The location of the artifact.
', ], ], 'TrialComponentArtifacts' => [ 'base' => NULL, 'refs' => [ 'CreateTrialComponentRequest$InputArtifacts' => 'The input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.
', 'CreateTrialComponentRequest$OutputArtifacts' => 'The output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.
', 'DescribeTrialComponentResponse$InputArtifacts' => 'The input artifacts of the component.
', 'DescribeTrialComponentResponse$OutputArtifacts' => 'The output artifacts of the component.
', 'TrialComponent$InputArtifacts' => 'The input artifacts of the component.
', 'TrialComponent$OutputArtifacts' => 'The output artifacts of the component.
', 'UpdateTrialComponentRequest$InputArtifacts' => 'Replaces all of the component\'s input artifacts with the specified artifacts or adds new input artifacts. Existing input artifacts are replaced if the trial component is updated with an identical input artifact key.
', 'UpdateTrialComponentRequest$OutputArtifacts' => 'Replaces all of the component\'s output artifacts with the specified artifacts or adds new output artifacts. Existing output artifacts are replaced if the trial component is updated with an identical output artifact key.
', ], ], 'TrialComponentKey128' => [ 'base' => NULL, 'refs' => [ 'TrialComponentArtifacts$key' => NULL, ], ], 'TrialComponentKey256' => [ 'base' => NULL, 'refs' => [ 'ListTrialComponentKey256$member' => NULL, ], ], 'TrialComponentKey320' => [ 'base' => NULL, 'refs' => [ 'TrialComponentParameters$key' => NULL, ], ], 'TrialComponentMetricSummaries' => [ 'base' => NULL, 'refs' => [ 'DescribeTrialComponentResponse$Metrics' => 'The metrics for the component.
', 'TrialComponent$Metrics' => 'The metrics for the component.
', ], ], 'TrialComponentMetricSummary' => [ 'base' => 'A summary of the metrics of a trial component.
', 'refs' => [ 'TrialComponentMetricSummaries$member' => NULL, ], ], 'TrialComponentParameterValue' => [ 'base' => 'The value of a hyperparameter. Only one of NumberValue
or StringValue
can be specified.
This object is specified in the CreateTrialComponent request.
', 'refs' => [ 'TrialComponentParameters$value' => NULL, ], ], 'TrialComponentParameters' => [ 'base' => NULL, 'refs' => [ 'CreateTrialComponentRequest$Parameters' => 'The hyperparameters for the component.
', 'DescribeTrialComponentResponse$Parameters' => 'The hyperparameters of the component.
', 'TrialComponent$Parameters' => 'The hyperparameters of the component.
', 'UpdateTrialComponentRequest$Parameters' => 'Replaces all of the component\'s hyperparameters with the specified hyperparameters or add new hyperparameters. Existing hyperparameters are replaced if the trial component is updated with an identical hyperparameter key.
', ], ], 'TrialComponentPrimaryStatus' => [ 'base' => NULL, 'refs' => [ 'TrialComponentStatus$PrimaryStatus' => 'The status of the trial component.
', ], ], 'TrialComponentSimpleSummaries' => [ 'base' => NULL, 'refs' => [ 'Trial$TrialComponentSummaries' => 'A list of the components associated with the trial. For each component, a summary of the component\'s properties is included.
', ], ], 'TrialComponentSimpleSummary' => [ 'base' => 'A short summary of a trial component.
', 'refs' => [ 'TrialComponentSimpleSummaries$member' => NULL, ], ], 'TrialComponentSource' => [ 'base' => 'The Amazon Resource Name (ARN) and job type of the source of a trial component.
', 'refs' => [ 'DescribeTrialComponentResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the job type.
', 'TrialComponent$Source' => 'The Amazon Resource Name (ARN) and job type of the source of the component.
', 'TrialComponentSimpleSummary$TrialComponentSource' => NULL, 'TrialComponentSources$member' => NULL, 'TrialComponentSummary$TrialComponentSource' => NULL, ], ], 'TrialComponentSourceArn' => [ 'base' => NULL, 'refs' => [ 'TrialComponentMetricSummary$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', 'TrialComponentSource$SourceArn' => 'The source Amazon Resource Name (ARN).
', 'TrialComponentSourceDetail$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'TrialComponentSourceDetail' => [ 'base' => 'Detailed information about the source of a trial component. Either ProcessingJob
or TrainingJob
is returned.
Details of the source of the component.
', ], ], 'TrialComponentSources' => [ 'base' => NULL, 'refs' => [ 'DescribeTrialComponentResponse$Sources' => 'A list of ARNs and, if applicable, job types for multiple sources of an experiment run.
', ], ], 'TrialComponentStatus' => [ 'base' => 'The status of the trial component.
', 'refs' => [ 'CreateTrialComponentRequest$Status' => 'The status of the component. States include:
InProgress
Completed
Failed
The status of the component. States include:
InProgress
Completed
Failed
The status of the component. States include:
InProgress
Completed
Failed
The new status of the component.
', ], ], 'TrialComponentStatusMessage' => [ 'base' => NULL, 'refs' => [ 'TrialComponentStatus$Message' => 'If the component failed, a message describing why.
', ], ], 'TrialComponentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrialComponentsResponse$TrialComponentSummaries' => 'A list of the summaries of your trial components.
', ], ], 'TrialComponentSummary' => [ 'base' => 'A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName
.
The source of the trial.
', 'refs' => [ 'DescribeTrialResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the job type.
', 'Trial$Source' => NULL, 'TrialSummary$TrialSource' => NULL, ], ], 'TrialSourceArn' => [ 'base' => NULL, 'refs' => [ 'TrialSource$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'TrialSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrialsResponse$TrialSummaries' => 'A list of the summaries of your trials.
', ], ], 'TrialSummary' => [ 'base' => 'A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName
.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt
= EventTime
+ TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt
= EventTime
+ TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt
= EventTime
+ TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
TtlDuration
time unit.
TtlDuration
time value.
The job completion criteria.
', 'refs' => [ 'HyperParameterTuningJobConfig$TuningJobCompletionCriteria' => 'The tuning job\'s completion criteria.
', ], ], 'TuningJobStepMetaData' => [ 'base' => 'Metadata for a tuning step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TuningJob' => 'The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
', ], ], 'USD' => [ 'base' => 'Represents an amount of money in United States dollars.
', 'refs' => [ 'PublicWorkforceTaskPrice$AmountInUsd' => 'Defines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.
', ], ], 'UiConfig' => [ 'base' => 'Provided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn
or UiTemplateS3Uri
.
For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn
.
For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri
to specify the location of a worker task template in Amazon S3.
Information about the user interface that workers use to complete the labeling task.
', ], ], 'UiTemplate' => [ 'base' => 'The Liquid template for the worker user interface.
', 'refs' => [ 'CreateHumanTaskUiRequest$UiTemplate' => NULL, 'RenderUiTemplateRequest$UiTemplate' => 'A Template
object containing the worker UI template to render.
Container for user interface template information.
', 'refs' => [ 'DescribeHumanTaskUiResponse$UiTemplate' => NULL, ], ], 'Uid' => [ 'base' => NULL, 'refs' => [ 'CustomPosixUserConfig$Uid' => 'The POSIX user ID.
', ], ], 'UpdateActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateClusterRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateClusterResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointWeightsAndCapacitiesInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointWeightsAndCapacitiesOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceComponentInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceComponentOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceComponentRuntimeConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceComponentRuntimeConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringAlertRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringAlertResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'Url' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$ModelDataUrl' => 'The location of the model artifacts. For more information, see ContainerDefinition.
', 'ClarifyShapBaselineConfig$ShapBaselineUri' => 'The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri
should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in ModelDataUrl
.
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'InferenceComponentContainerSpecificationSummary$ArtifactUrl' => 'The Amazon S3 path where the model artifacts are stored.
', 'ModelPackageContainerDefinition$ModelDataUrl' => 'The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip
compressed tar archive (.tar.gz
suffix).
The model artifacts must be in an S3 bucket that is in the same region as the model package.
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip
compressed tar archive (.tar.gz
suffix).
The model artifacts must be in an S3 bucket that is in the same Amazon Web Services region as the algorithm.
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
', 'refs' => [ 'AssociationSummary$CreatedBy' => NULL, 'DescribeActionResponse$CreatedBy' => NULL, 'DescribeActionResponse$LastModifiedBy' => NULL, 'DescribeArtifactResponse$CreatedBy' => NULL, 'DescribeArtifactResponse$LastModifiedBy' => NULL, 'DescribeContextResponse$CreatedBy' => NULL, 'DescribeContextResponse$LastModifiedBy' => NULL, 'DescribeExperimentResponse$CreatedBy' => 'Who created the experiment.
', 'DescribeExperimentResponse$LastModifiedBy' => 'Who last modified the experiment.
', 'DescribeLineageGroupResponse$CreatedBy' => NULL, 'DescribeLineageGroupResponse$LastModifiedBy' => NULL, 'DescribeModelCardResponse$CreatedBy' => NULL, 'DescribeModelCardResponse$LastModifiedBy' => NULL, 'DescribeModelPackageGroupOutput$CreatedBy' => NULL, 'DescribeModelPackageOutput$CreatedBy' => NULL, 'DescribeModelPackageOutput$LastModifiedBy' => NULL, 'DescribePipelineExecutionResponse$CreatedBy' => NULL, 'DescribePipelineExecutionResponse$LastModifiedBy' => NULL, 'DescribePipelineResponse$CreatedBy' => NULL, 'DescribePipelineResponse$LastModifiedBy' => NULL, 'DescribeProjectOutput$CreatedBy' => NULL, 'DescribeProjectOutput$LastModifiedBy' => NULL, 'DescribeTrialComponentResponse$CreatedBy' => 'Who created the trial component.
', 'DescribeTrialComponentResponse$LastModifiedBy' => 'Who last modified the component.
', 'DescribeTrialResponse$CreatedBy' => 'Who created the trial.
', 'DescribeTrialResponse$LastModifiedBy' => 'Who last modified the trial.
', 'Experiment$CreatedBy' => 'Who created the experiment.
', 'Experiment$LastModifiedBy' => NULL, 'ModelCard$CreatedBy' => NULL, 'ModelCard$LastModifiedBy' => NULL, 'ModelDashboardModelCard$CreatedBy' => NULL, 'ModelDashboardModelCard$LastModifiedBy' => NULL, 'ModelPackage$CreatedBy' => 'Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
', 'ModelPackage$LastModifiedBy' => 'Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
', 'ModelPackageGroup$CreatedBy' => NULL, 'Pipeline$CreatedBy' => NULL, 'Pipeline$LastModifiedBy' => NULL, 'PipelineExecution$CreatedBy' => NULL, 'PipelineExecution$LastModifiedBy' => NULL, 'Project$CreatedBy' => 'Who created the project.
', 'Project$LastModifiedBy' => NULL, 'Trial$CreatedBy' => 'Who created the trial.
', 'Trial$LastModifiedBy' => NULL, 'TrialComponent$CreatedBy' => 'Who created the trial component.
', 'TrialComponent$LastModifiedBy' => NULL, 'TrialComponentSimpleSummary$CreatedBy' => NULL, 'TrialComponentSummary$CreatedBy' => 'Who created the trial component.
', 'TrialComponentSummary$LastModifiedBy' => 'Who last modified the component.
', ], ], 'UserProfileArn' => [ 'base' => NULL, 'refs' => [ 'CreateUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', 'DescribeUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', 'UpdateUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', ], ], 'UserProfileDetails' => [ 'base' => 'The user profile details.
', 'refs' => [ 'UserProfileList$member' => NULL, ], ], 'UserProfileList' => [ 'base' => NULL, 'refs' => [ 'ListUserProfilesResponse$UserProfiles' => 'The list of user profiles.
', ], ], 'UserProfileName' => [ 'base' => NULL, 'refs' => [ 'AppDetails$UserProfileName' => 'The user profile name.
', 'CreateAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName
must be set.
The name of the UserProfile to sign-in as.
', 'CreateUserProfileRequest$UserProfileName' => 'A name for the UserProfile. This value is not case sensitive.
', 'DeleteAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName
must be set.
The user profile name.
', 'DescribeAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName
must be set.
The user profile name.
', 'DescribeUserProfileRequest$UserProfileName' => 'The user profile name. This value is not case sensitive.
', 'DescribeUserProfileResponse$UserProfileName' => 'The user profile name.
', 'ListAppsRequest$UserProfileNameEquals' => 'A parameter to search by user profile name. If SpaceNameEquals
is set, then this value cannot be set.
A parameter by which to filter the results.
', 'OwnershipSettings$OwnerUserProfileName' => 'The user profile who is the owner of the private space.
', 'OwnershipSettingsSummary$OwnerUserProfileName' => 'The user profile who is the owner of the private space.
', 'UpdateUserProfileRequest$UserProfileName' => 'The user profile name.
', 'UserProfileDetails$UserProfileName' => 'The user profile name.
', ], ], 'UserProfileSortKey' => [ 'base' => NULL, 'refs' => [ 'ListUserProfilesRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
', ], ], 'UserProfileStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeUserProfileResponse$Status' => 'The status.
', 'UserProfileDetails$Status' => 'The status.
', ], ], 'UserSettings' => [ 'base' => 'A collection of settings that apply to users in a domain. These settings are specified when the CreateUserProfile
API is called, and as DefaultUserSettings
when the CreateDomain
API is called.
SecurityGroups
is aggregated when specified in both calls. For all other settings in UserSettings
, the values specified in CreateUserProfile
take precedence over those specified in CreateDomain
.
The default settings to use to create a user profile when UserSettings
isn\'t specified in the call to the CreateUserProfile
API.
SecurityGroups
is aggregated when specified in both calls. For all other settings in UserSettings
, the values specified in CreateUserProfile
take precedence over those specified in CreateDomain
.
A collection of settings.
', 'DescribeDomainResponse$DefaultUserSettings' => 'Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.
', 'DescribeUserProfileResponse$UserSettings' => 'A collection of settings.
', 'UpdateDomainRequest$DefaultUserSettings' => 'A collection of settings.
', 'UpdateUserProfileRequest$UserSettings' => 'A collection of settings.
', ], ], 'UsersPerStep' => [ 'base' => NULL, 'refs' => [ 'Stairs$UsersPerStep' => 'Specifies how many new users to spawn in each step.
', ], ], 'UtilizationMetric' => [ 'base' => NULL, 'refs' => [ 'RecommendationMetrics$CpuUtilization' => 'The expected CPU utilization at maximum invocations per minute for the instance.
NaN
indicates that the value is not available.
The expected memory utilization at maximum invocations per minute for the instance.
NaN
indicates that the value is not available.
The percentage of how much utilization you want an instance to use before autoscaling. The default value is 50%.
', 'GetScalingConfigurationRecommendationResponse$TargetCpuUtilizationPerCore' => 'The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the request. The default value is 50%.
', ], ], 'ValidationFraction' => [ 'base' => NULL, 'refs' => [ 'AutoMLDataSplitConfig$ValidationFraction' => 'The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.
', ], ], 'VariantName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceComponentInput$VariantName' => 'The name of an existing production variant where you host the inference component.
', 'DescribeInferenceComponentOutput$VariantName' => 'The name of the production variant that hosts the inference component.
', 'DesiredWeightAndCapacity$VariantName' => 'The name of the variant to update.
', 'InferenceComponentSummary$VariantName' => 'The name of the production variant that hosts the inference component.
', 'ListInferenceComponentsInput$VariantNameEquals' => 'A production variant name to filter the listed inference components. The response includes only those inference components that are hosted at the specified variant.
', 'PendingProductionVariantSummary$VariantName' => 'The name of the variant.
', 'ProductionVariant$VariantName' => 'The name of the production variant.
', 'ProductionVariantSummary$VariantName' => 'The name of the variant.
', ], ], 'VariantProperty' => [ 'base' => 'Specifies a production variant property type for an Endpoint.
If you are updating an endpoint with the RetainAllVariantProperties
option of UpdateEndpointInput set to true
, the VariantProperty
objects listed in the ExcludeRetainedVariantProperties
parameter of UpdateEndpointInput override the existing variant properties of the endpoint.
When you are updating endpoint resources with RetainAllVariantProperties
, whose value is set to true
, ExcludeRetainedVariantProperties
specifies the list of type VariantProperty to override with the values provided by EndpointConfig
. If you don\'t specify a value for ExcludeRetainedVariantProperties
, no variant properties are overridden.
The type of variant property. The supported values are:
DesiredInstanceCount
: Overrides the existing variant instance counts using the InitialInstanceCount
values in the ProductionVariants
of CreateEndpointConfig.
DesiredWeight
: Overrides the existing variant weights using the InitialVariantWeight
values in the ProductionVariants
of CreateEndpointConfig.
DataCaptureConfig
: (Not currently supported.)
The endpoint variant status which describes the current deployment stage status or operational status.
Creating
: Creating inference resources for the production variant.
Deleting
: Terminating inference resources for the production variant.
Updating
: Updating capacity for the production variant.
ActivatingTraffic
: Turning on traffic for the production variant.
Baking
: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
A message that describes the status of the production variant.
', ], ], 'VariantWeight' => [ 'base' => NULL, 'refs' => [ 'DesiredWeightAndCapacity$DesiredWeight' => 'The variant\'s weight.
', 'PendingProductionVariantSummary$CurrentWeight' => 'The weight associated with the variant.
', 'PendingProductionVariantSummary$DesiredWeight' => 'The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
', 'ProductionVariant$InitialVariantWeight' => 'Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight
to the sum of all VariantWeight
values across all ProductionVariants. If unspecified, it defaults to 1.0.
The weight associated with the variant.
', 'ProductionVariantSummary$DesiredWeight' => 'The requested weight, as specified in the UpdateEndpointWeightsAndCapacities
request.
Configuration for your vector collection type.
', 'refs' => [ 'CollectionConfig$VectorConfig' => 'Configuration for your vector collection type.
Dimension
: The number of elements in your vector.
The stability of the image version, specified by the maintainer.
NOT_PROVIDED
: The maintainers did not provide a status for image version stability.
STABLE
: The image version is stable.
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The stability of the image version specified by the maintainer.
NOT_PROVIDED
: The maintainers did not provide a status for image version stability.
STABLE
: The image version is stable.
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The availability of the image version specified by the maintainer.
NOT_PROVIDED
: The maintainers did not provide a status for image version stability.
STABLE
: The image version is stable.
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Version Id of the pipeline definition file. If not specified, Amazon SageMaker will retrieve the latest version.
', ], ], 'VersionedArnOrName' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to use to create the model.
', 'DeleteModelPackageInput$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to delete.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'DescribeModelPackageInput$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to describe.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', ], ], 'Vertex' => [ 'base' => 'A lineage entity connected to the starting entity(ies).
', 'refs' => [ 'Vertices$member' => NULL, ], ], 'Vertices' => [ 'base' => NULL, 'refs' => [ 'QueryLineageResponse$Vertices' => 'A list of vertices connected to the start entity(ies) in the lineage graph.
', ], ], 'VisibilityConditions' => [ 'base' => 'The list of key-value pairs that you specify for your resources.
', 'refs' => [ 'VisibilityConditionsList$member' => NULL, ], ], 'VisibilityConditionsKey' => [ 'base' => NULL, 'refs' => [ 'VisibilityConditions$Key' => 'The key for that specifies the tag that you\'re using to filter the search results. The key must start with Tags.
.
Limits the results of your search request to the resources that you can access.
', ], ], 'VisibilityConditionsValue' => [ 'base' => NULL, 'refs' => [ 'VisibilityConditions$Value' => 'The value for the tag that you\'re using to filter the search results.
', ], ], 'VolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningInstanceConfig$VolumeSizeInGB' => 'The volume size in GB of the data to be processed for hyperparameter optimization (optional).
', 'ResourceConfig$VolumeSizeInGB' => 'The size of the ML storage volume that you want to provision.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose File
as the TrainingInputMode
in the algorithm specification.
When using an ML instance with NVMe SSD volumes, SageMaker doesn\'t provision Amazon EBS General Purpose SSD (gp2) storage. Available storage is fixed to the NVMe-type instance\'s storage capacity. SageMaker configures storage paths for training datasets, checkpoints, model artifacts, and outputs to use the entire capacity of the instance storage. For example, ML instance families with the NVMe-type instance storage include ml.p4d
, ml.g4dn
, and ml.g5
.
When using an ML instance with the EBS-only storage option and without instance storage, you must define the size of EBS volume through VolumeSizeInGB
in the ResourceConfig
API. For example, ML instance families that use EBS volumes include ml.c5
and ml.p2
.
To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
To find the default local paths defined by the SageMaker training platform, see Amazon SageMaker Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and Outputs.
', ], ], 'VpcConfig' => [ 'base' => 'Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
', 'refs' => [ 'AutoMLSecurityConfig$VpcConfig' => 'The VPC configuration.
', 'CreateClusterRequest$VpcConfig' => NULL, 'CreateEndpointConfigInput$VpcConfig' => NULL, 'CreateModelInput$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. VpcConfig
is used in hosting services and in batch transform. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.
A VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'DescribeClusterResponse$VpcConfig' => NULL, 'DescribeEndpointConfigOutput$VpcConfig' => NULL, 'DescribeModelOutput$VpcConfig' => 'A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
', 'DescribeTrainingJobResponse$VpcConfig' => 'A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'HyperParameterTrainingJobDefinition$VpcConfig' => 'The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'LabelingJobResourceConfig$VpcConfig' => NULL, 'Model$VpcConfig' => NULL, 'MonitoringNetworkConfig$VpcConfig' => NULL, 'NetworkConfig$VpcConfig' => NULL, 'TrainingJob$VpcConfig' => 'A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', ], ], 'VpcId' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$VpcId' => 'The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
', 'DescribeDomainResponse$VpcId' => 'The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
', ], ], 'VpcOnlyTrustedAccounts' => [ 'base' => NULL, 'refs' => [ 'DockerSettings$VpcOnlyTrustedAccounts' => 'The list of Amazon Web Services accounts that are trusted when the domain is created in VPC-only mode.
', ], ], 'VpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'VpcConfig$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in the Subnets
field.
The length of the baking period, during which SageMaker monitors alarms for each batch on the new fleet.
', 'TrafficRoutingConfig$WaitIntervalInSeconds' => 'The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
', ], ], 'WarmPoolResourceStatus' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsRequest$WarmPoolStatusEquals' => 'A filter that retrieves only training jobs with a specific warm pool status.
', 'WarmPoolStatus$Status' => 'The status of the warm pool.
InUse
: The warm pool is in use for the training job.
Available
: The warm pool is available to reuse for a matching training job.
Reused
: The warm pool moved to a matching training job for reuse.
Terminated
: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds
.
Status and billing information about the warm pool.
', 'refs' => [ 'DescribeTrainingJobResponse$WarmPoolStatus' => 'The status of the warm pool associated with the training job.
', 'TrainingJobSummary$WarmPoolStatus' => 'The status of the warm pool associated with the training job.
', ], ], 'Workforce' => [ 'base' => 'A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'refs' => [ 'DescribeWorkforceResponse$Workforce' => 'A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'UpdateWorkforceResponse$Workforce' => 'A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'Workforces$member' => NULL, ], ], 'WorkforceArn' => [ 'base' => NULL, 'refs' => [ 'CreateWorkforceResponse$WorkforceArn' => 'The Amazon Resource Name (ARN) of the workforce.
', 'Workforce$WorkforceArn' => 'The Amazon Resource Name (ARN) of the private workforce.
', 'Workteam$WorkforceArn' => 'The Amazon Resource Name (ARN) of the workforce.
', ], ], 'WorkforceFailureReason' => [ 'base' => NULL, 'refs' => [ 'Workforce$FailureReason' => 'The reason your workforce failed.
', ], ], 'WorkforceName' => [ 'base' => NULL, 'refs' => [ 'CreateWorkforceRequest$WorkforceName' => 'The name of the private workforce.
', 'CreateWorkteamRequest$WorkforceName' => 'The name of the workforce.
', 'DeleteWorkforceRequest$WorkforceName' => 'The name of the workforce.
', 'DescribeWorkforceRequest$WorkforceName' => 'The name of the private workforce whose access you want to restrict. WorkforceName
is automatically set to default
when a workforce is created and cannot be modified.
A filter you can use to search for workforces using part of the workforce name.
', 'UpdateWorkforceRequest$WorkforceName' => 'The name of the private workforce that you want to update. You can find your workforce name by using the ListWorkforces operation.
', 'Workforce$WorkforceName' => 'The name of the private workforce.
', ], ], 'WorkforceSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'WorkforceSecurityGroupIds$member' => NULL, ], ], 'WorkforceSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', 'WorkforceVpcConfigResponse$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', ], ], 'WorkforceStatus' => [ 'base' => NULL, 'refs' => [ 'Workforce$Status' => 'The status of your workforce.
', ], ], 'WorkforceSubnetId' => [ 'base' => NULL, 'refs' => [ 'WorkforceSubnets$member' => NULL, ], ], 'WorkforceSubnets' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$Subnets' => 'The ID of the subnets in the VPC that you want to connect.
', 'WorkforceVpcConfigResponse$Subnets' => 'The ID of the subnets in the VPC that you want to connect.
', ], ], 'WorkforceVpcConfigRequest' => [ 'base' => 'The VPC object you use to create or update a workforce.
', 'refs' => [ 'CreateWorkforceRequest$WorkforceVpcConfig' => 'Use this parameter to configure a workforce using VPC.
', 'UpdateWorkforceRequest$WorkforceVpcConfig' => 'Use this parameter to update your VPC configuration for a workforce.
', ], ], 'WorkforceVpcConfigResponse' => [ 'base' => 'A VpcConfig object that specifies the VPC that you want your workforce to connect to.
', 'refs' => [ 'Workforce$WorkforceVpcConfig' => 'The configuration of a VPC workforce.
', ], ], 'WorkforceVpcEndpointId' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigResponse$VpcEndpointId' => 'The IDs for the VPC service endpoints of your VPC workforce when it is created and updated.
', ], ], 'WorkforceVpcId' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$VpcId' => 'The ID of the VPC that the workforce uses for communication.
', 'WorkforceVpcConfigResponse$VpcId' => 'The ID of the VPC that the workforce uses for communication.
', ], ], 'Workforces' => [ 'base' => NULL, 'refs' => [ 'ListWorkforcesResponse$Workforces' => 'A list containing information about your workforce.
', ], ], 'WorkspaceSettings' => [ 'base' => 'The workspace settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$WorkspaceSettings' => 'The workspace settings for the SageMaker Canvas application.
', ], ], 'Workteam' => [ 'base' => 'Provides details about a labeling work team.
', 'refs' => [ 'DescribeWorkteamResponse$Workteam' => 'A Workteam
instance that contains information about the work team.
A Workteam
object that describes the updated work team.
The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.
', 'DescribeSubscribedWorkteamRequest$WorkteamArn' => 'The Amazon Resource Name (ARN) of the subscribed work team to describe.
', 'HumanLoopConfig$WorkteamArn' => 'Amazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see Create and Manage Workforces.
', 'HumanTaskConfig$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.
', 'LabelingJobSummary$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team assigned to the job.
', 'ListLabelingJobsForWorkteamRequest$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team for which you want to see labeling jobs for.
', 'SubscribedWorkteam$WorkteamArn' => 'The Amazon Resource Name (ARN) of the vendor that you have subscribed.
', 'Workteam$WorkteamArn' => 'The Amazon Resource Name (ARN) that identifies the work team.
', ], ], 'WorkteamName' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$WorkteamName' => 'The name of the work team. Use this name to identify the work team.
', 'DeleteWorkteamRequest$WorkteamName' => 'The name of the work team to delete.
', 'DescribeWorkteamRequest$WorkteamName' => 'The name of the work team to return a description of.
', 'ListSubscribedWorkteamsRequest$NameContains' => 'A string in the work team name. This filter returns only work teams whose name contains the specified string.
', 'ListWorkteamsRequest$NameContains' => 'A string in the work team\'s name. This filter returns only work teams whose name contains the specified string.
', 'UpdateWorkteamRequest$WorkteamName' => 'The name of the work team to update.
', 'Workteam$WorkteamName' => 'The name of the work team.
', ], ], 'Workteams' => [ 'base' => NULL, 'refs' => [ 'ListWorkteamsResponse$Workteams' => 'An array of Workteam
objects, each describing a work team.
Provides APIs for creating and managing SageMaker resources.
Other Resources:
', 'operations' => [ 'AddAssociation' => 'Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'AddTags' => 'Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags
parameter of CreateHyperParameterTuningJob
Tags that you add to a SageMaker Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags
parameter of CreateDomain or CreateUserProfile.
Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
', 'BatchDescribeModelPackage' => 'This action batch describes a list of versioned model packages
', 'CreateAction' => 'Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateAlgorithm' => 'Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
', 'CreateApp' => 'Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
', 'CreateAppImageConfig' => 'Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.
', 'CreateArtifact' => 'Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateAutoMLJob' => 'Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
CreateAutoMLJobV2
can manage tabular problem types identical to those of its previous version CreateAutoMLJob
, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob
to CreateAutoMLJobV2
in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
', 'CreateAutoMLJobV2' => 'Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.
CreateAutoMLJobV2
can manage tabular problem types identical to those of its previous version CreateAutoMLJob
, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob
to CreateAutoMLJobV2
in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2
, see AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
', 'CreateCluster' => 'Creates a SageMaker HyperPod cluster. SageMaker HyperPod is a capability of SageMaker for creating and managing persistent clusters for developing large machine learning models, such as large language models (LLMs) and diffusion models. To learn more, see Amazon SageMaker HyperPod in the Amazon SageMaker Developer Guide.
', 'CreateCodeRepository' => 'Creates a Git repository as a resource in your SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.
', 'CreateCompilationJob' => 'Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
You can also provide a Tag
to track the model compilation job\'s resource use and costs. The response body contains the CompilationJobArn
for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
', 'CreateContext' => 'Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateDataQualityJobDefinition' => 'Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'CreateDeviceFleet' => 'Creates a device fleet.
', 'CreateDomain' => 'Creates a Domain
. A domain consists of an associated Amazon Elastic File System volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All traffic between the domain and the Amazon EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType
parameter. AppNetworkAccessType
corresponds to the network access type that you choose when you onboard to the domain. The following options are available:
PublicInternetOnly
- Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
VpcOnly
- All traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
When internet access is disabled, you won\'t be able to run a Amazon SageMaker Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker Studio app successfully.
For more information, see Connect Amazon SageMaker Studio Notebooks to Resources in a VPC.
', 'CreateEdgeDeploymentPlan' => 'Creates an edge deployment plan, consisting of multiple stages. Each stage may have a different deployment configuration and devices.
', 'CreateEdgeDeploymentStage' => 'Creates a new stage in an existing edge deployment plan.
', 'CreateEdgePackagingJob' => 'Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.
', 'CreateEndpoint' => 'Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
Use this API to deploy models using SageMaker hosting services.
You must not delete an EndpointConfig
that is in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig
.
The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account.
When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads
, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
When SageMaker receives the request, it sets the endpoint status to Creating
. After it creates the endpoint, it sets the status to InService
. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
Option 1: For a full SageMaker access, search and attach the AmazonSageMakerFullAccess
policy.
Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
"Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
"Resource": [
"arn:aws:sagemaker:region:account-id:endpoint/endpointName"
"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
]
For more information, see SageMaker API Permissions: Actions, Permissions, and Resources Reference.
Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel
API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
Use this API if you want to use SageMaker hosting services to deploy models into production.
In the request, you define a ProductionVariant
, for each model that you want to deploy. Each ProductionVariant
parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight
to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads
, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
Creates a SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
In the Studio UI, trials are referred to as run groups and trial components are referred to as runs.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description
parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment\'s properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
', 'CreateFeatureGroup' => 'Create a new FeatureGroup
. A FeatureGroup
is a group of Features
defined in the FeatureStore
to describe a Record
.
The FeatureGroup
defines the schema and features contained in the FeatureGroup
. A FeatureGroup
definition is composed of a list of Features
, a RecordIdentifierFeatureName
, an EventTimeFeatureName
and configurations for its OnlineStore
and OfflineStore
. Check Amazon Web Services service quotas to see the FeatureGroup
s quota for your Amazon Web Services account.
Note that it can take approximately 10-15 minutes to provision an OnlineStore
FeatureGroup
with the InMemory
StorageType
.
You must include at least one of OnlineStoreConfig
and OfflineStoreConfig
to create a FeatureGroup
.
Creates a flow definition.
', 'CreateHub' => 'Create a hub.
Hub APIs are only callable through SageMaker Studio.
Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.
', 'CreateHyperParameterTuningJob' => 'Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Elastic Container Registry (ECR). For more information, see Bring your own SageMaker image.
', 'CreateImageVersion' => 'Creates a version of the SageMaker image specified by ImageName
. The version represents the Amazon Elastic Container Registry (ECR) container image specified by BaseImage
.
Creates an inference component, which is a SageMaker hosting object that you can use to deploy a model to an endpoint. In the inference component settings, you specify the model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You can optimize resource utilization by tailoring how the required CPU cores, accelerators, and memory are allocated. You can deploy multiple inference components to an endpoint, where each inference component contains one model and the resource utilization needs for that individual model. After you deploy an inference component, you can directly invoke the associated model when you use the InvokeEndpoint API action.
', 'CreateInferenceExperiment' => 'Creates an inference experiment using the configurations specified in the request.
Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For more information about inference experiments, see Shadow tests.
Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint\'s model variants based on your specified configuration.
While the experiment is in progress or after it has concluded, you can view metrics that compare your model variants. For more information, see View, monitor, and edit shadow tests.
', 'CreateInferenceRecommendationsJob' => 'Starts a recommendation job. You can create either an instance recommendation or load test job.
', 'CreateLabelingJob' => 'Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models.
You can select your workforce from one of three providers:
A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data.
The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri
have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress
) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
Creates a model in SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
Use this API to create a model if you want to use SageMaker hosting services or run a batch transform job.
To host your model, you create an endpoint configuration with the CreateEndpointConfig
API, and then create an endpoint with the CreateEndpoint
API. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
For an example that calls this method when deploying a model to SageMaker hosting services, see Create a Model (Amazon Web Services SDK for Python (Boto 3)).
To run a batch transform using your model, you start a job with the CreateTransformJob
API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
', 'CreateModelBiasJobDefinition' => 'Creates the definition for a model bias job.
', 'CreateModelCard' => 'Creates an Amazon SageMaker Model Card.
For information about how to use model cards, see Amazon SageMaker Model Card.
', 'CreateModelCardExportJob' => 'Creates an Amazon SageMaker Model Card export job.
', 'CreateModelExplainabilityJobDefinition' => 'Creates the definition for a model explainability job.
', 'CreateModelPackage' => 'Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification
. To create a model from an algorithm resource that you created or subscribed to in Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification
.
There are two types of model packages:
Versioned - a model that is part of a model group in the model registry.
Unversioned - a model package that is not part of a model group.
Creates a model group. A model group contains a group of model versions.
', 'CreateModelQualityJobDefinition' => 'Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'CreateMonitoringSchedule' => 'Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint.
', 'CreateNotebookInstance' => 'Creates an SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
In a CreateNotebookInstance
request, specify the type of ML compute instance that you want to run. SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.
After receiving the request, SageMaker does the following:
Creates a network interface in the SageMaker VPC.
(Option) If you specified SubnetId
, SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the SageMaker VPC. If you specified SubnetId
of your VPC, SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN). You can\'t change the name of a notebook instance after you create it.
After SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker endpoints, and validate hosted models.
For more information, see How It Works.
', 'CreateNotebookInstanceLifecycleConfig' => 'Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH
environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin
.
View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances
in log stream [notebook-instance-name]/[LifecycleConfigHook]
.
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'CreatePipeline' => 'Creates a pipeline using a JSON pipeline definition.
', 'CreatePresignedDomainUrl' => 'Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to the domain, and granted access to all of the Apps and files associated with the Domain\'s Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.
The IAM role or user passed to this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.
You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to Amazon SageMaker Studio Through an Interface VPC Endpoint .
The URL that you get from a call to CreatePresignedDomainUrl
has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds
. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker console, when you choose Open
next to a notebook instance, SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress
condition operator and the aws:SourceIP
condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
Creates a processing job.
', 'CreateProject' => 'Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
', 'CreateSpace' => 'Creates a space used for real time collaboration in a Domain.
', 'CreateStudioLifecycleConfig' => 'Creates a new Amazon SageMaker Studio Lifecycle Configuration.
', 'CreateTrainingJob' => 'Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
If you choose to host your model using SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than SageMaker, provided that you know how to use them for inference.
In the request body, you provide the following:
AlgorithmSpecification
- Identifies the training algorithm to use.
HyperParameters
- Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
InputDataConfig
- Describes the input required by the training job and the Amazon S3, EFS, or FSx location where it is stored.
OutputDataConfig
- Identifies the Amazon S3 bucket where you want SageMaker to save the results of model training.
ResourceConfig
- Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
EnableManagedSpotTraining
- Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training.
RoleArn
- The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training.
StoppingCondition
- To help cap training costs, use MaxRuntimeInSeconds
to set a time limit for training. Use MaxWaitTimeInSeconds
to specify how long a managed spot training job has to complete.
Environment
- The environment variables to set in the Docker container.
RetryStrategy
- The number of times to retry the job when the job fails due to an InternalServerError
.
For more information about SageMaker, see How It Works.
', 'CreateTransformJob' => 'Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
To perform batch transformations, you create a transform job and use the data that you have readily available.
In the request body, you provide the following:
TransformJobName
- Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
ModelName
- Identifies the model to use. ModelName
must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see CreateModel.
TransformInput
- Describes the dataset to be transformed and the Amazon S3 location where it is stored.
TransformOutput
- Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
TransformResources
- Identifies the ML compute instances for the transform job.
For more information about how batch transformation works, see Batch Transform.
', 'CreateTrial' => 'Creates an SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single SageMaker experiment.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial and then use the Search API to search for the tags.
To get a list of all your trials, call the ListTrials API. To view a trial\'s properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
', 'CreateTrialComponent' => 'Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials.
Trial components include pre-processing jobs, training jobs, and batch transform jobs.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial component and then use the Search API to search for the tags.
', 'CreateUserProfile' => 'Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to a domain. If an administrator invites a person by email or imports them from IAM Identity Center, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user\'s private Amazon Elastic File System (EFS) home directory.
', 'CreateWorkforce' => 'Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the DeleteWorkforce API operation to delete the existing workforce and then use CreateWorkforce
to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig
. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig
. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).
Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.
You cannot create more than 25 work teams in an account and region.
', 'DeleteAction' => 'Deletes an action.
', 'DeleteAlgorithm' => 'Removes the specified algorithm from your account.
', 'DeleteApp' => 'Used to stop and delete an app.
', 'DeleteAppImageConfig' => 'Deletes an AppImageConfig.
', 'DeleteArtifact' => 'Deletes an artifact. Either ArtifactArn
or Source
must be specified.
Deletes an association.
', 'DeleteCluster' => 'Delete a SageMaker HyperPod cluster.
', 'DeleteCodeRepository' => 'Deletes the specified Git repository from your account.
', 'DeleteCompilationJob' => 'Deletes the specified compilation job. This action deletes only the compilation job resource in Amazon SageMaker. It doesn\'t delete other resources that are related to that job, such as the model artifacts that the job creates, the compilation logs in CloudWatch, the compiled model, or the IAM role.
You can delete a compilation job only if its current status is COMPLETED
, FAILED
, or STOPPED
. If the job status is STARTING
or INPROGRESS
, stop the job, and then delete it after its status becomes STOPPED
.
Deletes an context.
', 'DeleteDataQualityJobDefinition' => 'Deletes a data quality monitoring job definition.
', 'DeleteDeviceFleet' => 'Deletes a fleet.
', 'DeleteDomain' => 'Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using IAM Identity Center. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
', 'DeleteEdgeDeploymentPlan' => 'Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan.
', 'DeleteEdgeDeploymentStage' => 'Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
', 'DeleteEndpoint' => 'Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don\'t need to use the RevokeGrant API call.
When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn
, otherwise SageMaker cannot delete these resources.
Deletes an endpoint configuration. The DeleteEndpointConfig
API deletes only the specified configuration. It does not delete endpoints created using the configuration.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. If you delete the EndpointConfig
of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Deletes an SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
', 'DeleteFeatureGroup' => 'Delete the FeatureGroup
and any data that was written to the OnlineStore
of the FeatureGroup
. Data cannot be accessed from the OnlineStore
immediately after DeleteFeatureGroup
is called.
Data written into the OfflineStore
will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your OfflineStore
are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore
FeatureGroup
with the InMemory
StorageType
.
Deletes the specified flow definition.
', 'DeleteHub' => 'Delete a hub.
Hub APIs are only callable through SageMaker Studio.
Delete the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
Use this operation to delete a human task user interface (worker task template).
To see a list of human task user interfaces (work task templates) in your account, use ListHumanTaskUis. When you delete a worker task template, it no longer appears when you call ListHumanTaskUis
.
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob
API deletes only the tuning job entry that was created in SageMaker when you called the CreateHyperParameterTuningJob
API. It does not delete training jobs, artifacts, or the IAM role that you specified when creating the model.
Deletes a SageMaker image and all versions of the image. The container images aren\'t deleted.
', 'DeleteImageVersion' => 'Deletes a version of a SageMaker image. The container image the version represents isn\'t deleted.
', 'DeleteInferenceComponent' => 'Deletes an inference component.
', 'DeleteInferenceExperiment' => 'Deletes an inference experiment.
This operation does not delete your endpoint, variants, or any underlying resources. This operation only deletes the metadata of your experiment.
Deletes a model. The DeleteModel
API deletes only the model entry that was created in SageMaker when you called the CreateModel
API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
Deletes an Amazon SageMaker model bias job definition.
', 'DeleteModelCard' => 'Deletes an Amazon SageMaker Model Card.
', 'DeleteModelExplainabilityJobDefinition' => 'Deletes an Amazon SageMaker model explainability job definition.
', 'DeleteModelPackage' => 'Deletes a model package.
A model package is used to create SageMaker models or list on Amazon Web Services Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
', 'DeleteModelPackageGroup' => 'Deletes the specified model group.
', 'DeleteModelPackageGroupPolicy' => 'Deletes a model group resource policy.
', 'DeleteModelQualityJobDefinition' => 'Deletes the secified model quality monitoring job definition.
', 'DeleteMonitoringSchedule' => 'Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.
', 'DeleteNotebookInstance' => ' Deletes an SageMaker notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance
API.
When you delete a notebook instance, you lose all of your data. SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
Deletes a notebook instance lifecycle configuration.
', 'DeletePipeline' => 'Deletes a pipeline if there are no running instances of the pipeline. To delete a pipeline, you must stop all running instances of the pipeline using the StopPipelineExecution
API. When you delete a pipeline, all instances of the pipeline are deleted.
Delete the specified project.
', 'DeleteSpace' => 'Used to delete a space.
', 'DeleteStudioLifecycleConfig' => 'Deletes the Amazon SageMaker Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.
', 'DeleteTags' => 'Deletes the specified tags from an SageMaker resource.
To list a resource\'s tags, use the ListTags
API.
When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.
When you call this API to delete tags from a SageMaker Domain or User Profile, the deleted tags are not removed from Apps that the SageMaker Domain or User Profile launched before you called this API.
Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.
', 'DeleteTrialComponent' => 'Deletes the specified trial component. A trial component must be disassociated from all trials before the trial component can be deleted. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
', 'DeleteUserProfile' => 'Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
', 'DeleteWorkforce' => 'Use this operation to delete a workforce.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use this operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
If a private workforce contains one or more work teams, you must use the DeleteWorkteam operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse
error.
Deletes an existing work team. This operation can\'t be undone.
', 'DeregisterDevices' => 'Deregisters the specified devices. After you deregister a device, you will need to re-register the devices.
', 'DescribeAction' => 'Describes an action.
', 'DescribeAlgorithm' => 'Returns a description of the specified algorithm that is in your account.
', 'DescribeApp' => 'Describes the app.
', 'DescribeAppImageConfig' => 'Describes an AppImageConfig.
', 'DescribeArtifact' => 'Describes an artifact.
', 'DescribeAutoMLJob' => 'Returns information about an AutoML job created by calling CreateAutoMLJob.
AutoML jobs created by calling CreateAutoMLJobV2 cannot be described by DescribeAutoMLJob
.
Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob.
', 'DescribeCluster' => 'Retrieves information of a SageMaker HyperPod cluster.
', 'DescribeClusterNode' => 'Retrieves information of an instance (also called a node interchangeably) of a SageMaker HyperPod cluster.
', 'DescribeCodeRepository' => 'Gets details about the specified Git repository.
', 'DescribeCompilationJob' => 'Returns information about a model compilation job.
To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
', 'DescribeContext' => 'Describes a context.
', 'DescribeDataQualityJobDefinition' => 'Gets the details of a data quality monitoring job definition.
', 'DescribeDevice' => 'Describes the device.
', 'DescribeDeviceFleet' => 'A description of the fleet the device belongs to.
', 'DescribeDomain' => 'The description of the domain.
', 'DescribeEdgeDeploymentPlan' => 'Describes an edge deployment plan with deployment status per stage.
', 'DescribeEdgePackagingJob' => 'A description of edge packaging jobs.
', 'DescribeEndpoint' => 'Returns the description of an endpoint.
', 'DescribeEndpointConfig' => 'Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
Provides a list of an experiment\'s properties.
', 'DescribeFeatureGroup' => 'Use this operation to describe a FeatureGroup
. The response includes information on the creation time, FeatureGroup
name, the unique identifier for each FeatureGroup
, and more.
Shows the metadata for a feature within a feature group.
', 'DescribeFlowDefinition' => 'Returns information about the specified flow definition.
', 'DescribeHub' => 'Describe a hub.
Hub APIs are only callable through SageMaker Studio.
Describe the content of a hub.
Hub APIs are only callable through SageMaker Studio.
Returns information about the requested human task user interface (worker task template).
', 'DescribeHyperParameterTuningJob' => 'Returns a description of a hyperparameter tuning job, depending on the fields selected. These fields can include the name, Amazon Resource Name (ARN), job status of your tuning job and more.
', 'DescribeImage' => 'Describes a SageMaker image.
', 'DescribeImageVersion' => 'Describes a version of a SageMaker image.
', 'DescribeInferenceComponent' => 'Returns information about an inference component.
', 'DescribeInferenceExperiment' => 'Returns details about an inference experiment.
', 'DescribeInferenceRecommendationsJob' => 'Provides the results of the Inference Recommender job. One or more recommendation jobs are returned.
', 'DescribeLabelingJob' => 'Gets information about a labeling job.
', 'DescribeLineageGroup' => 'Provides a list of properties for the requested lineage group. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
', 'DescribeModel' => 'Describes a model that you created using the CreateModel
API.
Returns a description of a model bias job definition.
', 'DescribeModelCard' => 'Describes the content, creation time, and security configuration of an Amazon SageMaker Model Card.
', 'DescribeModelCardExportJob' => 'Describes an Amazon SageMaker Model Card export job.
', 'DescribeModelExplainabilityJobDefinition' => 'Returns a description of a model explainability job definition.
', 'DescribeModelPackage' => 'Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
To create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
', 'DescribeModelPackageGroup' => 'Gets a description for the specified model group.
', 'DescribeModelQualityJobDefinition' => 'Returns a description of a model quality job definition.
', 'DescribeMonitoringSchedule' => 'Describes the schedule for a monitoring job.
', 'DescribeNotebookInstance' => 'Returns information about a notebook instance.
', 'DescribeNotebookInstanceLifecycleConfig' => 'Returns a description of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'DescribePipeline' => 'Describes the details of a pipeline.
', 'DescribePipelineDefinitionForExecution' => 'Describes the details of an execution\'s pipeline definition.
', 'DescribePipelineExecution' => 'Describes the details of a pipeline execution.
', 'DescribeProcessingJob' => 'Returns a description of a processing job.
', 'DescribeProject' => 'Describes the details of a project.
', 'DescribeSpace' => 'Describes the space.
', 'DescribeStudioLifecycleConfig' => 'Describes the Amazon SageMaker Studio Lifecycle Configuration.
', 'DescribeSubscribedWorkteam' => 'Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the Amazon Web Services Marketplace.
', 'DescribeTrainingJob' => 'Returns information about a training job.
Some of the attributes below only appear if the training job successfully starts. If the training job fails, TrainingJobStatus
is Failed
and, depending on the FailureReason
, attributes like TrainingStartTime
, TrainingTimeInSeconds
, TrainingEndTime
, and BillableTimeInSeconds
may not be present in the response.
Returns information about a transform job.
', 'DescribeTrial' => 'Provides a list of a trial\'s properties.
', 'DescribeTrialComponent' => 'Provides a list of a trials component\'s properties.
', 'DescribeUserProfile' => 'Describes a user profile. For more information, see CreateUserProfile
.
Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team\'s Amazon Resource Name (ARN).
', 'DisableSagemakerServicecatalogPortfolio' => 'Disables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'DisassociateTrialComponent' => 'Disassociates a trial component from a trial. This doesn\'t effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API.
To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent
for the Resource
parameter. The list appears in the response under Results.TrialComponent.Parents
.
Enables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'GetDeviceFleetReport' => 'Describes a fleet.
', 'GetLineageGroupPolicy' => 'The resource policy for the lineage group.
', 'GetModelPackageGroupPolicy' => 'Gets a resource policy that manages access for a model group. For information about resource policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
', 'GetSagemakerServicecatalogPortfolioStatus' => 'Gets the status of Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'GetScalingConfigurationRecommendation' => 'Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.
', 'GetSearchSuggestions' => 'An auto-complete API for the search functionality in the SageMaker console. It returns suggestions of possible matches for the property name to use in Search
queries. Provides suggestions for HyperParameters
, Tags
, and Metrics
.
Import hub content.
Hub APIs are only callable through SageMaker Studio.
Lists the actions in your account and their properties.
', 'ListAlgorithms' => 'Lists the machine learning algorithms that have been created.
', 'ListAliases' => 'Lists the aliases of a specified image or image version.
', 'ListAppImageConfigs' => 'Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.
', 'ListApps' => 'Lists apps.
', 'ListArtifacts' => 'Lists the artifacts in your account and their properties.
', 'ListAssociations' => 'Lists the associations in your account and their properties.
', 'ListAutoMLJobs' => 'Request a list of jobs.
', 'ListCandidatesForAutoMLJob' => 'List the candidates created for the job.
', 'ListClusterNodes' => 'Retrieves the list of instances (also called nodes interchangeably) in a SageMaker HyperPod cluster.
', 'ListClusters' => 'Retrieves the list of SageMaker HyperPod clusters.
', 'ListCodeRepositories' => 'Gets a list of the Git repositories in your account.
', 'ListCompilationJobs' => 'Lists model compilation jobs that satisfy various filters.
To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
', 'ListContexts' => 'Lists the contexts in your account and their properties.
', 'ListDataQualityJobDefinitions' => 'Lists the data quality job definitions in your account.
', 'ListDeviceFleets' => 'Returns a list of devices in the fleet.
', 'ListDevices' => 'A list of devices.
', 'ListDomains' => 'Lists the domains.
', 'ListEdgeDeploymentPlans' => 'Lists all edge deployment plans.
', 'ListEdgePackagingJobs' => 'Returns a list of edge packaging jobs.
', 'ListEndpointConfigs' => 'Lists endpoint configurations.
', 'ListEndpoints' => 'Lists endpoints.
', 'ListExperiments' => 'Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
', 'ListFeatureGroups' => 'List FeatureGroup
s based on given filter and order.
Returns information about the flow definitions in your account.
', 'ListHubContentVersions' => 'List hub content versions.
Hub APIs are only callable through SageMaker Studio.
List the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
List all existing hubs.
Hub APIs are only callable through SageMaker Studio.
Returns information about the human task user interfaces in your account.
', 'ListHyperParameterTuningJobs' => 'Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
', 'ListImageVersions' => 'Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.
', 'ListImages' => 'Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.
', 'ListInferenceComponents' => 'Lists the inference components in your account and their properties.
', 'ListInferenceExperiments' => 'Returns the list of all inference experiments.
', 'ListInferenceRecommendationsJobSteps' => 'Returns a list of the subtasks for an Inference Recommender job.
The supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
', 'ListInferenceRecommendationsJobs' => 'Lists recommendation jobs that satisfy various filters.
', 'ListLabelingJobs' => 'Gets a list of labeling jobs.
', 'ListLabelingJobsForWorkteam' => 'Gets a list of labeling jobs assigned to a specified work team.
', 'ListLineageGroups' => 'A list of lineage groups shared with your Amazon Web Services account. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
', 'ListModelBiasJobDefinitions' => 'Lists model bias jobs definitions that satisfy various filters.
', 'ListModelCardExportJobs' => 'List the export jobs for the Amazon SageMaker Model Card.
', 'ListModelCardVersions' => 'List existing versions of an Amazon SageMaker Model Card.
', 'ListModelCards' => 'List existing model cards.
', 'ListModelExplainabilityJobDefinitions' => 'Lists model explainability job definitions that satisfy various filters.
', 'ListModelMetadata' => 'Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
', 'ListModelPackageGroups' => 'Gets a list of the model groups in your Amazon Web Services account.
', 'ListModelPackages' => 'Lists the model packages that have been created.
', 'ListModelQualityJobDefinitions' => 'Gets a list of model quality monitoring job definitions in your account.
', 'ListModels' => 'Lists models created with the CreateModel
API.
Gets a list of past alerts in a model monitoring schedule.
', 'ListMonitoringAlerts' => 'Gets the alerts for a single monitoring schedule.
', 'ListMonitoringExecutions' => 'Returns list of all monitoring job executions.
', 'ListMonitoringSchedules' => 'Returns list of all monitoring schedules.
', 'ListNotebookInstanceLifecycleConfigs' => 'Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
', 'ListNotebookInstances' => 'Returns a list of the SageMaker notebook instances in the requester\'s account in an Amazon Web Services Region.
', 'ListPipelineExecutionSteps' => 'Gets a list of PipeLineExecutionStep
objects.
Gets a list of the pipeline executions.
', 'ListPipelineParametersForExecution' => 'Gets a list of parameters for a pipeline execution.
', 'ListPipelines' => 'Gets a list of pipelines.
', 'ListProcessingJobs' => 'Lists processing jobs that satisfy various filters.
', 'ListProjects' => 'Gets a list of the projects in an Amazon Web Services account.
', 'ListResourceCatalogs' => ' Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of ResourceCatalog
s viewable is 1000.
Lists spaces.
', 'ListStageDevices' => 'Lists devices allocated to the stage, containing detailed device information and deployment status.
', 'ListStudioLifecycleConfigs' => 'Lists the Amazon SageMaker Studio Lifecycle Configurations in your Amazon Web Services Account.
', 'ListSubscribedWorkteams' => 'Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains
parameter.
Returns the tags for the specified SageMaker resource.
', 'ListTrainingJobs' => 'Lists training jobs.
When StatusEquals
and MaxResults
are set at the same time, the MaxResults
number of training jobs are first retrieved ignoring the StatusEquals
parameter and then they are filtered by the StatusEquals
parameter, which is returned as a response.
For example, if ListTrainingJobs
is invoked with the following parameters:
{ ... MaxResults: 100, StatusEquals: InProgress ... }
First, 100 trainings jobs with any status, including those other than InProgress
, are selected (sorted according to the creation time, from the most current to the oldest). Next, those with a status of InProgress
are returned.
You can quickly test the API using the following Amazon Web Services CLI code.
aws sagemaker list-training-jobs --max-results 100 --status-equals InProgress
Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
', 'ListTransformJobs' => 'Lists transform jobs.
', 'ListTrialComponents' => 'Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
ExperimentName
SourceArn
TrialName
Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
', 'ListUserProfiles' => 'Lists user profiles.
', 'ListWorkforces' => 'Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only have one private workforce per Amazon Web Services Region.
', 'ListWorkteams' => 'Gets a list of private work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains
parameter.
Adds a resouce policy to control access to a model group. For information about resoure policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
', 'QueryLineage' => 'Use this action to inspect your lineage and discover relationships between entities. For more information, see Querying Lineage Entities in the Amazon SageMaker Developer Guide.
', 'RegisterDevices' => 'Register devices.
', 'RenderUiTemplate' => 'Renders the UI template so that you can preview the worker\'s experience.
', 'RetryPipelineExecution' => 'Retry the execution of the pipeline.
', 'Search' => 'Finds SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord
objects in the response. You can sort the search results by any resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
The Search API may provide access to otherwise restricted data. See Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference for more information.
Notifies the pipeline that the execution of a callback step failed, along with a message describing why. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
', 'SendPipelineExecutionStepSuccess' => 'Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step\'s output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
', 'StartEdgeDeploymentStage' => 'Starts a stage in an edge deployment plan.
', 'StartInferenceExperiment' => 'Starts an inference experiment.
', 'StartMonitoringSchedule' => 'Starts a previously stopped monitoring schedule.
By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled
.
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker sets the notebook instance status to InService
. A notebook instance\'s status must be InService
before you can connect to your Jupyter notebook.
Starts a pipeline execution.
', 'StopAutoMLJob' => 'A method for forcing a running job to shut down.
', 'StopCompilationJob' => 'Stops a model compilation job.
To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn\'t stopped, it sends the SIGKILL signal.
When it receives a StopCompilationJob
request, Amazon SageMaker changes the CompilationJobStatus
of the job to Stopping
. After Amazon SageMaker stops the job, it sets the CompilationJobStatus
to Stopped
.
Stops a stage in an edge deployment plan.
', 'StopEdgePackagingJob' => 'Request to stop an edge packaging job.
', 'StopHyperParameterTuningJob' => 'Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped
state, it releases all reserved resources for the tuning job.
Stops an inference experiment.
', 'StopInferenceRecommendationsJob' => 'Stops an Inference Recommender job.
', 'StopLabelingJob' => 'Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
', 'StopMonitoringSchedule' => 'Stops a previously started monitoring schedule.
', 'StopNotebookInstance' => 'Terminates the ML compute instance. Before terminating the instance, SageMaker disconnects the ML storage volume from it. SageMaker preserves the ML storage volume. SageMaker stops charging you for the ML compute instance when you call StopNotebookInstance
.
To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance
API. StartNotebookInstance
launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.
Stops a pipeline execution.
Callback Step
A pipeline execution won\'t stop while a callback step is running. When you call StopPipelineExecution
on a pipeline execution with a running callback step, SageMaker Pipelines sends an additional Amazon SQS message to the specified SQS queue. The body of the SQS message contains a "Status" field which is set to "Stopping".
You should add logic to your Amazon SQS message consumer to take any needed action (for example, resource cleanup) upon receipt of the message followed by a call to SendPipelineExecutionStepSuccess
or SendPipelineExecutionStepFailure
.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
Lambda Step
A pipeline execution can\'t be stopped while a lambda step is running because the Lambda function invoked by the lambda step can\'t be stopped. If you attempt to stop the execution while the Lambda function is running, the pipeline waits for the Lambda function to finish or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function finishes, the pipeline execution status is Stopped
. If the timeout is hit the pipeline execution status is Failed
.
Stops a processing job.
', 'StopTrainingJob' => 'Stops a training job. To stop a job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost.
When it receives a StopTrainingJob
request, SageMaker changes the status of the job to Stopping
. After SageMaker stops the job, it sets the status to Stopped
.
Stops a batch transform job.
When Amazon SageMaker receives a StopTransformJob
request, the status of the job changes to Stopping
. After Amazon SageMaker stops the job, the status is set to Stopped
. When you stop a batch transform job before it is completed, Amazon SageMaker doesn\'t store the job\'s output in Amazon S3.
Updates an action.
', 'UpdateAppImageConfig' => 'Updates the properties of an AppImageConfig.
', 'UpdateArtifact' => 'Updates an artifact.
', 'UpdateCluster' => 'Update a SageMaker HyperPod cluster.
', 'UpdateCodeRepository' => 'Updates the specified Git repository with the specified values.
', 'UpdateContext' => 'Updates a context.
', 'UpdateDeviceFleet' => 'Updates a fleet of devices.
', 'UpdateDevices' => 'Updates one or more devices in a fleet.
', 'UpdateDomain' => 'Updates the default settings for new user profiles in the domain.
', 'UpdateEndpoint' => 'Deploys the EndpointConfig
specified in the request to a new fleet of instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint configuration and then deletes the old instances using the previous EndpointConfig
(there is no availability loss). For more information about how to control the update and traffic shifting process, see Update models in production.
When SageMaker receives the request, it sets the endpoint status to Updating
. After updating the endpoint, it sets the status to InService
. To check the status of an endpoint, use the DescribeEndpoint API.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig
.
If you delete the EndpointConfig
of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, SageMaker sets the endpoint status to Updating
. After updating the endpoint, it sets the status to InService
. To check the status of an endpoint, use the DescribeEndpoint API.
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
', 'UpdateFeatureGroup' => 'Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the UpdateFeatureGroup
API.
You can add features for your feature group using the FeatureAdditions
request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the OnlineStoreConfig
request parameter. If a TtlDuration
is specified, the default TtlDuration
applies for all records added to the feature group after the feature group is updated. If a record level TtlDuration
exists from using the PutRecord
API, the record level TtlDuration
applies to that record instead of the default TtlDuration
.
Updates the description and parameters of the feature group.
', 'UpdateHub' => 'Update a hub.
Hub APIs are only callable through SageMaker Studio.
Updates the properties of a SageMaker image. To change the image\'s tags, use the AddTags and DeleteTags APIs.
', 'UpdateImageVersion' => 'Updates the properties of a SageMaker image version.
', 'UpdateInferenceComponent' => 'Updates an inference component.
', 'UpdateInferenceComponentRuntimeConfig' => 'Runtime settings for a model that is deployed with an inference component.
', 'UpdateInferenceExperiment' => ' Updates an inference experiment that you created. The status of the inference experiment has to be either Created
, Running
. For more information on the status of an inference experiment, see DescribeInferenceExperiment.
Update an Amazon SageMaker Model Card.
You cannot update both model card content and model card status in a single call.
Updates a versioned model.
', 'UpdateMonitoringAlert' => 'Update the parameters of a model monitor alert.
', 'UpdateMonitoringSchedule' => 'Updates a previously created schedule.
', 'UpdateNotebookInstance' => 'Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
', 'UpdateNotebookInstanceLifecycleConfig' => 'Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
', 'UpdatePipeline' => 'Updates a pipeline.
', 'UpdatePipelineExecution' => 'Updates a pipeline execution.
', 'UpdateProject' => 'Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
You must not update a project that is in use. If you update the ServiceCatalogProvisioningUpdateDetails
of a project that is active or being created, or updated, you may lose resources already created by the project.
Updates the settings of a space.
', 'UpdateTrainingJob' => 'Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.
', 'UpdateTrial' => 'Updates the display name of a trial.
', 'UpdateTrialComponent' => 'Updates one or more properties of a trial component.
', 'UpdateUserProfile' => 'Updates a user profile.
', 'UpdateWorkforce' => 'Use this operation to update your workforce. You can use this operation to require that workers use specific IP addresses to work on tasks and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.
The worker portal is now supported in VPC and public internet.
Use SourceIpConfig
to restrict worker access to tasks to a specific range of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs. By default, a workforce isn\'t restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied and get a Not Found
error message on the worker portal.
To restrict access to all the workers in public internet, add the SourceIpConfig
CIDR value as "10.0.0.0/16".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
Use OidcConfig
to update the configuration of a workforce created using your own OIDC IdP.
You can only update your OIDC IdP configuration when there are no work teams associated with your workforce. You can delete work teams using the DeleteWorkteam operation.
After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you can view details about your update workforce using the DescribeWorkforce operation.
This operation only applies to private workforces.
Updates an existing work team with new member definitions or description.
', ], 'shapes' => [ 'Accept' => [ 'base' => NULL, 'refs' => [ 'TransformOutput$Accept' => 'The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
', ], ], 'AcceptEula' => [ 'base' => NULL, 'refs' => [ 'ModelAccessConfig$AcceptEula' => 'Specifies agreement to the model end-user license agreement (EULA). The AcceptEula
value must be explicitly defined as True
in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The Amazon Web Services account ID of the account used to start the labeling job.
', 'VpcOnlyTrustedAccounts$member' => NULL, ], ], 'ActionArn' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'CreateActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'DeleteActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'DescribeActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'UpdateActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', ], ], 'ActionSource' => [ 'base' => 'A structure describing the source of an action.
', 'refs' => [ 'ActionSummary$Source' => 'The source of the action.
', 'CreateActionRequest$Source' => 'The source type, ID, and URI.
', 'DescribeActionResponse$Source' => 'The source of the action.
', ], ], 'ActionStatus' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$Status' => 'The status of the action.
', 'CreateActionRequest$Status' => 'The status of the action.
', 'DescribeActionResponse$Status' => 'The status of the action.
', 'UpdateActionRequest$Status' => 'The new status for the action.
', ], ], 'ActionSummaries' => [ 'base' => NULL, 'refs' => [ 'ListActionsResponse$ActionSummaries' => 'A list of actions and their properties.
', ], ], 'ActionSummary' => [ 'base' => 'Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.
', 'refs' => [ 'ActionSummaries$member' => NULL, ], ], 'AddAssociationRequest' => [ 'base' => NULL, 'refs' => [], ], 'AddAssociationResponse' => [ 'base' => NULL, 'refs' => [], ], 'AddTagsInput' => [ 'base' => NULL, 'refs' => [], ], 'AddTagsOutput' => [ 'base' => NULL, 'refs' => [], ], 'AdditionalCodeRepositoryNamesOrUrls' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$AdditionalCodeRepositories' => 'An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'DescribeNotebookInstanceOutput$AdditionalCodeRepositories' => 'An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'NotebookInstanceSummary$AdditionalCodeRepositories' => 'An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'UpdateNotebookInstanceInput$AdditionalCodeRepositories' => 'An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', ], ], 'AdditionalInferenceSpecificationDefinition' => [ 'base' => 'A structure of additional Inference Specification. Additional Inference Specification specifies details about inference jobs that can be run with models based on this model package
', 'refs' => [ 'AdditionalInferenceSpecifications$member' => NULL, ], ], 'AdditionalInferenceSpecifications' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', 'DescribeModelPackageOutput$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', 'ModelPackage$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects.
', 'UpdateModelPackageInput$AdditionalInferenceSpecificationsToAdd' => 'An array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', ], ], 'AdditionalS3DataSource' => [ 'base' => 'A data source used for training or inference that is in addition to the input dataset or model data.
', 'refs' => [ 'ModelPackageContainerDefinition$AdditionalS3DataSource' => 'The additional data source that is used during inference in the Docker container for your model package.
', 'TrainingSpecification$AdditionalS3DataSource' => 'The additional data source used during the training job.
', ], ], 'AdditionalS3DataSourceDataType' => [ 'base' => NULL, 'refs' => [ 'AdditionalS3DataSource$S3DataType' => 'The data type of the additional data source that you specify for use in inference or training.
', ], ], 'AgentVersion' => [ 'base' => 'Edge Manager agent version.
', 'refs' => [ 'AgentVersions$member' => NULL, ], ], 'AgentVersions' => [ 'base' => NULL, 'refs' => [ 'GetDeviceFleetReportResponse$AgentVersions' => 'The versions of Edge Manager agent deployed on the fleet.
', ], ], 'AggregationTransformationValue' => [ 'base' => NULL, 'refs' => [ 'AggregationTransformations$value' => NULL, ], ], 'AggregationTransformations' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesTransformations$Aggregation' => 'A key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.
The supported aggregation methods are sum
(default), avg
, first
, min
, max
.
Aggregation is only supported for the target column.
An Amazon CloudWatch alarm configured to monitor metrics on an endpoint.
', 'refs' => [ 'AlarmList$member' => NULL, ], ], 'AlarmList' => [ 'base' => NULL, 'refs' => [ 'AutoRollbackConfig$Alarms' => 'List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.
', ], ], 'AlarmName' => [ 'base' => NULL, 'refs' => [ 'Alarm$AlarmName' => 'The name of a CloudWatch alarm in your account.
', ], ], 'AlgorithmArn' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the algorithm.
', 'CreateAlgorithmOutput$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the new algorithm.
', 'DescribeAlgorithmOutput$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the algorithm.
', ], ], 'AlgorithmImage' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$TrainingImage' => 'The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information about using your custom training container, see Using Your Own Algorithms with Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName
parameter or the image URI of the algorithm container to the TrainingImage
parameter.
For more information, see the note in the AlgorithmName
parameter description.
The Amazon Elastic Container (ECR) Image for the managed rule evaluation.
', 'HyperParameterAlgorithmSpecification$TrainingImage' => ' The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. SageMaker supports both registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The Amazon Elastic Container Registry Image for the managed rule evaluation.
', ], ], 'AlgorithmSortBy' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsInput$SortBy' => 'The parameter by which to sort the results. The default is CreationTime
.
Specifies the training algorithm to use in a CreateTrainingJob request.
For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
', 'refs' => [ 'CreateTrainingJobRequest$AlgorithmSpecification' => 'The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about providing your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
', 'DescribeTrainingJobResponse$AlgorithmSpecification' => 'Information about the algorithm used for training, and algorithm metadata.
', 'TrainingJob$AlgorithmSpecification' => 'Information about the algorithm used for training, and algorithm metadata.
', ], ], 'AlgorithmStatus' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$AlgorithmStatus' => 'The overall status of the algorithm.
', 'DescribeAlgorithmOutput$AlgorithmStatus' => 'The current status of the algorithm.
', ], ], 'AlgorithmStatusDetails' => [ 'base' => 'Specifies the validation and image scan statuses of the algorithm.
', 'refs' => [ 'DescribeAlgorithmOutput$AlgorithmStatusDetails' => 'Details about the current status of the algorithm.
', ], ], 'AlgorithmStatusItem' => [ 'base' => 'Represents the overall status of an algorithm.
', 'refs' => [ 'AlgorithmStatusItemList$member' => NULL, ], ], 'AlgorithmStatusItemList' => [ 'base' => NULL, 'refs' => [ 'AlgorithmStatusDetails$ValidationStatuses' => 'The status of algorithm validation.
', 'AlgorithmStatusDetails$ImageScanStatuses' => 'The status of the scan of the algorithm\'s Docker image container.
', ], ], 'AlgorithmSummary' => [ 'base' => 'Provides summary information about an algorithm.
', 'refs' => [ 'AlgorithmSummaryList$member' => NULL, ], ], 'AlgorithmSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsOutput$AlgorithmSummaryList' => '>An array of AlgorithmSummary
objects, each of which lists an algorithm.
Defines a training job and a batch transform job that SageMaker runs to validate your algorithm.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
', 'refs' => [ 'AlgorithmValidationProfiles$member' => NULL, ], ], 'AlgorithmValidationProfiles' => [ 'base' => NULL, 'refs' => [ 'AlgorithmValidationSpecification$ValidationProfiles' => 'An array of AlgorithmValidationProfile
objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm.
Specifies configurations for one or more training jobs that SageMaker runs to test the algorithm.
', 'refs' => [ 'CreateAlgorithmInput$ValidationSpecification' => 'Specifies configurations for one or more training jobs and that SageMaker runs to test the algorithm\'s training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm\'s inference code.
', 'DescribeAlgorithmOutput$ValidationSpecification' => 'Details about configurations for one or more training jobs that SageMaker runs to test the algorithm.
', ], ], 'AnnotationConsolidationConfig' => [ 'base' => 'Configures how labels are consolidated across human workers and processes output data.
', 'refs' => [ 'HumanTaskConfig$AnnotationConsolidationConfig' => 'Configures how labels are consolidated across human workers.
', ], ], 'AppArn' => [ 'base' => NULL, 'refs' => [ 'CreateAppResponse$AppArn' => 'The Amazon Resource Name (ARN) of the app.
', 'DescribeAppResponse$AppArn' => 'The Amazon Resource Name (ARN) of the app.
', ], ], 'AppDetails' => [ 'base' => 'Details about an Amazon SageMaker app.
', 'refs' => [ 'AppList$member' => NULL, ], ], 'AppImageConfigArn' => [ 'base' => NULL, 'refs' => [ 'AppImageConfigDetails$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'CreateAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'DescribeAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'UpdateAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) for the AppImageConfig.
', ], ], 'AppImageConfigDetails' => [ 'base' => 'The configuration for running a SageMaker image as a KernelGateway app.
', 'refs' => [ 'AppImageConfigList$member' => NULL, ], ], 'AppImageConfigList' => [ 'base' => NULL, 'refs' => [ 'ListAppImageConfigsResponse$AppImageConfigs' => 'A list of AppImageConfigs and their properties.
', ], ], 'AppImageConfigName' => [ 'base' => NULL, 'refs' => [ 'AppImageConfigDetails$AppImageConfigName' => 'The name of the AppImageConfig. Must be unique to your account.
', 'CreateAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig. Must be unique to your account.
', 'CustomImage$AppImageConfigName' => 'The name of the AppImageConfig.
', 'DeleteAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to delete.
', 'DescribeAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to describe.
', 'DescribeAppImageConfigResponse$AppImageConfigName' => 'The name of the AppImageConfig.
', 'ListAppImageConfigsRequest$NameContains' => 'A filter that returns only AppImageConfigs whose name contains the specified string.
', 'UpdateAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to update.
', ], ], 'AppImageConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListAppImageConfigsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime
.
The instance type that the image version runs on.
JupyterServer apps only support the system
value.
For KernelGateway apps, the system
value is translated to ml.t3.medium
. KernelGateway apps also support all other values for available instance types.
The list of apps.
', ], ], 'AppManaged' => [ 'base' => NULL, 'refs' => [ 'ProcessingInput$AppManaged' => 'When True
, input operations such as data download are managed natively by the processing job application. When False
(default), input operations are managed by Amazon SageMaker.
When True
, output operations such as data upload are managed natively by the processing job application. When False
(default), output operations are managed by Amazon SageMaker.
The name of the app.
', 'CreateAppRequest$AppName' => 'The name of the app.
', 'DeleteAppRequest$AppName' => 'The name of the app.
', 'DescribeAppRequest$AppName' => 'The name of the app.
', 'DescribeAppResponse$AppName' => 'The name of the app.
', ], ], 'AppNetworkAccessType' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$AppNetworkAccessType' => 'Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly
.
PublicInternetOnly
- Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly
- All traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly
.
PublicInternetOnly
- Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly
- All traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic.
PublicInternetOnly
- Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access.
VpcOnly
- All Studio traffic is through the specified VPC and subnets.
This configuration can only be modified if there are no apps in the InService
, Pending
, or Deleting
state. The configuration cannot be updated if DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is already set or DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided as part of the same request.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly
mode. Required when CreateDomain.AppNetworkAccessType
is VPCOnly
and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided. If setting up the domain for use with RStudio, this value must be set to Service
.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly
mode. Required when CreateDomain.AppNetworkAccessType
is VPCOnly
and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly
mode. Required when CreateDomain.AppNetworkAccessType
is VPCOnly
and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided. If setting up the domain for use with RStudio, this value must be set to Service
.
The parameter by which to sort the results. The default is CreationTime.
', ], ], 'AppSpecification' => [ 'base' => 'Configuration to run a processing job in a specified container image.
', 'refs' => [ 'CreateProcessingJobRequest$AppSpecification' => 'Configures the processing job to run a specified Docker container image.
', 'DescribeProcessingJobResponse$AppSpecification' => 'Configures the processing job to run a specified container image.
', 'ProcessingJob$AppSpecification' => NULL, ], ], 'AppStatus' => [ 'base' => NULL, 'refs' => [ 'AppDetails$Status' => 'The status.
', 'DescribeAppResponse$Status' => 'The status.
', ], ], 'AppType' => [ 'base' => NULL, 'refs' => [ 'AppDetails$AppType' => 'The type of app.
', 'CreateAppRequest$AppType' => 'The type of app.
', 'DeleteAppRequest$AppType' => 'The type of app.
', 'DescribeAppRequest$AppType' => 'The type of app.
', 'DescribeAppResponse$AppType' => 'The type of app.
', 'SpaceSettings$AppType' => 'The type of app created within the space.
', 'SpaceSettingsSummary$AppType' => 'The type of app created within the space.
', ], ], 'ApprovalDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeModelPackageOutput$ApprovalDescription' => 'A description provided for the model approval.
', 'ModelPackage$ApprovalDescription' => 'A description provided when the model approval is set.
', 'UpdateModelPackageInput$ApprovalDescription' => 'A description for the approval status of the model.
', ], ], 'ArnOrName' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$AlgorithmName' => 'The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the AlgorithmName
parameter or the image URI of the algorithm container to the TrainingImage
parameter.
Note that the AlgorithmName
parameter is mutually exclusive with the TrainingImage
parameter. If you specify a value for the AlgorithmName
parameter, you can\'t specify a value for TrainingImage
, and vice versa.
If you specify values for both parameters, the training job might break; if you don\'t specify any value for both parameters, the training job might raise a null
error.
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
', 'DeleteModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group to delete.
', 'DescribeAlgorithmInput$AlgorithmName' => 'The name of the algorithm to describe.
', 'DescribeModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group to describe.
', 'HyperParameterAlgorithmSpecification$AlgorithmName' => 'The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage
.
A filter that returns only model versions that belong to the specified model group.
', 'SourceAlgorithm$AlgorithmName' => 'The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
', ], ], 'ArtifactArn' => [ 'base' => NULL, 'refs' => [ 'ArtifactSummary$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'CreateArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'DeleteArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to delete.
', 'DeleteArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'DescribeArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to describe.
', 'DescribeArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'UpdateArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to update.
', 'UpdateArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', ], ], 'ArtifactDigest' => [ 'base' => NULL, 'refs' => [ 'ModelDigests$ArtifactDigest' => 'Provides a hash value that uniquely identifies the stored model artifacts.
', ], ], 'ArtifactProperties' => [ 'base' => NULL, 'refs' => [ 'CreateArtifactRequest$Properties' => 'A list of properties to add to the artifact.
', 'UpdateArtifactRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', ], ], 'ArtifactPropertyValue' => [ 'base' => NULL, 'refs' => [ 'ArtifactProperties$value' => NULL, ], ], 'ArtifactSource' => [ 'base' => 'A structure describing the source of an artifact.
', 'refs' => [ 'ArtifactSummary$Source' => 'The source of the artifact.
', 'CreateArtifactRequest$Source' => 'The ID, ID type, and URI of the source.
', 'DeleteArtifactRequest$Source' => 'The URI of the source.
', 'DescribeArtifactResponse$Source' => 'The source of the artifact.
', ], ], 'ArtifactSourceIdType' => [ 'base' => NULL, 'refs' => [ 'ArtifactSourceType$SourceIdType' => 'The type of ID.
', ], ], 'ArtifactSourceType' => [ 'base' => 'The ID and ID type of an artifact source.
', 'refs' => [ 'ArtifactSourceTypes$member' => NULL, ], ], 'ArtifactSourceTypes' => [ 'base' => NULL, 'refs' => [ 'ArtifactSource$SourceTypes' => 'A list of source types.
', ], ], 'ArtifactSummaries' => [ 'base' => NULL, 'refs' => [ 'ListArtifactsResponse$ArtifactSummaries' => 'A list of artifacts and their properties.
', ], ], 'ArtifactSummary' => [ 'base' => 'Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.
', 'refs' => [ 'ArtifactSummaries$member' => NULL, ], ], 'AssemblyType' => [ 'base' => NULL, 'refs' => [ 'TransformOutput$AssembleWith' => 'Defines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None
. To add a newline character at the end of every transformed record, specify Line
.
The type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.
ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.
AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.
DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.
Produced - The source generated the destination. For example, a training job produced a model artifact.
The type of the association.
', 'Edge$AssociationType' => 'The type of the Association(Edge) between the source and destination. For example ContributedTo
, Produced
, or DerivedFrom
.
A filter that returns only associations of the specified type.
', ], ], 'AssociationEntityArn' => [ 'base' => NULL, 'refs' => [ 'AddAssociationRequest$SourceArn' => 'The ARN of the source.
', 'AddAssociationRequest$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'AddAssociationResponse$SourceArn' => 'The ARN of the source.
', 'AddAssociationResponse$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'AssociationSummary$SourceArn' => 'The ARN of the source.
', 'AssociationSummary$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'DeleteAssociationRequest$SourceArn' => 'The ARN of the source.
', 'DeleteAssociationRequest$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'DeleteAssociationResponse$SourceArn' => 'The ARN of the source.
', 'DeleteAssociationResponse$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'Edge$SourceArn' => 'The Amazon Resource Name (ARN) of the source lineage entity of the directed edge.
', 'Edge$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination lineage entity of the directed edge.
', 'ListAssociationsRequest$SourceArn' => 'A filter that returns only associations with the specified source ARN.
', 'ListAssociationsRequest$DestinationArn' => 'A filter that returns only associations with the specified destination Amazon Resource Name (ARN).
', 'QueryLineageStartArns$member' => NULL, 'Vertex$Arn' => 'The Amazon Resource Name (ARN) of the lineage entity resource.
', ], ], 'AssociationSummaries' => [ 'base' => NULL, 'refs' => [ 'ListAssociationsResponse$AssociationSummaries' => 'A list of associations and their properties.
', ], ], 'AssociationSummary' => [ 'base' => 'Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.
', 'refs' => [ 'AssociationSummaries$member' => NULL, ], ], 'AsyncInferenceClientConfig' => [ 'base' => 'Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
', 'refs' => [ 'AsyncInferenceConfig$ClientConfig' => 'Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
', ], ], 'AsyncInferenceConfig' => [ 'base' => 'Specifies configuration for how an endpoint performs asynchronous inference.
', 'refs' => [ 'CreateEndpointConfigInput$AsyncInferenceConfig' => 'Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
', 'DescribeEndpointConfigOutput$AsyncInferenceConfig' => 'Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
Specifies the configuration for notifications of inference results for asynchronous inference.
', 'refs' => [ 'AsyncInferenceOutputConfig$NotificationConfig' => 'Specifies the configuration for notifications of inference results for asynchronous inference.
', ], ], 'AsyncInferenceOutputConfig' => [ 'base' => 'Specifies the configuration for asynchronous inference invocation outputs.
', 'refs' => [ 'AsyncInferenceConfig$OutputConfig' => 'Specifies the configuration for asynchronous inference invocation outputs.
', ], ], 'AsyncNotificationTopicTypeList' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceNotificationConfig$IncludeInferenceResponseIn' => 'The Amazon SNS topics where you want the inference response to be included.
The inference response is included only if the response size is less than or equal to 128 KB.
The name of the data catalog used in Athena query execution.
', 'refs' => [ 'AthenaDatasetDefinition$Catalog' => NULL, ], ], 'AthenaDatabase' => [ 'base' => 'The name of the database used in the Athena query execution.
', 'refs' => [ 'AthenaDatasetDefinition$Database' => NULL, ], ], 'AthenaDatasetDefinition' => [ 'base' => 'Configuration for Athena Dataset Definition input.
', 'refs' => [ 'DatasetDefinition$AthenaDatasetDefinition' => NULL, ], ], 'AthenaQueryString' => [ 'base' => 'The SQL query statements, to be executed.
', 'refs' => [ 'AthenaDatasetDefinition$QueryString' => NULL, ], ], 'AthenaResultCompressionType' => [ 'base' => 'The compression used for Athena query results.
', 'refs' => [ 'AthenaDatasetDefinition$OutputCompression' => NULL, ], ], 'AthenaResultFormat' => [ 'base' => 'The data storage format for Athena query results.
', 'refs' => [ 'AthenaDatasetDefinition$OutputFormat' => NULL, ], ], 'AthenaWorkGroup' => [ 'base' => 'The name of the workgroup in which the Athena query is being started.
', 'refs' => [ 'AthenaDatasetDefinition$WorkGroup' => NULL, ], ], 'AttributeName' => [ 'base' => NULL, 'refs' => [ 'AttributeNames$member' => NULL, ], ], 'AttributeNames' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$AttributeNames' => 'A list of one or more attribute names to use that are found in a specified augmented manifest file.
', ], ], 'AuthMode' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$AuthMode' => 'The mode of authentication that members use to access the domain.
', 'DescribeDomainResponse$AuthMode' => 'The domain\'s authentication mode.
', ], ], 'AutoGenerateEndpointName' => [ 'base' => NULL, 'refs' => [ 'ModelDeployConfig$AutoGenerateEndpointName' => 'Set to True
to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False
otherwise. The default value is False
.
If you set AutoGenerateEndpointName
to True
, do not specify the EndpointName
; otherwise a 400 error is thrown.
The collection of algorithms run on a dataset for training the model candidates of an Autopilot job.
', 'refs' => [ 'AutoMLAlgorithmsConfig$member' => NULL, ], ], 'AutoMLAlgorithms' => [ 'base' => NULL, 'refs' => [ 'AutoMLAlgorithmConfig$AutoMLAlgorithms' => 'The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (ENSEMBLING
or HYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.
In ENSEMBLING
mode:
"catboost"
"extra-trees"
"fastai"
"lightgbm"
"linear-learner"
"nn-torch"
"randomforest"
"xgboost"
In HYPERPARAMETER_TUNING
mode:
"linear-learner"
"mlp"
"xgboost"
Stores the configuration information for the selection of algorithms used to train the model candidates.
The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode
.
AlgorithmsConfig
should not be set in AUTO
training mode.
When AlgorithmsConfig
is provided, one AutoMLAlgorithms
attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms
is empty, AutoMLCandidateGenerationConfig
uses the full set of algorithms for the given training mode.
When AlgorithmsConfig
is not provided, AutoMLCandidateGenerationConfig
uses the full set of algorithms for the given training mode.
For the list of all algorithms per training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
', 'CandidateGenerationConfig$AlgorithmsConfig' => 'Stores the configuration information for the selection of algorithms used to train model candidates on tabular data.
The list of available algorithms to choose from depends on the training mode set in TabularJobConfig.Mode
.
AlgorithmsConfig
should not be set in AUTO
training mode.
When AlgorithmsConfig
is provided, one AutoMLAlgorithms
attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms
is empty, CandidateGenerationConfig
uses the full set of algorithms for the given training mode.
When AlgorithmsConfig
is not provided, CandidateGenerationConfig
uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
', ], ], 'AutoMLCandidate' => [ 'base' => 'Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.
', 'refs' => [ 'AutoMLCandidates$member' => NULL, 'DescribeAutoMLJobResponse$BestCandidate' => 'The best model candidate selected by SageMaker Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.
', 'DescribeAutoMLJobV2Response$BestCandidate' => 'Information about the candidate produced by an AutoML training job V2, including its status, steps, and other properties.
', ], ], 'AutoMLCandidateGenerationConfig' => [ 'base' => 'Stores the configuration information for how a candidate is generated (optional).
', 'refs' => [ 'AutoMLJobConfig$CandidateGenerationConfig' => 'The configuration for generating a candidate for an AutoML job (optional).
', ], ], 'AutoMLCandidateStep' => [ 'base' => 'Information about the steps for a candidate and what step it is working on.
', 'refs' => [ 'CandidateSteps$member' => NULL, ], ], 'AutoMLCandidates' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobResponse$Candidates' => 'Summaries about the AutoMLCandidates
.
A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.
A validation dataset must contain the same headers as the training dataset.
The channel type (optional) is an enum
string. The default value is training
. Channels for training and validation must share the same ContentType
and TargetAttributeName
. For information on specifying training and validation channel types, see How to specify training and validation datasets.
The type of channel. Defines whether the data are used for training or validation. The default value is training
. Channels for training
and validation
must share the same ContentType
The type of channel defaults to training
for the time-series forecasting problem type.
A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see ContainerDefinition.
', 'refs' => [ 'AutoMLContainerDefinitions$member' => NULL, ], ], 'AutoMLContainerDefinitions' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$InferenceContainers' => 'Information about the recommended inference container definitions.
', 'AutoMLInferenceContainerDefinitions$value' => 'Information about the recommended inference container definitions.
', ], ], 'AutoMLDataSource' => [ 'base' => 'The data source for the Autopilot job.
', 'refs' => [ 'AutoMLChannel$DataSource' => 'The data source for an AutoML channel.
', 'AutoMLJobChannel$DataSource' => 'The data source for an AutoML channel (Required).
', ], ], 'AutoMLDataSplitConfig' => [ 'base' => 'This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob
, the validation dataset must be less than 2 GB in size.
The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
', 'CreateAutoMLJobV2Request$DataSplitConfig' => 'This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob
, the validation dataset must be less than 2 GB in size.
This attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.
Returns the configuration settings of how the data are split into train and validation datasets.
', ], ], 'AutoMLFailureReason' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$FailureReason' => 'The failure reason.
', 'AutoMLJobSummary$FailureReason' => 'The failure reason of an AutoML job.
', 'AutoMLPartialFailureReason$PartialFailureMessage' => 'The message containing the reason for a partial failure of an AutoML job.
', 'DescribeAutoMLJobResponse$FailureReason' => 'Returns the failure reason for an AutoML job, when applicable.
', 'DescribeAutoMLJobV2Response$FailureReason' => 'Returns the reason for the failure of the AutoML job V2, when applicable.
', ], ], 'AutoMLInferenceContainerDefinitions' => [ 'base' => 'The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the V2 API only (for example, for jobs created by calling CreateAutoMLJobV2
).
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the AutoML jobs V2 (for example, for jobs created by calling CreateAutoMLJobV2
) related to image or text classification problem types only.
An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig
supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.
Returns the input data configuration for the AutoML job.
', ], ], 'AutoMLJobArn' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the AutoML job.
', 'AutoMLJobSummary$AutoMLJobArn' => 'The ARN of the AutoML job.
', 'CreateAutoMLJobResponse$AutoMLJobArn' => 'The unique ARN assigned to the AutoML job when it is created.
', 'CreateAutoMLJobV2Response$AutoMLJobArn' => 'The unique ARN assigned to the AutoMLJob when it is created.
', 'DescribeAutoMLJobResponse$AutoMLJobArn' => 'Returns the ARN of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobArn' => 'Returns the Amazon Resource Name (ARN) of the AutoML job V2.
', 'DescribeProcessingJobResponse$AutoMLJobArn' => 'The ARN of an AutoML job associated with this processing job.
', 'DescribeTrainingJobResponse$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of an AutoML job.
', 'DescribeTransformJobResponse$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML transform job.
', 'ProcessingJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.
', 'TrainingJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the job.
', 'TransformJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML job that created the transform job.
', ], ], 'AutoMLJobArtifacts' => [ 'base' => 'The artifacts that are generated during an AutoML job.
', 'refs' => [ 'DescribeAutoMLJobResponse$AutoMLJobArtifacts' => 'Returns information on the job\'s artifacts found in AutoMLJobArtifacts
.
A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
', 'refs' => [ 'AutoMLJobInputDataConfig$member' => NULL, ], ], 'AutoMLJobCompletionCriteria' => [ 'base' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'refs' => [ 'AutoMLJobConfig$CompletionCriteria' => 'How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
', 'AutoMLResolvedAttributes$CompletionCriteria' => NULL, 'ImageClassificationJobConfig$CompletionCriteria' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'ResolvedAttributes$CompletionCriteria' => NULL, 'TabularJobConfig$CompletionCriteria' => NULL, 'TextClassificationJobConfig$CompletionCriteria' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'TextGenerationJobConfig$CompletionCriteria' => 'How long a fine-tuning job is allowed to run. For TextGenerationJobConfig
problem types, the MaxRuntimePerTrainingJobInSeconds
attribute of AutoMLJobCompletionCriteria
defaults to 72h (259200s).
A collection of settings used for an AutoML job.
', 'refs' => [ 'CreateAutoMLJobRequest$AutoMLJobConfig' => 'A collection of settings used to configure an AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobConfig' => 'Returns the configuration for the AutoML job.
', ], ], 'AutoMLJobInputDataConfig' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobV2Request$AutoMLJobInputDataConfig' => 'An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob
input parameters. The supported formats depend on the problem type:
For tabular problem types: S3Prefix
, ManifestFile
.
For image classification: S3Prefix
, ManifestFile
, AugmentedManifestFile
.
For text classification: S3Prefix
.
For time-series forecasting: S3Prefix
.
For text generation (LLMs fine-tuning): S3Prefix
.
Returns an array of channel objects describing the input data and their location.
', ], ], 'AutoMLJobName' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobName' => 'The name of the AutoML job you are requesting.
', 'CreateAutoMLJobRequest$AutoMLJobName' => 'Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
', 'CreateAutoMLJobV2Request$AutoMLJobName' => 'Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
', 'DescribeAutoMLJobRequest$AutoMLJobName' => 'Requests information about an AutoML job using its unique name.
', 'DescribeAutoMLJobResponse$AutoMLJobName' => 'Returns the name of the AutoML job.
', 'DescribeAutoMLJobV2Request$AutoMLJobName' => 'Requests information about an AutoML job V2 using its unique name.
', 'DescribeAutoMLJobV2Response$AutoMLJobName' => 'Returns the name of the AutoML job V2.
', 'ListCandidatesForAutoMLJobRequest$AutoMLJobName' => 'List the candidates created for the job by providing the job\'s name.
', 'StopAutoMLJobRequest$AutoMLJobName' => 'The name of the object you are requesting.
', ], ], 'AutoMLJobObjective' => [ 'base' => 'Specifies a metric to minimize or maximize as the objective of an AutoML job.
', 'refs' => [ 'AutoMLResolvedAttributes$AutoMLJobObjective' => NULL, 'CreateAutoMLJobRequest$AutoMLJobObjective' => 'Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
', 'CreateAutoMLJobV2Request$AutoMLJobObjective' => 'Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.
For tabular problem types: You must either provide both the AutoMLJobObjective
and indicate the type of supervised learning problem in AutoMLProblemTypeConfig
(TabularJobConfig.ProblemType
), or none at all.
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective
field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
Returns the job\'s objective.
', 'DescribeAutoMLJobV2Response$AutoMLJobObjective' => 'Returns the job\'s objective.
', 'ResolvedAttributes$AutoMLJobObjective' => NULL, ], ], 'AutoMLJobObjectiveType' => [ 'base' => NULL, 'refs' => [ 'FinalAutoMLJobObjectiveMetric$Type' => 'The type of metric with the best result.
', ], ], 'AutoMLJobSecondaryStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobSecondaryStatus' => 'The secondary status of the AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobSecondaryStatus' => 'Returns the secondary status of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobSecondaryStatus' => 'Returns the secondary status of the AutoML job V2.
', ], ], 'AutoMLJobStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobStatus' => 'The status of the AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobStatus' => 'Returns the status of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobStatus' => 'Returns the status of the AutoML job V2.
', 'ListAutoMLJobsRequest$StatusEquals' => 'Request a list of jobs, using a filter for status.
', ], ], 'AutoMLJobStepMetadata' => [ 'base' => 'Metadata for an AutoML job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$AutoMLJob' => 'The Amazon Resource Name (ARN) of the AutoML job that was run by this step.
', ], ], 'AutoMLJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsResponse$AutoMLJobSummaries' => 'Returns a summary list of jobs.
', ], ], 'AutoMLJobSummary' => [ 'base' => 'Provides a summary about an AutoML job.
', 'refs' => [ 'AutoMLJobSummaries$member' => NULL, ], ], 'AutoMLMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsRequest$MaxResults' => 'Request a list of jobs up to a specified limit.
', ], ], 'AutoMLMaxResultsForTrials' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobRequest$MaxResults' => 'List the job\'s candidates up to a specified limit.
', ], ], 'AutoMLMetricEnum' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobObjective$MetricName' => 'The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model\'s parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.
The list of available metrics supported by Autopilot and the default metric applied when you do not specify a metric name explicitly depend on the problem type.
For tabular problem types:
List of available metrics:
Regression: InferenceLatency
, MAE
, MSE
, R2
, RMSE
Binary classification: Accuracy
, AUC
, BalancedAccuracy
, F1
, InferenceLatency
, LogLoss
, Precision
, Recall
Multiclass classification: Accuracy
, BalancedAccuracy
, F1macro
, InferenceLatency
, LogLoss
, PrecisionMacro
, RecallMacro
For a description of each metric, see Autopilot metrics for classification and regression.
Default objective metrics:
Regression: MSE
.
Binary classification: F1
.
Multiclass classification: Accuracy
.
For image or text classification problem types:
List of available metrics: Accuracy
For a description of each metric, see Autopilot metrics for text and image classification.
Default objective metrics: Accuracy
For time-series forecasting problem types:
List of available metrics: RMSE
, wQL
, Average wQL
, MASE
, MAPE
, WAPE
For a description of each metric, see Autopilot metrics for time-series forecasting.
Default objective metrics: AverageWeightedQuantileLoss
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective
field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.
', 'FinalAutoMLJobObjectiveMetric$StandardMetricName' => 'The name of the standard metric. For a description of the standard metrics, see Autopilot candidate metrics.
', 'MetricDatum$MetricName' => 'The name of the metric.
', ], ], 'AutoMLMetricExtendedEnum' => [ 'base' => NULL, 'refs' => [ 'MetricDatum$StandardMetricName' => 'The name of the standard metric.
For definitions of the standard metrics, see Autopilot candidate metrics
.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO
. In AUTO
mode, Autopilot chooses ENSEMBLING
for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING
for larger ones.
The ENSEMBLING
mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING
mode.
The HYPERPARAMETER_TUNING
(HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING
mode.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO
. In AUTO
mode, Autopilot chooses ENSEMBLING
for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING
for larger ones.
The ENSEMBLING
mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING
mode.
The HYPERPARAMETER_TUNING
(HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING
mode.
Request a list of jobs, using a search filter for name.
', ], ], 'AutoMLOutputDataConfig' => [ 'base' => 'The output data configuration.
', 'refs' => [ 'CreateAutoMLJobRequest$OutputDataConfig' => 'Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
', 'CreateAutoMLJobV2Request$OutputDataConfig' => 'Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
', 'DescribeAutoMLJobResponse$OutputDataConfig' => 'Returns the job\'s output data config.
', 'DescribeAutoMLJobV2Response$OutputDataConfig' => 'Returns the job\'s output data config.
', ], ], 'AutoMLPartialFailureReason' => [ 'base' => 'The reason for a partial failure of an AutoML job.
', 'refs' => [ 'AutoMLPartialFailureReasons$member' => NULL, ], ], 'AutoMLPartialFailureReasons' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$PartialFailureReasons' => 'The list of reasons for partial failures within an AutoML job.
', 'DescribeAutoMLJobResponse$PartialFailureReasons' => 'Returns a list of reasons for partial failures within an AutoML job.
', 'DescribeAutoMLJobV2Response$PartialFailureReasons' => 'Returns a list of reasons for partial failures within an AutoML job V2.
', ], ], 'AutoMLProblemTypeConfig' => [ 'base' => 'A collection of settings specific to the problem type used to configure an AutoML job V2. There must be one and only one config of the following type.
', 'refs' => [ 'CreateAutoMLJobV2Request$AutoMLProblemTypeConfig' => 'Defines the configuration settings of one of the supported problem types.
', 'DescribeAutoMLJobV2Response$AutoMLProblemTypeConfig' => 'Returns the configuration settings of the problem type set for the AutoML job V2.
', ], ], 'AutoMLProblemTypeConfigName' => [ 'base' => NULL, 'refs' => [ 'DescribeAutoMLJobV2Response$AutoMLProblemTypeConfigName' => 'Returns the name of the problem type configuration set for the AutoML job V2.
', ], ], 'AutoMLProblemTypeResolvedAttributes' => [ 'base' => 'Stores resolved attributes specific to the problem type of an AutoML job V2.
', 'refs' => [ 'AutoMLResolvedAttributes$AutoMLProblemTypeResolvedAttributes' => 'Defines the resolved attributes specific to a problem type.
', ], ], 'AutoMLProcessingUnit' => [ 'base' => NULL, 'refs' => [ 'AutoMLInferenceContainerDefinitions$key' => 'Processing unit for an inference container. Currently Autopilot only supports CPU
or GPU
.
The resolved attributes used to configure an AutoML job V2.
', 'refs' => [ 'DescribeAutoMLJobV2Response$ResolvedAttributes' => 'Returns the resolved attributes used by the AutoML job V2.
', ], ], 'AutoMLS3DataSource' => [ 'base' => 'Describes the Amazon S3 data source.
', 'refs' => [ 'AutoMLDataSource$S3DataSource' => 'The Amazon S3 location of the input data.
', ], ], 'AutoMLS3DataType' => [ 'base' => NULL, 'refs' => [ 'AutoMLS3DataSource$S3DataType' => 'The data type.
If you choose S3Prefix
, S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
The S3Prefix
should have the following format:
s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE
If you choose ManifestFile
, S3Uri
identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
A ManifestFile
should have the format shown below:
[ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"},
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",
... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]
If you choose AugmentedManifestFile
, S3Uri
identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile
is available for V2 API jobs only (for example, for jobs created by calling CreateAutoMLJobV2
).
Here is a minimal, single-record example of an AugmentedManifestFile
:
{"source-ref": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",
"label-metadata": {"class-name": "cat"
}
For more information on AugmentedManifestFile
, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.
Security options.
', 'refs' => [ 'AutoMLJobConfig$SecurityConfig' => 'The security configuration for traffic encryption or Amazon VPC settings.
', 'CreateAutoMLJobV2Request$SecurityConfig' => 'The security configuration for traffic encryption or Amazon VPC settings.
', 'DescribeAutoMLJobV2Response$SecurityConfig' => 'Returns the security configuration for traffic encryption or Amazon VPC settings.
', ], ], 'AutoMLSortBy' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsRequest$SortBy' => 'The parameter by which to sort the results. The default is Name
.
The sort order for the results. The default is Descending
.
The sort order for the results. The default is Ascending
.
The name and an example value of the hyperparameter that you want to use in Autotune. If Automatic model tuning (AMT) determines that your hyperparameter is eligible for Autotune, an optimal hyperparameter range is selected for you.
', 'refs' => [ 'AutoParameters$member' => NULL, ], ], 'AutoParameters' => [ 'base' => NULL, 'refs' => [ 'ParameterRanges$AutoParameters' => 'A list containing hyperparameter names and example values to be used by Autotune to determine optimal ranges for your tuning job.
', ], ], 'AutoRollbackConfig' => [ 'base' => 'Automatic rollback configuration for handling endpoint deployment failures and recovery.
', 'refs' => [ 'DeploymentConfig$AutoRollbackConfiguration' => 'Automatic rollback configuration for handling endpoint deployment failures and recovery.
', ], ], 'Autotune' => [ 'base' => 'A flag to indicate if you want to use Autotune to automatically find optimal values for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
A flag to indicate if autotune is enabled for the hyperparameter tuning job.
', ], ], 'AutotuneMode' => [ 'base' => NULL, 'refs' => [ 'Autotune$Mode' => 'Set Mode
to Enabled
if you want to use Autotune.
Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. The default field settings and JSON parsing rules are different based on the integration source. Valid values:
', ], ], 'BacktestResultsLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$BacktestResults' => 'The Amazon S3 prefix to the accuracy metrics and the inference results observed over the testing window. Available only for the time-series forecasting problem type.
', ], ], 'BaseModelName' => [ 'base' => NULL, 'refs' => [ 'TextGenerationJobConfig$BaseModelName' => 'The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no BaseModelName
is provided, the default model used is Falcon7BInstruct.
The name of the base model to fine-tune.
', ], ], 'BatchDataCaptureConfig' => [ 'base' => 'Configuration to control how SageMaker captures inference data for batch transform jobs.
', 'refs' => [ 'CreateTransformJobRequest$DataCaptureConfig' => 'Configuration to control how SageMaker captures inference data.
', 'DescribeTransformJobResponse$DataCaptureConfig' => 'Configuration to control how SageMaker captures inference data.
', 'TransformJob$DataCaptureConfig' => NULL, ], ], 'BatchDescribeModelPackageError' => [ 'base' => 'The error code and error description associated with the resource.
', 'refs' => [ 'BatchDescribeModelPackageErrorMap$value' => NULL, ], ], 'BatchDescribeModelPackageErrorMap' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageOutput$BatchDescribeModelPackageErrorMap' => 'A map of the resource and BatchDescribeModelPackageError objects reporting the error associated with describing the model package.
', ], ], 'BatchDescribeModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'BatchDescribeModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'BatchDescribeModelPackageSummary' => [ 'base' => 'Provides summary information about the model package.
', 'refs' => [ 'ModelPackageSummaries$value' => NULL, ], ], 'BatchStrategy' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$BatchStrategy' => 'Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set the SplitType
property to Line
, RecordIO
, or TFRecord
.
To use only one record when making an HTTP invocation request to a container, set BatchStrategy
to SingleRecord
and SplitType
to Line
.
To fit as many records in a mini-batch as can fit within the MaxPayloadInMB
limit, set BatchStrategy
to MultiRecord
and SplitType
to Line
.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set SplitType
to Line
, RecordIO
, or TFRecord
.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
', 'TransformJobDefinition$BatchStrategy' => 'A string that determines the number of records included in a single mini-batch.
SingleRecord
means only one record is used per mini-batch. MultiRecord
means a mini-batch is set to contain as many records that can fit within the MaxPayloadInMB
limit.
Input object for the batch transform job.
', 'refs' => [ 'DataQualityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelBiasJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelDashboardMonitoringSchedule$BatchTransformInput' => NULL, 'ModelExplainabilityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelQualityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'MonitoringInput$BatchTransformInput' => 'Input object for the batch transform job.
', ], ], 'BestObjectiveNotImproving' => [ 'base' => 'A structure that keeps track of which training jobs launched by your hyperparameter tuning job are not improving model performance as evaluated against an objective function.
', 'refs' => [ 'TuningJobCompletionCriteria$BestObjectiveNotImproving' => 'A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.
', ], ], 'Bias' => [ 'base' => 'Contains bias metrics for a model.
', 'refs' => [ 'ModelMetrics$Bias' => 'Metrics that measure bais in a model.
', ], ], 'BillableTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$BillableTimeInSeconds' => 'The billable time in seconds. Billable time refers to the absolute wall-clock time.
Multiply BillableTimeInSeconds
by the number of instances (InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: BillableTimeInSeconds * InstanceCount
.
You can calculate the savings from using managed spot training using the formula (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100
. For example, if BillableTimeInSeconds
is 100 and TrainingTimeInSeconds
is 500, the savings is 80%.
The billable time in seconds.
', ], ], 'BlockedReason' => [ 'base' => NULL, 'refs' => [ 'OfflineStoreStatus$BlockedReason' => 'The justification for why the OfflineStoreStatus is Blocked (if applicable).
', ], ], 'BlueGreenUpdatePolicy' => [ 'base' => 'Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
', 'refs' => [ 'DeploymentConfig$BlueGreenUpdatePolicy' => 'Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
', ], ], 'Boolean' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$EnableSageMakerMetricsTimeSeries' => 'To generate and save time-series metrics during training, set to true
. The default is false
and time-series metrics aren\'t generated except in the following cases:
You use one of the SageMaker built-in algorithms
You use one of the following Prebuilt SageMaker Docker Images:
Tensorflow (version >= 1.15)
MXNet (version >= 1.6)
PyTorch (version >= 1.3)
You specify at least one MetricDefinition
Whether to use traffic encryption between the container layers.
', 'BatchDataCaptureConfig$GenerateInferenceId' => 'Flag that indicates whether to append inference id to the output.
', 'ChannelSpecification$IsRequired' => 'Indicates whether the channel is required by the algorithm.
', 'ClarifyCheckStepMetadata$SkipCheck' => 'This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False
, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints
and BaselineUsedForDriftCheckStatistics
. If it is set to False
, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints
property.
Sets whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
', 'CreateModelInput$EnableNetworkIsolation' => 'Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
', 'CreateTrainingJobRequest$EnableNetworkIsolation' => 'Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
', 'CreateTrainingJobRequest$EnableInterContainerTrafficEncryption' => 'To encrypt all communications between ML compute instances in distributed training, choose True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see Protect Communications Between ML Compute Instances in a Distributed Training Job.
To train models using managed spot training, choose True
. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.
The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
', 'DescribeEndpointConfigOutput$EnableNetworkIsolation' => 'Indicates whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
', 'DescribeModelOutput$EnableNetworkIsolation' => 'If True
, no inbound or outbound network calls can be made to or from the model container.
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True
. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
To encrypt all communications between ML compute instances in distributed training, choose True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.
A Boolean indicating whether managed spot training is enabled (True
) or not (False
).
Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.
', 'HyperParameterSpecification$IsRequired' => 'Indicates whether this hyperparameter is required.
', 'HyperParameterTrainingJobDefinition$EnableNetworkIsolation' => 'Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
', 'HyperParameterTrainingJobDefinition$EnableInterContainerTrafficEncryption' => 'To encrypt all communications between ML compute instances in distributed training, choose True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
A Boolean indicating whether managed spot training is enabled (True
) or not (False
).
Toggle for excluding devices deployed in other stages.
', 'Model$EnableNetworkIsolation' => 'Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
', 'ModelDashboardIndicatorAction$Enabled' => 'Indicates whether the alert action is turned on.
', 'MonitoringCsvDatasetFormat$Header' => 'Indicates if the CSV data has a header.
', 'MonitoringJsonDatasetFormat$Line' => 'Indicates if the file should be read as a JSON object per line.
', 'MonitoringNetworkConfig$EnableInterContainerTrafficEncryption' => 'Whether to encrypt all communications between the instances used for the monitoring jobs. Choose True
to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for the monitoring job.
', 'NetworkConfig$EnableInterContainerTrafficEncryption' => 'Whether to encrypt all communications between distributed processing jobs. Choose True
to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
', 'OfflineStoreConfig$DisableGlueTableCreation' => 'Set to True
to disable the automatic creation of an Amazon Web Services Glue table when configuring an OfflineStore
. If set to False
, Feature Store will name the OfflineStore
Glue table following Athena\'s naming recommendations.
The default value is False
.
Turn OnlineStore
off by specifying False
for the EnableOnlineStore
flag. Turn OnlineStore
on by specifying True
for the EnableOnlineStore
flag.
The default value is False
.
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False
, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints
and BaselineUsedForDriftCheckStatistics
. If it is set to False
, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints
and BaselineUsedForDriftCheckStatistics
properties.
Setting this value to True
retrieves not only the entities of interest but also the Associations and lineage entities on the path. Set to False
to only return lineage entities that match your query.
If the TrainingJob
was created with network isolation, the value is set to true
. If network isolation is enabled, nodes can\'t communicate beyond the VPC they run in.
To encrypt all communications between ML compute instances in distributed training, choose True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
', 'TrainingSpecification$SupportsDistributedTraining' => 'Indicates whether the algorithm supports distributed training. If set to false, buyers can\'t request more than one instance during training.
', 'UpdateEndpointInput$RetainAllVariantProperties' => 'When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties
to true
. To use the variant properties specified in a new EndpointConfig
call when updating an endpoint, set RetainAllVariantProperties
to false
. The default is false
.
Specifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).
', ], ], 'BooleanOperator' => [ 'base' => NULL, 'refs' => [ 'SearchExpression$Operator' => 'A Boolean operator used to evaluate the search expression. If you want every conditional statement in all lists to be satisfied for the entire search expression to be true, specify And
. If only a single conditional statement needs to be true for the entire search expression to be true, specify Or
. The default value is And
.
The default branch for the Git repository.
', ], ], 'BucketName' => [ 'base' => NULL, 'refs' => [ 'PipelineDefinitionS3Location$Bucket' => 'Name of the S3 bucket.
', ], ], 'CacheHitResult' => [ 'base' => 'Details on the cache hit of a pipeline execution step.
', 'refs' => [ 'PipelineExecutionStep$CacheHitResult' => 'If this pipeline execution step was cached, details on the cache hit.
', ], ], 'CallbackStepMetadata' => [ 'base' => 'Metadata about a callback step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Callback' => 'The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.
', ], ], 'CallbackToken' => [ 'base' => NULL, 'refs' => [ 'CallbackStepMetadata$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', 'SendPipelineExecutionStepFailureRequest$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', 'SendPipelineExecutionStepSuccessRequest$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', ], ], 'CandidateArtifactLocations' => [ 'base' => 'The location of artifacts for an AutoML candidate job.
', 'refs' => [ 'CandidateProperties$CandidateArtifactLocations' => 'The Amazon S3 prefix to the artifacts generated for an AutoML candidate.
', ], ], 'CandidateDefinitionNotebookLocation' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobArtifacts$CandidateDefinitionNotebookLocation' => 'The URL of the notebook location.
', ], ], 'CandidateGenerationConfig' => [ 'base' => 'Stores the configuration information for how model candidates are generated using an AutoML job V2.
', 'refs' => [ 'TabularJobConfig$CandidateGenerationConfig' => 'The configuration information of how model candidates are generated.
', ], ], 'CandidateName' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$CandidateName' => 'The name of the candidate.
', 'ListCandidatesForAutoMLJobRequest$CandidateNameEquals' => 'List the candidates for the job and filter by candidate name.
', ], ], 'CandidateProperties' => [ 'base' => 'The properties of an AutoML candidate job.
', 'refs' => [ 'AutoMLCandidate$CandidateProperties' => 'The properties of an AutoML candidate job.
', ], ], 'CandidateSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobRequest$SortBy' => 'The parameter by which to sort the results. The default is Descending
.
The candidate\'s status.
', 'ListCandidatesForAutoMLJobRequest$StatusEquals' => 'List the candidates for the job and filter by status.
', ], ], 'CandidateStepArn' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepArn' => 'The ARN for the candidate\'s step.
', ], ], 'CandidateStepName' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepName' => 'The name for the candidate\'s step.
', ], ], 'CandidateStepType' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepType' => 'Whether the candidate is at the transform, training, or processing step.
', ], ], 'CandidateSteps' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$CandidateSteps' => 'Information about the candidate\'s steps.
', ], ], 'CanvasAppSettings' => [ 'base' => 'The SageMaker Canvas application settings.
', 'refs' => [ 'UserSettings$CanvasAppSettings' => 'The Canvas app settings.
', ], ], 'CapacitySize' => [ 'base' => 'Specifies the type and size of the endpoint capacity to activate for a blue/green deployment, a rolling deployment, or a rollback strategy. You can specify your batches as either instance count or the overall percentage or your fleet.
For a rollback strategy, if you don\'t specify the fields in this object, or if you set the Value
to 100%, then SageMaker uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant\'s total instance count.
', 'RollingUpdatePolicy$RollbackMaximumBatchSize' => 'Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.
', 'TrafficRoutingConfig$CanarySize' => 'Batch size for the first step to turn on traffic on the new endpoint fleet. Value
must be less than or equal to 50% of the variant\'s total instance count.
Batch size for each step to turn on traffic on the new endpoint fleet. Value
must be 10-50% of the variant\'s total instance count.
Specifies the endpoint capacity type.
INSTANCE_COUNT
: The endpoint activates based on the number of instances.
CAPACITY_PERCENT
: The endpoint activates based on the specified percentage of capacity.
Defines the capacity size, either as a number of instances or a capacity percentage.
', ], ], 'CapacityUnit' => [ 'base' => NULL, 'refs' => [ 'ThroughputConfig$ProvisionedReadCapacityUnits' => 'For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
', 'ThroughputConfig$ProvisionedWriteCapacityUnits' => 'For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
', 'ThroughputConfigDescription$ProvisionedReadCapacityUnits' => 'For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
', 'ThroughputConfigDescription$ProvisionedWriteCapacityUnits' => 'For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
', 'ThroughputConfigUpdate$ProvisionedReadCapacityUnits' => 'For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
', 'ThroughputConfigUpdate$ProvisionedWriteCapacityUnits' => 'For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
', ], ], 'CaptureContentTypeHeader' => [ 'base' => 'Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker will by default base64 encode when capturing the data.
', 'refs' => [ 'DataCaptureConfig$CaptureContentTypeHeader' => 'Configuration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.
', 'InferenceExperimentDataStorageConfig$ContentType' => NULL, ], ], 'CaptureMode' => [ 'base' => NULL, 'refs' => [ 'CaptureOption$CaptureMode' => 'Specify the boundary of data to capture.
', ], ], 'CaptureOption' => [ 'base' => 'Specifies data Model Monitor will capture.
', 'refs' => [ 'CaptureOptionList$member' => NULL, ], ], 'CaptureOptionList' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$CaptureOptions' => 'Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
', ], ], 'CaptureStatus' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfigSummary$CaptureStatus' => 'Whether data capture is currently functional.
', ], ], 'Catalog' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$Catalog' => 'The name of the Glue table catalog.
', ], ], 'CategoricalParameter' => [ 'base' => 'Environment parameters you want to benchmark your load test against.
', 'refs' => [ 'CategoricalParameters$member' => NULL, ], ], 'CategoricalParameterRange' => [ 'base' => 'A list of categorical hyperparameters to tune.
', 'refs' => [ 'CategoricalParameterRanges$member' => NULL, ], ], 'CategoricalParameterRangeSpecification' => [ 'base' => 'Defines the possible values for a categorical hyperparameter.
', 'refs' => [ 'ParameterRange$CategoricalParameterRangeSpecification' => 'A CategoricalParameterRangeSpecification
object that defines the possible values for a categorical hyperparameter.
The list of values you can pass.
', ], ], 'CategoricalParameterRanges' => [ 'base' => NULL, 'refs' => [ 'ParameterRanges$CategoricalParameterRanges' => 'The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.
', ], ], 'CategoricalParameters' => [ 'base' => NULL, 'refs' => [ 'EnvironmentParameterRanges$CategoricalParameterRanges' => 'Specified a list of parameters for each category.
', ], ], 'Cents' => [ 'base' => NULL, 'refs' => [ 'USD$Cents' => 'The fractional portion, in cents, of the amount.
', ], ], 'CertifyForMarketplace' => [ 'base' => NULL, 'refs' => [ 'CreateAlgorithmInput$CertifyForMarketplace' => 'Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.
', 'CreateModelPackageInput$CertifyForMarketplace' => 'Whether to certify the model package for listing on Amazon Web Services Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
', 'DescribeAlgorithmOutput$CertifyForMarketplace' => 'Whether the algorithm is certified to be listed in Amazon Web Services Marketplace.
', 'DescribeModelPackageOutput$CertifyForMarketplace' => 'Whether the model package is certified for listing on Amazon Web Services Marketplace.
', 'ModelPackage$CertifyForMarketplace' => 'Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.
', ], ], 'Channel' => [ 'base' => 'A channel is a named input source that training algorithms can consume.
', 'refs' => [ 'InputDataConfig$member' => NULL, ], ], 'ChannelName' => [ 'base' => NULL, 'refs' => [ 'Channel$ChannelName' => 'The name of the channel.
', 'ChannelSpecification$Name' => 'The name of the channel.
', ], ], 'ChannelSpecification' => [ 'base' => 'Defines a named input source, called a channel, to be used by an algorithm.
', 'refs' => [ 'ChannelSpecifications$member' => NULL, ], ], 'ChannelSpecifications' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$TrainingChannels' => 'A list of ChannelSpecification
objects, which specify the input sources to be used by the algorithm.
Contains information about the output location for managed spot training checkpoint data.
', 'refs' => [ 'CreateTrainingJobRequest$CheckpointConfig' => 'Contains information about the output location for managed spot training checkpoint data.
', 'DescribeTrainingJobResponse$CheckpointConfig' => NULL, 'HyperParameterTrainingJobDefinition$CheckpointConfig' => NULL, 'TrainingJob$CheckpointConfig' => NULL, ], ], 'Cidr' => [ 'base' => NULL, 'refs' => [ 'Cidrs$member' => NULL, ], ], 'Cidrs' => [ 'base' => NULL, 'refs' => [ 'SourceIpConfig$Cidrs' => 'A list of one to ten Classless Inter-Domain Routing (CIDR) values.
Maximum: Ten CIDR values
The following Length Constraints apply to individual CIDR values in the CIDR value list.
The container for the metadata for the ClarifyCheck step. For more information, see the topic on ClarifyCheck step in the Amazon SageMaker Developer Guide.
', 'refs' => [ 'PipelineExecutionStepMetadata$ClarifyCheck' => 'Container for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes:
The type of the check conducted,
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck
is set the same as CalculatedBaseline
.
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate
string \'{"myfeatures":$features}\'
will format a list of features [1,2,3]
into the record string \'{"myfeatures":[1,2,3]}\'
. Required only when the model container input is in JSON Lines format.
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See EnableExplanations
for additional information.
The configuration parameters for the SageMaker Clarify explainer.
', 'refs' => [ 'ExplainerConfig$ClarifyExplainerConfig' => 'A member of ExplainerConfig
that contains configuration parameters for the SageMaker Clarify explainer.
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint
output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes
must have at least one \'text\'
string (for example, [\'text\']
). If FeatureTypes
is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute
is the JMESPath expression \'myfeatures\'
, it extracts a list of features [1,2,3]
from request data \'{"myfeatures":[1,2,3]}\'
.
The inference configuration parameter for the model container.
', 'refs' => [ 'ClarifyExplainerConfig$InferenceConfig' => 'The inference configuration parameter for the model container.
', ], ], 'ClarifyLabelAttribute' => [ 'base' => NULL, 'refs' => [ 'ClarifyInferenceConfig$LabelAttribute' => 'A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is \'{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}\'
, then set LabelAttribute
to \'labels\'
to extract the list of label headers ["cat","dog","fish"]
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint
API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: \'"[\\\'cat\\\',\\\'dog\\\',\\\'fish\\\']","[0.1,0.6,0.3]"\'
, set LabelIndex
to 0
to select the label headers [\'cat\',\'dog\',\'fish\']
.
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6
MB.
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount
is 1
, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container\'s capacity at runtime.
The MIME type of the baseline data. Choose from \'text/csv\'
or \'application/jsonlines\'
. Defaults to \'text/csv\'
.
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is \'{"predicted_label":1,"probability":0.6}\'
, then set ProbabilityAttribute
to \'probability\'
.
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: \'1,0.6\'
, set ProbabilityIndex
to 1
to select the probability value 0.6
.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: \'"[\\\'cat\\\',\\\'dog\\\',\\\'fish\\\']","[0.1,0.6,0.3]"\'
, set ProbabilityIndex
to 1
to select the probability values [0.1,0.6,0.3]
.
The inline SHAP baseline data in string format. ShapBaseline
can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity
of the TextConfig
parameter. The size limit for ShapBasline
is 4 KB. Use the ShapBaselineUri
parameter if you want to provide more than 4 KB of baseline data.
The configuration for the SHAP baseline (also called the background or reference dataset) of the Kernal SHAP algorithm.
The number of records in the baseline data determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
ShapBaseline
and ShapBaselineUri
are mutually exclusive parameters. One or the either is required to configure a SHAP baseline.
The configuration for the SHAP baseline of the Kernal SHAP algorithm.
', ], ], 'ClarifyShapConfig' => [ 'base' => 'The configuration for SHAP analysis using SageMaker Clarify Explainer.
', 'refs' => [ 'ClarifyExplainerConfig$ShapConfig' => 'The configuration for SHAP analysis.
', ], ], 'ClarifyShapNumberOfSamples' => [ 'base' => NULL, 'refs' => [ 'ClarifyShapConfig$NumberOfSamples' => 'The number of samples to be used for analysis by the Kernal SHAP algorithm.
The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
', ], ], 'ClarifyShapUseLogit' => [ 'base' => NULL, 'refs' => [ 'ClarifyShapConfig$UseLogit' => 'A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
', ], ], 'ClarifyTextConfig' => [ 'base' => 'A parameter used to configure the SageMaker Clarify explainer to treat text features as text so that explanations are provided for individual units of text. Required only for natural language processing (NLP) explainability.
', 'refs' => [ 'ClarifyShapConfig$TextConfig' => 'A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
', ], ], 'ClarifyTextGranularity' => [ 'base' => NULL, 'refs' => [ 'ClarifyTextConfig$Granularity' => 'The unit of granularity for the analysis of text features. For example, if the unit is \'token\'
, then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
For a mix of multiple languages, use code \'xx\'
.
The client ID for your Amazon Cognito user pool.
', 'CognitoMemberDefinition$ClientId' => 'An identifier for an application client. You must create the app client ID using Amazon Cognito.
', 'OidcConfig$ClientId' => 'The OIDC IdP client ID used to configure your private workforce.
', 'OidcConfigForResponse$ClientId' => 'The OIDC IdP client ID used to configure your private workforce.
', ], ], 'ClientSecret' => [ 'base' => NULL, 'refs' => [ 'OidcConfig$ClientSecret' => 'The OIDC IdP client secret used to configure your private workforce.
', ], ], 'ClientToken' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ClientToken' => 'A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.
', 'CreateModelPackageInput$ClientToken' => 'A unique token that guarantees that the call to this API is idempotent.
', ], ], 'ClusterArn' => [ 'base' => NULL, 'refs' => [ 'ClusterSummary$ClusterArn' => 'The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
', 'CreateClusterResponse$ClusterArn' => 'The Amazon Resource Name (ARN) of the cluster.
', 'DeleteClusterResponse$ClusterArn' => 'The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster to delete.
', 'DescribeClusterResponse$ClusterArn' => 'The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
', 'UpdateClusterResponse$ClusterArn' => 'The Amazon Resource Name (ARN) of the updated SageMaker HyperPod cluster.
', ], ], 'ClusterInstanceCount' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$TargetCount' => 'The number of instances you specified to add to the instance group of a SageMaker HyperPod cluster.
', 'ClusterInstanceGroupSpecification$InstanceCount' => 'Specifies the number of instances to add to the instance group of a SageMaker HyperPod cluster.
', ], ], 'ClusterInstanceGroupDetails' => [ 'base' => 'Details of an instance group in a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterInstanceGroupDetailsList$member' => NULL, ], ], 'ClusterInstanceGroupDetailsList' => [ 'base' => NULL, 'refs' => [ 'DescribeClusterResponse$InstanceGroups' => 'The instance groups of the SageMaker HyperPod cluster.
', ], ], 'ClusterInstanceGroupName' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$InstanceGroupName' => 'The name of the instance group of a SageMaker HyperPod cluster.
', 'ClusterInstanceGroupSpecification$InstanceGroupName' => 'Specifies the name of the instance group.
', 'ClusterNodeDetails$InstanceGroupName' => 'The instance group name in which the instance is.
', 'ClusterNodeSummary$InstanceGroupName' => 'The name of the instance group in which the instance is.
', 'ListClusterNodesRequest$InstanceGroupNameContains' => 'A filter that returns the instance groups whose name contain a specified string.
', ], ], 'ClusterInstanceGroupSpecification' => [ 'base' => 'The specifications of an instance group that you need to define.
', 'refs' => [ 'ClusterInstanceGroupSpecifications$member' => NULL, ], ], 'ClusterInstanceGroupSpecifications' => [ 'base' => NULL, 'refs' => [ 'CreateClusterRequest$InstanceGroups' => 'The instance groups to be created in the SageMaker HyperPod cluster.
', 'UpdateClusterRequest$InstanceGroups' => 'Specify the instance groups to update.
', ], ], 'ClusterInstanceStatus' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceStatusDetails$Status' => 'The status of an instance in a SageMaker HyperPod cluster.
', ], ], 'ClusterInstanceStatusDetails' => [ 'base' => 'Details of an instance in a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterNodeDetails$InstanceStatus' => 'The status of the instance.
', 'ClusterNodeSummary$InstanceStatus' => 'The status of the instance.
', ], ], 'ClusterInstanceType' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$InstanceType' => 'The instance type of the instance group of a SageMaker HyperPod cluster.
', 'ClusterInstanceGroupSpecification$InstanceType' => 'Specifies the instance type of the instance group.
', 'ClusterNodeDetails$InstanceType' => 'The type of the instance.
', 'ClusterNodeSummary$InstanceType' => 'The type of the instance.
', ], ], 'ClusterLifeCycleConfig' => [ 'base' => 'The LifeCycle configuration for a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterInstanceGroupDetails$LifeCycleConfig' => 'Details of LifeCycle configuration for the instance group.
', 'ClusterInstanceGroupSpecification$LifeCycleConfig' => 'Specifies the LifeCycle configuration for the instance group.
', 'ClusterNodeDetails$LifeCycleConfig' => 'The LifeCycle configuration applied to the instance.
', ], ], 'ClusterLifeCycleConfigFileName' => [ 'base' => NULL, 'refs' => [ 'ClusterLifeCycleConfig$OnCreate' => 'The directory of the LifeCycle script under SourceS3Uri
. This LifeCycle script runs during cluster creation.
The name of the SageMaker HyperPod cluster.
', 'CreateClusterRequest$ClusterName' => 'The name for the new SageMaker HyperPod cluster.
', 'DescribeClusterResponse$ClusterName' => 'The name of the SageMaker HyperPod cluster.
', ], ], 'ClusterNameOrArn' => [ 'base' => NULL, 'refs' => [ 'DeleteClusterRequest$ClusterName' => 'The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster to delete.
', 'DescribeClusterNodeRequest$ClusterName' => 'The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which the instance is.
', 'DescribeClusterRequest$ClusterName' => 'The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
', 'ListClusterNodesRequest$ClusterName' => 'The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which you want to retrieve the list of nodes.
', 'UpdateClusterRequest$ClusterName' => 'Specify the name of the SageMaker HyperPod cluster you want to update.
', ], ], 'ClusterNodeDetails' => [ 'base' => 'Details of an instance (also called a node interchangeably) in a SageMaker HyperPod cluster.
', 'refs' => [ 'DescribeClusterNodeResponse$NodeDetails' => 'The details of the instance.
', ], ], 'ClusterNodeId' => [ 'base' => NULL, 'refs' => [ 'DescribeClusterNodeRequest$NodeId' => 'The ID of the instance.
', ], ], 'ClusterNodeSummaries' => [ 'base' => NULL, 'refs' => [ 'ListClusterNodesResponse$ClusterNodeSummaries' => 'The summaries of listed instances in a SageMaker HyperPod cluster
', ], ], 'ClusterNodeSummary' => [ 'base' => 'Lists a summary of the properties of an instance (also called a node interchangeably) of a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterNodeSummaries$member' => NULL, ], ], 'ClusterNonNegativeInstanceCount' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$CurrentCount' => 'The number of instances that are currently in the instance group of a SageMaker HyperPod cluster.
', ], ], 'ClusterSortBy' => [ 'base' => NULL, 'refs' => [ 'ListClusterNodesRequest$SortBy' => 'The field by which to sort results. The default value is CREATION_TIME
.
The field by which to sort results. The default value is CREATION_TIME
.
The status of the SageMaker HyperPod cluster.
', 'DescribeClusterResponse$ClusterStatus' => 'The status of the SageMaker HyperPod cluster.
', ], ], 'ClusterSummaries' => [ 'base' => NULL, 'refs' => [ 'ListClustersResponse$ClusterSummaries' => 'The summaries of listed SageMaker HyperPod clusters.
', ], ], 'ClusterSummary' => [ 'base' => 'Lists a summary of the properties of a SageMaker HyperPod cluster.
', 'refs' => [ 'ClusterSummaries$member' => NULL, ], ], 'ClusterThreadsPerCore' => [ 'base' => NULL, 'refs' => [ 'ClusterInstanceGroupDetails$ThreadsPerCore' => 'The number you specified to TreadsPerCore
in CreateCluster
for enabling or disabling multithreading. For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
Specifies the value for Threads per core. For instance types that support multithreading, you can specify 1
for disabling multithreading and 2
for enabling multithreading. For instance types that doesn\'t support multithreading, specify 1
. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
The number of threads per CPU core you specified under CreateCluster
.
The Code Editor application settings.
For more information about Code Editor, see Get started with Code Editor in Amazon SageMaker.
', 'refs' => [ 'UserSettings$CodeEditorAppSettings' => 'The Code Editor application settings.
', ], ], 'CodeRepositories' => [ 'base' => NULL, 'refs' => [ 'JupyterLabAppSettings$CodeRepositories' => 'A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterLab application.
', 'JupyterServerAppSettings$CodeRepositories' => 'A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.
', 'SpaceJupyterLabAppSettings$CodeRepositories' => 'A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterLab application.
', ], ], 'CodeRepository' => [ 'base' => 'A Git repository that SageMaker automatically displays to users for cloning in the JupyterServer application.
', 'refs' => [ 'CodeRepositories$member' => NULL, ], ], 'CodeRepositoryArn' => [ 'base' => NULL, 'refs' => [ 'CodeRepositorySummary$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the Git repository.
', 'CreateCodeRepositoryOutput$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the new repository.
', 'DescribeCodeRepositoryOutput$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the Git repository.
', 'UpdateCodeRepositoryOutput$CodeRepositoryArn' => 'The ARN of the Git repository.
', ], ], 'CodeRepositoryContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$DefaultCodeRepositoryContains' => 'A string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.
', ], ], 'CodeRepositoryNameContains' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesInput$NameContains' => 'A string in the Git repositories name. This filter returns only repositories whose name contains the specified string.
', ], ], 'CodeRepositoryNameOrUrl' => [ 'base' => NULL, 'refs' => [ 'AdditionalCodeRepositoryNamesOrUrls$member' => NULL, 'CreateNotebookInstanceInput$DefaultCodeRepository' => 'A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'DescribeNotebookInstanceOutput$DefaultCodeRepository' => 'The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'ListNotebookInstancesInput$AdditionalCodeRepositoryEquals' => 'A filter that returns only notebook instances with associated with the specified git repository.
', 'NotebookInstanceSummary$DefaultCodeRepository' => 'The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'UpdateNotebookInstanceInput$DefaultCodeRepository' => 'The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', ], ], 'CodeRepositorySortBy' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesInput$SortBy' => 'The field to sort results by. The default is Name
.
The sort order for results. The default is Ascending
.
Specifies summary information about a Git repository.
', 'refs' => [ 'CodeRepositorySummaryList$member' => NULL, ], ], 'CodeRepositorySummaryList' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesOutput$CodeRepositorySummaryList' => 'Gets a list of summaries of the Git repositories. Each summary specifies the following values for the repository:
Name
Amazon Resource Name (ARN)
Creation time
Last modified time
Configuration information, including the URL location of the repository and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
', 'refs' => [ 'CreateWorkforceRequest$CognitoConfig' => 'Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use OidcConfig
if you specify values for CognitoConfig
.
The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
', ], ], 'CognitoMemberDefinition' => [ 'base' => 'Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
', 'refs' => [ 'MemberDefinition$CognitoMemberDefinition' => 'The Amazon Cognito user group that is part of the work team.
', ], ], 'CognitoUserGroup' => [ 'base' => NULL, 'refs' => [ 'CognitoMemberDefinition$UserGroup' => 'An identifier for a user group.
', ], ], 'CognitoUserPool' => [ 'base' => NULL, 'refs' => [ 'CognitoConfig$UserPool' => 'A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.
', 'CognitoMemberDefinition$UserPool' => 'An identifier for a user pool. The user pool must be in the same region as the service that you are calling.
', ], ], 'CollectionConfig' => [ 'base' => 'Configuration for your collection.
', 'refs' => [ 'FeatureDefinition$CollectionConfig' => 'Configuration for your collection.
', ], ], 'CollectionConfiguration' => [ 'base' => 'Configuration information for the Amazon SageMaker Debugger output tensor collections.
', 'refs' => [ 'CollectionConfigurations$member' => NULL, ], ], 'CollectionConfigurations' => [ 'base' => NULL, 'refs' => [ 'DebugHookConfig$CollectionConfigurations' => 'Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
The name of the tensor collection. The name must be unique relative to other rule configuration names.
', ], ], 'CollectionParameters' => [ 'base' => NULL, 'refs' => [ 'CollectionConfiguration$CollectionParameters' => 'Parameter values for the tensor collection. The allowed parameters are "name"
, "include_regex"
, "reduction_config"
, "save_config"
, "tensor_names"
, and "save_histogram"
.
A grouping of elements where each element within the collection must have the same feature type (String
, Integral
, or Fractional
).
List
: An ordered collection of elements.
Set
: An unordered collection of unique elements.
Vector
: A specialized list that represents a fixed-size array of elements. The vector dimension is determined by you. Must have elements with fractional feature types.
The Amazon Resource Name (ARN) of the model compilation job.
', 'CreateCompilationJobResponse$CompilationJobArn' => 'If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker returns the following data in JSON format:
CompilationJobArn
: The Amazon Resource Name (ARN) of the compiled job.
The Amazon Resource Name (ARN) of the model compilation job.
', ], ], 'CompilationJobStatus' => [ 'base' => NULL, 'refs' => [ 'CompilationJobSummary$CompilationJobStatus' => 'The status of the model compilation job.
', 'DescribeCompilationJobResponse$CompilationJobStatus' => 'The status of the model compilation job.
', 'ListCompilationJobsRequest$StatusEquals' => 'A filter that retrieves model compilation jobs with a specific CompilationJobStatus
status.
An array of CompilationJobSummary objects, each describing a model compilation job.
', ], ], 'CompilationJobSummary' => [ 'base' => 'A summary of a model compilation job.
', 'refs' => [ 'CompilationJobSummaries$member' => NULL, ], ], 'CompilerOptions' => [ 'base' => NULL, 'refs' => [ 'OutputConfig$CompilerOptions' => 'Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform
specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.
DTYPE
: Specifies the data type for the input. When compiling for ml_*
(except for ml_inf
) instances using PyTorch framework, provide the data type (dtype) of the model\'s input. "float32"
is used if "DTYPE"
is not specified. Options for data type are:
float32: Use either "float"
or "float32"
.
int64: Use either "int64"
or "long"
.
For example, {"dtype" : "float32"}
.
CPU
: Compilation for CPU supports the following compiler options.
mcpu
: CPU micro-architecture. For example, {\'mcpu\': \'skylake-avx512\'}
mattr
: CPU flags. For example, {\'mattr\': [\'+neon\', \'+vfpv4\']}
ARM
: Details of ARM CPU compilations.
NEON
: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.
For example, add {\'mattr\': [\'+neon\']}
to the compiler options if compiling for ARM 32-bit platform with the NEON support.
NVIDIA
: Compilation for NVIDIA GPU supports the following compiler options.
gpu_code
: Specifies the targeted architecture.
trt-ver
: Specifies the TensorRT versions in x.y.z. format.
cuda-ver
: Specifies the CUDA version in x.y format.
For example, {\'gpu-code\': \'sm_72\', \'trt-ver\': \'6.0.1\', \'cuda-ver\': \'10.1\'}
ANDROID
: Compilation for the Android OS supports the following compiler options:
ANDROID_PLATFORM
: Specifies the Android API levels. Available levels range from 21 to 29. For example, {\'ANDROID_PLATFORM\': 28}
.
mattr
: Add {\'mattr\': [\'+neon\']}
to compiler options if compiling for ARM 32-bit platform with NEON support.
INFERENTIA
: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, "CompilerOptions": "\\"--verbose 1 --num-neuroncores 2 -O2\\""
.
For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
CoreML
: Compilation for the CoreML OutputConfig TargetDevice
supports the following compiler options:
class_labels
: Specifies the classification labels file name inside input tar.gz file. For example, {"class_labels": "imagenet_labels_1000.txt"}
. Labels inside the txt file should be separated by newlines.
EIA
: Compilation for the Elastic Inference Accelerator supports the following compiler options:
precision_mode
: Specifies the precision of compiled artifacts. Supported values are "FP16"
and "FP32"
. Default is "FP32"
.
signature_def_key
: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow\'s default signature def key.
output_names
: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: signature_def_key
or output_names
.
For example: {"precision_mode": "FP32", "output_names": ["output:0"]}
A flag to stop a tuning job once AMT has detected that the job has converged.
', ], ], 'CompressionType' => [ 'base' => NULL, 'refs' => [ 'AdditionalS3DataSource$CompressionType' => 'The type of compression used for an additional data source used in inference or training. Specify None
if your additional data source is not compressed.
You can use Gzip
or None
. The default value is None
.
The allowed compression types depend on the input format and problem type. We allow the compression type Gzip
for S3Prefix
inputs on tabular data only. For all other inputs, the compression type should be None
. If no compression type is provided, we default to None
.
If training data is compressed, the compression type. The default value is None
. CompressionType
is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None
.
The allowed compression types, if data compression is used.
', ], ], 'ConditionOutcome' => [ 'base' => NULL, 'refs' => [ 'ConditionStepMetadata$Outcome' => 'The outcome of the Condition step evaluation.
', ], ], 'ConditionStepMetadata' => [ 'base' => 'Metadata for a Condition step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Condition' => 'The outcome of the condition evaluation that was run by this step execution.
', ], ], 'ConfigKey' => [ 'base' => NULL, 'refs' => [ 'CollectionParameters$key' => NULL, 'HookParameters$key' => NULL, 'ProfilingParameters$key' => NULL, 'RuleParameters$key' => NULL, ], ], 'ConfigValue' => [ 'base' => NULL, 'refs' => [ 'CollectionParameters$value' => NULL, 'HookParameters$value' => NULL, 'ProfilingParameters$value' => NULL, 'RuleParameters$value' => NULL, ], ], 'ConflictException' => [ 'base' => 'There was a conflict when you attempted to modify a SageMaker entity such as an Experiment
or Artifact
.
The arguments for a container used to run a processing job.
', ], ], 'ContainerConfig' => [ 'base' => 'The configuration used to run the application image container.
', 'refs' => [ 'JupyterLabAppImageConfig$ContainerConfig' => NULL, ], ], 'ContainerDefinition' => [ 'base' => 'Describes the container, as part of model definition.
', 'refs' => [ 'ContainerDefinitionList$member' => NULL, 'CreateModelInput$PrimaryContainer' => 'The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
', 'DescribeModelOutput$PrimaryContainer' => 'The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
', 'Model$PrimaryContainer' => NULL, ], ], 'ContainerDefinitionList' => [ 'base' => NULL, 'refs' => [ 'CreateModelInput$Containers' => 'Specifies the containers in the inference pipeline.
', 'DescribeModelOutput$Containers' => 'The containers in the inference pipeline.
', 'Model$Containers' => 'The containers in the inference pipeline.
', ], ], 'ContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'AppSpecification$ContainerEntrypoint' => 'The entrypoint for a container used to run a processing job.
', 'DataQualityAppSpecification$ContainerEntrypoint' => 'The entrypoint for a container used to run a monitoring job.
', 'ModelQualityAppSpecification$ContainerEntrypoint' => 'Specifies the entrypoint for a container that the monitoring job runs.
', 'MonitoringAppSpecification$ContainerEntrypoint' => 'Specifies the entrypoint for a container used to run the monitoring job.
', ], ], 'ContainerEntrypointString' => [ 'base' => NULL, 'refs' => [ 'ContainerEntrypoint$member' => NULL, ], ], 'ContainerHostname' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$ContainerHostname' => 'This parameter is ignored for models that contain only a PrimaryContainer
.
When a ContainerDefinition
is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don\'t specify a value for this parameter for a ContainerDefinition
that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition
in the pipeline. If you specify a value for the ContainerHostName
for any ContainerDefinition
that is part of an inference pipeline, you must specify a value for the ContainerHostName
parameter of every ContainerDefinition
in that pipeline.
The DNS host name for the Docker container.
', ], ], 'ContainerImage' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$Image' => 'The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see ContainerDefinition.
', 'ContainerDefinition$Image' => 'The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The image path you specified when you created the model.
', 'DeployedImage$ResolvedImage' => 'The specific digest path of the image hosted in this ProductionVariant
.
The Amazon Elastic Container Registry (Amazon ECR) path where the Docker image for the model is stored.
', 'ModelPackageContainerDefinition$Image' => 'The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The Amazon ECR registry path of the Docker image that contains the training algorithm.
', ], ], 'ContainerMode' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$Mode' => 'Whether the container hosts a single model or multiple models.
', ], ], 'ContentClassifier' => [ 'base' => NULL, 'refs' => [ 'ContentClassifiers$member' => NULL, ], ], 'ContentClassifiers' => [ 'base' => NULL, 'refs' => [ 'LabelingJobDataAttributes$ContentClassifiers' => 'Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.
', ], ], 'ContentColumn' => [ 'base' => NULL, 'refs' => [ 'TextClassificationJobConfig$ContentColumn' => 'The name of the column used to provide the sentences to be classified. It should not be the same as the target column.
', ], ], 'ContentDigest' => [ 'base' => NULL, 'refs' => [ 'FileSource$ContentDigest' => 'The digest of the file source.
', 'MetricsSource$ContentDigest' => 'The hash key used for the metrics source.
', ], ], 'ContentType' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$ContentType' => 'The content type of the data from the input source. You can use text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
The content type of the data from the input source. The following are the allowed content types for different problems:
For tabular problem types: text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
For image classification: image/png
, image/jpeg
, or image/*
. The default value is image/*
.
For text classification: text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
For time-series forecasting: text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
For text generation (LLMs fine-tuning): text/csv;header=present
or x-application/vnd.amazon+parquet
. The default value is text/csv;header=present
.
The MIME type of the data.
', 'ContentTypes$member' => NULL, 'FileSource$ContentType' => 'The type of content stored in the file source.
', 'MetricsSource$ContentType' => 'The metric source content type.
', 'TransformInput$ContentType' => 'The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
', ], ], 'ContentTypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedContentTypes' => 'The supported MIME types for the input data.
', 'ChannelSpecification$SupportedContentTypes' => 'The supported MIME types for the data.
', 'InferenceSpecification$SupportedContentTypes' => 'The supported MIME types for the input data.
', ], ], 'ContextArn' => [ 'base' => NULL, 'refs' => [ 'ContextSummary$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'CreateContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'DeleteContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'DescribeContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'UpdateContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', ], ], 'ContextName' => [ 'base' => NULL, 'refs' => [ 'ContextSummary$ContextName' => 'The name of the context.
', 'CreateContextRequest$ContextName' => 'The name of the context. Must be unique to your account in an Amazon Web Services Region.
', 'DeleteContextRequest$ContextName' => 'The name of the context to delete.
', 'DescribeContextResponse$ContextName' => 'The name of the context.
', 'UpdateContextRequest$ContextName' => 'The name of the context to update.
', ], ], 'ContextNameOrArn' => [ 'base' => NULL, 'refs' => [ 'DescribeContextRequest$ContextName' => 'The name of the context to describe.
', ], ], 'ContextSource' => [ 'base' => 'A structure describing the source of a context.
', 'refs' => [ 'ContextSummary$Source' => 'The source of the context.
', 'CreateContextRequest$Source' => 'The source type, ID, and URI.
', 'DescribeContextResponse$Source' => 'The source of the context.
', ], ], 'ContextSummaries' => [ 'base' => NULL, 'refs' => [ 'ListContextsResponse$ContextSummaries' => 'A list of contexts and their properties.
', ], ], 'ContextSummary' => [ 'base' => 'Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
', 'refs' => [ 'ContextSummaries$member' => NULL, ], ], 'ContinuousParameterRange' => [ 'base' => 'A list of continuous hyperparameters to tune.
', 'refs' => [ 'ContinuousParameterRanges$member' => NULL, ], ], 'ContinuousParameterRangeSpecification' => [ 'base' => 'Defines the possible values for a continuous hyperparameter.
', 'refs' => [ 'ParameterRange$ContinuousParameterRangeSpecification' => 'A ContinuousParameterRangeSpecification
object that defines the possible values for a continuous hyperparameter.
The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.
', ], ], 'ConvergenceDetected' => [ 'base' => 'A flag to indicating that automatic model tuning (AMT) has detected model convergence, defined as a lack of significant improvement (1% or less) against an objective metric.
', 'refs' => [ 'TuningJobCompletionCriteria$ConvergenceDetected' => 'A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.
', ], ], 'CountryCode' => [ 'base' => NULL, 'refs' => [ 'HolidayConfigAttributes$CountryCode' => 'The country code for the holiday calendar.
For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your choice.
', ], ], 'CreateActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAlgorithmInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateAlgorithmOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobV2Request' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobV2Response' => [ 'base' => NULL, 'refs' => [], ], 'CreateClusterRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateClusterResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateCompilationJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateDataQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDataQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentPlanRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentPlanResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFlowDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFlowDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHumanTaskUiRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHumanTaskUiResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceComponentInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceComponentOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceRecommendationsJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateLabelingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelBiasJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelBiasJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardExportJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardExportJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelExplainabilityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelExplainabilityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageGroupInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageGroupOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreatePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreatePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedDomainUrlRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedDomainUrlResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedNotebookInstanceUrlInput' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedNotebookInstanceUrlOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateProcessingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateStudioLifecycleConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateStudioLifecycleConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTransformJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreationTime' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$CreationTime' => 'A timestamp that shows when the algorithm was created.
', 'AppDetails$CreationTime' => 'The creation time.
', 'BatchDescribeModelPackageSummary$CreationTime' => 'The creation time of the mortgage package summary.
', 'CodeRepositorySummary$CreationTime' => 'The date and time that the Git repository was created.
', 'CompilationJobSummary$CreationTime' => 'The time when the model compilation job was created.
', 'DescribeAlgorithmOutput$CreationTime' => 'A timestamp specifying when the algorithm was created.
', 'DescribeCodeRepositoryOutput$CreationTime' => 'The date and time that the repository was created.
', 'DescribeCompilationJobResponse$CreationTime' => 'The time that the model compilation job was created.
', 'DescribeDomainResponse$CreationTime' => 'The creation time.
', 'DescribeFeatureGroupResponse$CreationTime' => 'A timestamp indicating when SageMaker created the FeatureGroup
.
A timestamp indicating when the feature was created.
', 'DescribeInferenceRecommendationsJobResponse$CreationTime' => 'A timestamp that shows when the job was created.
', 'DescribeModelPackageGroupOutput$CreationTime' => 'The time that the model group was created.
', 'DescribeModelPackageOutput$CreationTime' => 'A timestamp specifying when the model package was created.
', 'DescribeNotebookInstanceLifecycleConfigOutput$CreationTime' => 'A timestamp that tells when the lifecycle configuration was created.
', 'DescribeNotebookInstanceOutput$CreationTime' => 'A timestamp. Use this parameter to return the time when the notebook instance was created
', 'DescribeSpaceResponse$CreationTime' => 'The creation time.
', 'DescribeUserProfileResponse$CreationTime' => 'The creation time.
', 'DomainDetails$CreationTime' => 'The creation time.
', 'FeatureGroup$CreationTime' => 'The time a FeatureGroup
was created.
A timestamp indicating when the feature was created.
', 'InferenceRecommendationsJob$CreationTime' => 'A timestamp that shows when the job was created.
', 'ListAlgorithmsInput$CreationTimeAfter' => 'A filter that returns only algorithms created after the specified time (timestamp).
', 'ListAlgorithmsInput$CreationTimeBefore' => 'A filter that returns only algorithms created before the specified time (timestamp).
', 'ListCodeRepositoriesInput$CreationTimeAfter' => 'A filter that returns only Git repositories that were created after the specified time.
', 'ListCodeRepositoriesInput$CreationTimeBefore' => 'A filter that returns only Git repositories that were created before the specified time.
', 'ListCompilationJobsRequest$CreationTimeAfter' => 'A filter that returns the model compilation jobs that were created after a specified time.
', 'ListCompilationJobsRequest$CreationTimeBefore' => 'A filter that returns the model compilation jobs that were created before a specified time.
', 'ListFeatureGroupsRequest$CreationTimeAfter' => 'Use this parameter to search for FeatureGroups
s created after a specific date and time.
Use this parameter to search for FeatureGroups
s created before a specific date and time.
A filter that returns only jobs created after the specified time (timestamp).
', 'ListInferenceRecommendationsJobsRequest$CreationTimeBefore' => 'A filter that returns only jobs created before the specified time (timestamp).
', 'ListModelPackageGroupsInput$CreationTimeAfter' => 'A filter that returns only model groups created after the specified time.
', 'ListModelPackageGroupsInput$CreationTimeBefore' => 'A filter that returns only model groups created before the specified time.
', 'ListModelPackagesInput$CreationTimeAfter' => 'A filter that returns only model packages created after the specified time (timestamp).
', 'ListModelPackagesInput$CreationTimeBefore' => 'A filter that returns only model packages created before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$CreationTimeBefore' => 'A filter that returns only lifecycle configurations that were created before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$CreationTimeAfter' => 'A filter that returns only lifecycle configurations that were created after the specified time (timestamp).
', 'ListNotebookInstancesInput$CreationTimeBefore' => 'A filter that returns only notebook instances that were created before the specified time (timestamp).
', 'ListNotebookInstancesInput$CreationTimeAfter' => 'A filter that returns only notebook instances that were created after the specified time (timestamp).
', 'ModelPackage$CreationTime' => 'The time that the model package was created.
', 'ModelPackageGroup$CreationTime' => 'The time that the model group was created.
', 'ModelPackageGroupSummary$CreationTime' => 'The time that the model group was created.
', 'ModelPackageSummary$CreationTime' => 'A timestamp that shows when the model package was created.
', 'NotebookInstanceLifecycleConfigSummary$CreationTime' => 'A timestamp that tells when the lifecycle configuration was created.
', 'NotebookInstanceSummary$CreationTime' => 'A timestamp that shows when the notebook instance was created.
', 'SpaceDetails$CreationTime' => 'The creation time.
', 'UserProfileDetails$CreationTime' => 'The creation time.
', ], ], 'CrossAccountFilterOption' => [ 'base' => NULL, 'refs' => [ 'SearchRequest$CrossAccountFilterOption' => ' A cross account filter option. When the value is "CrossAccount"
the search results will only include resources made discoverable to you from other accounts. When the value is "SameAccount"
or null
the search results will only include resources from your account. Default is null
. For more information on searching for resources made discoverable to your account, see Search discoverable resources in the SageMaker Developer Guide. The maximum number of ResourceCatalog
s viewable is 1000.
The list of all content type headers that Amazon SageMaker will treat as CSV and capture accordingly.
', ], ], 'CustomFileSystem' => [ 'base' => 'A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
', 'refs' => [ 'CustomFileSystems$member' => NULL, ], ], 'CustomFileSystemConfig' => [ 'base' => 'The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
', 'refs' => [ 'CustomFileSystemConfigs$member' => NULL, ], ], 'CustomFileSystemConfigs' => [ 'base' => NULL, 'refs' => [ 'UserSettings$CustomFileSystemConfigs' => 'The settings for assigning a custom file system to a user profile. Permitted users can access this file system in Amazon SageMaker Studio.
', ], ], 'CustomFileSystems' => [ 'base' => NULL, 'refs' => [ 'SpaceSettings$CustomFileSystems' => 'A file system, created by you, that you assign to a space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
', ], ], 'CustomImage' => [ 'base' => 'A custom SageMaker image. For more information, see Bring your own SageMaker image.
', 'refs' => [ 'CustomImages$member' => NULL, ], ], 'CustomImageContainerArguments' => [ 'base' => NULL, 'refs' => [ 'ContainerConfig$ContainerArguments' => 'The arguments for the container when you\'re running the application.
', ], ], 'CustomImageContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'ContainerConfig$ContainerEntrypoint' => 'The entrypoint used to run the application in the container.
', ], ], 'CustomImageContainerEnvironmentVariables' => [ 'base' => NULL, 'refs' => [ 'ContainerConfig$ContainerEnvironmentVariables' => 'The environment variables to set in the container
', ], ], 'CustomImages' => [ 'base' => NULL, 'refs' => [ 'JupyterLabAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a JupyterLab app.
', 'KernelGatewayAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a KernelGateway app.
', 'RSessionAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a RSession app.
', ], ], 'CustomPosixUserConfig' => [ 'base' => 'Details about the POSIX identity that is used for file system operations.
', 'refs' => [ 'UserSettings$CustomPosixUserConfig' => 'Details about the POSIX identity that is used for file system operations.
', ], ], 'CustomerMetadataKey' => [ 'base' => NULL, 'refs' => [ 'CustomerMetadataKeyList$member' => NULL, 'CustomerMetadataMap$key' => NULL, ], ], 'CustomerMetadataKeyList' => [ 'base' => NULL, 'refs' => [ 'UpdateModelPackageInput$CustomerMetadataPropertiesToRemove' => 'The metadata properties associated with the model package versions to remove.
', ], ], 'CustomerMetadataMap' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', 'DescribeModelPackageOutput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', 'ModelPackage$CustomerMetadataProperties' => 'The metadata properties for the model package.
', 'UpdateModelPackageInput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', ], ], 'CustomerMetadataValue' => [ 'base' => NULL, 'refs' => [ 'CustomerMetadataMap$value' => NULL, ], ], 'CustomizedMetricSpecification' => [ 'base' => 'A customized metric.
', 'refs' => [ 'MetricSpecification$Customized' => 'Information about a customized metric.
', ], ], 'DataCaptureConfig' => [ 'base' => 'Configuration to control how SageMaker captures inference data.
', 'refs' => [ 'CreateEndpointConfigInput$DataCaptureConfig' => NULL, 'DescribeEndpointConfigOutput$DataCaptureConfig' => NULL, ], ], 'DataCaptureConfigSummary' => [ 'base' => 'The currently active data capture configuration used by your Endpoint.
', 'refs' => [ 'DescribeEndpointOutput$DataCaptureConfig' => NULL, 'Endpoint$DataCaptureConfig' => NULL, ], ], 'DataCatalogConfig' => [ 'base' => 'The meta data of the Glue table which serves as data catalog for the OfflineStore
.
The meta data of the Glue table that is autogenerated when an OfflineStore
is created.
Whether the generated dataset is FullyReplicated
or ShardedByS3Key
(default).
The URL of the notebook location.
', ], ], 'DataInputConfig' => [ 'base' => NULL, 'refs' => [ 'DerivedInformation$DerivedDataInputConfig' => 'The data input configuration that SageMaker Neo automatically derived for the model. When SageMaker Neo derives this information, you don\'t need to specify the data input configuration when you create a compilation job.
', 'InputConfig$DataInputConfig' => 'Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are Framework
specific.
TensorFlow
: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"input":[1,1024,1024,3]}
If using the CLI, {\\"input\\":[1,1024,1024,3]}
Examples for two inputs:
If using the console, {"data1": [1,28,28,1], "data2":[1,28,28,1]}
If using the CLI, {\\"data1\\": [1,28,28,1], \\"data2\\":[1,28,28,1]}
KERAS
: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig
should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"input_1":[1,3,224,224]}
If using the CLI, {\\"input_1\\":[1,3,224,224]}
Examples for two inputs:
If using the console, {"input_1": [1,3,224,224], "input_2":[1,3,224,224]}
If using the CLI, {\\"input_1\\": [1,3,224,224], \\"input_2\\":[1,3,224,224]}
MXNET/ONNX/DARKNET
: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"data":[1,3,1024,1024]}
If using the CLI, {\\"data\\":[1,3,1024,1024]}
Examples for two inputs:
If using the console, {"var1": [1,1,28,28], "var2":[1,1,28,28]}
If using the CLI, {\\"var1\\": [1,1,28,28], \\"var2\\":[1,1,28,28]}
PyTorch
: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.
Examples for one input in dictionary format:
If using the console, {"input0":[1,3,224,224]}
If using the CLI, {\\"input0\\":[1,3,224,224]}
Example for one input in list format: [[1,3,224,224]]
Examples for two inputs in dictionary format:
If using the console, {"input0":[1,3,224,224], "input1":[1,3,224,224]}
If using the CLI, {\\"input0\\":[1,3,224,224], \\"input1\\":[1,3,224,224]}
Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]
XGBOOST
: input data name and shape are not needed.
DataInputConfig
supports the following parameters for CoreML
TargetDevice
(ML Model format):
shape
: Input shape, for example {"input_1": {"shape": [1,224,224,3]}}
. In addition to static input shapes, CoreML converter supports Flexible input shapes:
Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: {"input_1": {"shape": ["1..10", 224, 224, 3]}}
Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: {"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]}}
default_shape
: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example {"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]}}
type
: Input type. Allowed values: Image
and Tensor
. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias
and scale
.
bias
: If the input type is an Image, you need to provide the bias vector.
scale
: If the input type is an Image, you need to provide a scale factor.
CoreML ClassifierConfig
parameters can be specified using OutputConfig CompilerOptions
. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:
Tensor type input:
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]}}
Tensor type input without input name (PyTorch):
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]}]
Image type input:
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}}
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
Image type input without input name (PyTorch):
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}]
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
Depending on the model format, DataInputConfig
requires the following parameters for ml_eia2
OutputConfig:TargetDevice.
For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key
and the input model shapes for DataInputConfig
. Specify the signature_def_key
in OutputConfig:CompilerOptions
if the model does not use TensorFlow\'s default signature def key. For example:
"DataInputConfig": {"inputs": [1, 224, 224, 3]}
"CompilerOptions": {"signature_def_key": "serving_custom"}
For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig
and the output tensor names for output_names
in OutputConfig:CompilerOptions
. For example:
"DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]}
"CompilerOptions": {"output_names": ["output_tensor:0"]}
The input configuration object for the model.
', ], ], 'DataProcessing' => [ 'base' => 'The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
', 'refs' => [ 'CreateTransformJobRequest$DataProcessing' => 'The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
', 'DescribeTransformJobResponse$DataProcessing' => NULL, 'TransformJob$DataProcessing' => NULL, ], ], 'DataQualityAppSpecification' => [ 'base' => 'Information about the container that a data quality monitoring job runs.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityAppSpecification' => 'Specifies the container that runs the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityAppSpecification' => 'Information about the container that runs the data quality monitoring job.
', ], ], 'DataQualityBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityBaselineConfig' => 'Configures the constraints and baselines for the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityBaselineConfig' => 'The constraints and baselines for the data quality monitoring job definition.
', ], ], 'DataQualityJobInput' => [ 'base' => 'The input for the data quality monitoring job. Currently endpoints are supported for input.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityJobInput' => 'A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityJobInput' => 'The list of inputs for the data quality monitoring job. Currently endpoints are supported.
', ], ], 'DataSource' => [ 'base' => 'Describes the location of the channel data.
', 'refs' => [ 'Channel$DataSource' => 'The location of the channel data.
', ], ], 'DataSourceName' => [ 'base' => NULL, 'refs' => [ 'IdentityProviderOAuthSetting$DataSourceName' => 'The name of the data source that you\'re connecting to. Canvas currently supports OAuth for Snowflake and Salesforce Data Cloud.
', ], ], 'Database' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$Database' => 'The name of the Glue table database.
', ], ], 'DatasetDefinition' => [ 'base' => 'Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition
or RedshiftDatasetDefinition
types.
Configuration for a Dataset Definition input.
', ], ], 'DebugHookConfig' => [ 'base' => 'Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
', 'DescribeTrainingJobResponse$DebugRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
', 'TrainingJob$DebugRuleConfigurations' => 'Information about the debug rule configuration.
', ], ], 'DebugRuleEvaluationStatus' => [ 'base' => 'Information about the status of the rule evaluation.
', 'refs' => [ 'DebugRuleEvaluationStatuses$member' => NULL, ], ], 'DebugRuleEvaluationStatuses' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$DebugRuleEvaluationStatuses' => 'Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
', 'TrainingJob$DebugRuleEvaluationStatuses' => 'Information about the evaluation status of the rules for the training job.
', ], ], 'DefaultEbsStorageSettings' => [ 'base' => 'A collection of default EBS storage settings that applies to private spaces created within a domain or user profile.
', 'refs' => [ 'DefaultSpaceStorageSettings$DefaultEbsStorageSettings' => 'The default EBS storage settings for a private space.
', ], ], 'DefaultGid' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$DefaultGid' => 'The default POSIX group ID (GID). If not specified, defaults to 100
.
A collection of settings that apply to spaces created in the Domain.
', 'refs' => [ 'CreateDomainRequest$DefaultSpaceSettings' => 'The default settings used to create a space.
', 'DescribeDomainResponse$DefaultSpaceSettings' => 'The default settings used to create a space.
', 'UpdateDomainRequest$DefaultSpaceSettings' => 'The default settings used to create a space within the Domain.
', ], ], 'DefaultSpaceStorageSettings' => [ 'base' => 'The default storage settings for a private space.
', 'refs' => [ 'UserSettings$SpaceStorageSettings' => 'The storage settings for a private space.
', ], ], 'DefaultUid' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$DefaultUid' => 'The default POSIX user ID (UID). If not specified, defaults to 1000
.
The hub content dependency copy path.
', ], ], 'DependencyOriginPath' => [ 'base' => NULL, 'refs' => [ 'HubContentDependency$DependencyOriginPath' => 'The hub content dependency origin path.
', ], ], 'DeployedImage' => [ 'base' => 'Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag]
form to specify the image path of the primary container when you created the model hosted in this ProductionVariant
, the path resolves to a path of the form registry/repository[@digest]
. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
An array of DeployedImage
objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant
.
An array of DeployedImage
objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant
.
The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
', 'refs' => [ 'CreateEndpointInput$DeploymentConfig' => NULL, 'DescribeEndpointOutput$LastDeploymentConfig' => 'The most recent deployment configuration for the endpoint.
', 'UpdateEndpointInput$DeploymentConfig' => 'The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
', ], ], 'DeploymentRecommendation' => [ 'base' => 'A set of recommended deployment configurations for the model. To get more advanced recommendations, see CreateInferenceRecommendationsJob to create an inference recommendation job.
', 'refs' => [ 'DescribeModelOutput$DeploymentRecommendation' => 'A set of recommended deployment configurations for the model.
', 'Model$DeploymentRecommendation' => 'A set of recommended deployment configurations for the model.
', ], ], 'DeploymentStage' => [ 'base' => 'Contains information about a stage in an edge deployment plan.
', 'refs' => [ 'DeploymentStages$member' => NULL, ], ], 'DeploymentStageMaxResults' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgeDeploymentPlanRequest$MaxResults' => 'The maximum number of results to select (50 by default).
', ], ], 'DeploymentStageStatusSummaries' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgeDeploymentPlanResponse$Stages' => 'List of stages in the edge deployment plan.
', ], ], 'DeploymentStageStatusSummary' => [ 'base' => 'Contains information summarizing the deployment stage results.
', 'refs' => [ 'DeploymentStageStatusSummaries$member' => NULL, ], ], 'DeploymentStages' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanRequest$Stages' => 'List of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.
', 'CreateEdgeDeploymentStageRequest$Stages' => 'List of stages to be added to the edge deployment plan.
', ], ], 'DeregisterDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'DerivedInformation' => [ 'base' => 'Information that SageMaker Neo automatically derived about the model.
', 'refs' => [ 'DescribeCompilationJobResponse$DerivedInformation' => 'Information that SageMaker Neo automatically derived about the model.
', ], ], 'DescribeActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAlgorithmInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAlgorithmOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobV2Request' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobV2Response' => [ 'base' => NULL, 'refs' => [], ], 'DescribeClusterNodeRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeClusterNodeResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeClusterRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeClusterResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCompilationJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDataQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDataQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceFleetResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgeDeploymentPlanRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgeDeploymentPlanResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgePackagingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureMetadataResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFlowDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFlowDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubContentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubContentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHumanTaskUiRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHumanTaskUiResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceComponentInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceComponentOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceRecommendationsJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLabelingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLineageGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLineageGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelBiasJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelBiasJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardExportJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardExportJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelExplainabilityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelExplainabilityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageGroupInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageGroupOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineDefinitionForExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineDefinitionForExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProcessingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStudioLifecycleConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStudioLifecycleConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSubscribedWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSubscribedWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTransformJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'Description' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupRequest$Description' => 'A free-form description of a FeatureGroup
.
A free form description of the feature group.
', 'FeatureGroup$Description' => 'A free form description of a FeatureGroup
.
Specifies weight and capacity values for a production variant.
', 'refs' => [ 'DesiredWeightAndCapacityList$member' => NULL, ], ], 'DesiredWeightAndCapacityList' => [ 'base' => NULL, 'refs' => [ 'UpdateEndpointWeightsAndCapacitiesInput$DesiredWeightsAndCapacities' => 'An object that provides new capacity and weight values for a variant.
', ], ], 'DestinationS3Uri' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceOutputConfig$S3OutputPath' => 'The Amazon S3 location to upload inference responses to.
', 'AsyncInferenceOutputConfig$S3FailurePath' => 'The Amazon S3 location to upload failure inference responses to.
', 'BatchTransformInput$DataCapturedDestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'DataCaptureConfig$DestinationS3Uri' => 'The Amazon S3 location used to capture the data.
', 'DataCaptureConfigSummary$DestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'InferenceExperimentDataStorageConfig$Destination' => 'The Amazon S3 bucket where the inference request and response data is stored.
', 'ProductionVariantCoreDumpConfig$DestinationS3Uri' => 'The Amazon S3 bucket to send the core dump to.
', ], ], 'DetailedAlgorithmStatus' => [ 'base' => NULL, 'refs' => [ 'AlgorithmStatusItem$Status' => 'The current status.
', ], ], 'DetailedModelPackageStatus' => [ 'base' => NULL, 'refs' => [ 'ModelPackageStatusItem$Status' => 'The current status.
', ], ], 'Device' => [ 'base' => 'Information of a particular device.
', 'refs' => [ 'Devices$member' => NULL, ], ], 'DeviceArn' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$DeviceArn' => 'The Amazon Resource Name (ARN) of the device.
', 'DeviceDeploymentSummary$DeviceArn' => 'The ARN of the device.
', 'DeviceSummary$DeviceArn' => 'Amazon Resource Name (ARN) of the device.
', ], ], 'DeviceDeploymentStatus' => [ 'base' => NULL, 'refs' => [ 'DeviceDeploymentSummary$DeviceDeploymentStatus' => 'The deployment status of the device.
', ], ], 'DeviceDeploymentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListStageDevicesResponse$DeviceDeploymentSummaries' => 'List of summaries of devices allocated to the stage.
', ], ], 'DeviceDeploymentSummary' => [ 'base' => 'Contains information summarizing device details and deployment status.
', 'refs' => [ 'DeviceDeploymentSummaries$member' => NULL, ], ], 'DeviceDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$Description' => 'A description of the device.
', 'Device$Description' => 'Description of the device.
', 'DeviceDeploymentSummary$Description' => 'The description of the device.
', 'DeviceSummary$Description' => 'A description of the device.
', ], ], 'DeviceFleetArn' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceFleetResponse$DeviceFleetArn' => 'The The Amazon Resource Name (ARN) of the fleet.
', 'DeviceFleetSummary$DeviceFleetArn' => 'Amazon Resource Name (ARN) of the device fleet.
', 'GetDeviceFleetReportResponse$DeviceFleetArn' => 'The Amazon Resource Name (ARN) of the device.
', ], ], 'DeviceFleetDescription' => [ 'base' => NULL, 'refs' => [ 'CreateDeviceFleetRequest$Description' => 'A description of the fleet.
', 'DescribeDeviceFleetResponse$Description' => 'A description of the fleet.
', 'GetDeviceFleetReportResponse$Description' => 'Description of the fleet.
', 'UpdateDeviceFleetRequest$Description' => 'Description of the fleet.
', ], ], 'DeviceFleetSummaries' => [ 'base' => NULL, 'refs' => [ 'ListDeviceFleetsResponse$DeviceFleetSummaries' => 'Summary of the device fleet.
', ], ], 'DeviceFleetSummary' => [ 'base' => 'Summary of the device fleet.
', 'refs' => [ 'DeviceFleetSummaries$member' => NULL, ], ], 'DeviceName' => [ 'base' => NULL, 'refs' => [ 'Device$DeviceName' => 'The name of the device.
', 'DeviceDeploymentSummary$DeviceName' => 'The name of the device.
', 'DeviceNames$member' => NULL, 'DeviceSelectionConfig$DeviceNameContains' => 'A filter to select devices with names containing this name.
', ], ], 'DeviceNames' => [ 'base' => NULL, 'refs' => [ 'DeregisterDevicesRequest$DeviceNames' => 'The unique IDs of the devices.
', 'DeviceSelectionConfig$DeviceNames' => 'List of devices chosen to deploy.
', ], ], 'DeviceSelectionConfig' => [ 'base' => 'Contains information about the configurations of selected devices.
', 'refs' => [ 'DeploymentStage$DeviceSelectionConfig' => 'Configuration of the devices in the stage.
', 'DeploymentStageStatusSummary$DeviceSelectionConfig' => 'Configuration of the devices in the stage.
', ], ], 'DeviceStats' => [ 'base' => 'Status of devices.
', 'refs' => [ 'GetDeviceFleetReportResponse$DeviceStats' => 'Status of devices.
', ], ], 'DeviceSubsetType' => [ 'base' => NULL, 'refs' => [ 'DeviceSelectionConfig$DeviceSubsetType' => 'Type of device subsets to deploy to the current stage.
', ], ], 'DeviceSummaries' => [ 'base' => NULL, 'refs' => [ 'ListDevicesResponse$DeviceSummaries' => 'Summary of devices.
', ], ], 'DeviceSummary' => [ 'base' => 'Summary of the device.
', 'refs' => [ 'DeviceSummaries$member' => NULL, ], ], 'Devices' => [ 'base' => NULL, 'refs' => [ 'RegisterDevicesRequest$Devices' => 'A list of devices to register with SageMaker Edge Manager.
', 'UpdateDevicesRequest$Devices' => 'List of devices to register with Edge Manager agent.
', ], ], 'Dimension' => [ 'base' => NULL, 'refs' => [ 'VectorConfig$Dimension' => 'The number of elements in your vector.
', ], ], 'DirectDeploySettings' => [ 'base' => 'The model deployment settings for the SageMaker Canvas application.
In order to enable model deployment for Canvas, the SageMaker Domain\'s or user profile\'s Amazon Web Services IAM execution role must have the AmazonSageMakerCanvasDirectDeployAccess
policy attached. You can also turn on model deployment permissions through the SageMaker Domain\'s or user profile\'s settings in the SageMaker console.
The model deployment settings for the SageMaker Canvas application.
', ], ], 'DirectInternetAccess' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$DirectInternetAccess' => 'Sets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled
this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled
only if you set a value for the SubnetId
parameter.
Describes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.
For more information, see Notebook Instances Are Internet-Enabled by Default.
', ], ], 'Direction' => [ 'base' => NULL, 'refs' => [ 'QueryLineageRequest$Direction' => 'Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.
', ], ], 'DirectoryPath' => [ 'base' => NULL, 'refs' => [ 'CheckpointConfig$LocalPath' => '(Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/
.
Path to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/
.
Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/
.
The full path to the directory to associate with the channel.
', 'ProfilerRuleConfiguration$LocalPath' => 'Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/
.
Path to local storage location for tensorBoard output. Defaults to /opt/ml/output/tensorboard
.
Configuration to turn off Amazon SageMaker Debugger\'s system monitoring and profiling functionality. To turn it off, set to True
.
To turn off Amazon SageMaker Debugger monitoring and profiling while a training job is in progress, set to True
.
A list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateDefaultCodeRepository' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateDefaultCodeRepository' => 'The name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateNotebookInstanceAcceleratorTypes' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateAcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types to remove from this notebook instance. This operation is idempotent. If you specify an accelerator type that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateNotebookInstanceLifecycleConfig' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateLifecycleConfig' => 'Set to true
to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.
A collection of settings that configure the domain\'s Docker interaction.
', 'refs' => [ 'DomainSettings$DockerSettings' => 'A collection of settings that configure the domain\'s Docker interaction.
', 'DomainSettingsForUpdate$DockerSettings' => 'A collection of settings that configure the domain\'s Docker interaction.
', ], ], 'DocumentSchemaVersion' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$DocumentSchemaVersion' => 'The document schema version for the hub content.
', 'HubContentInfo$DocumentSchemaVersion' => 'The version of the hub content document schema.
', 'ImportHubContentRequest$DocumentSchemaVersion' => 'The version of the hub content schema to import.
', 'ListHubContentVersionsRequest$MaxSchemaVersion' => 'The upper bound of the hub content schema version.
', 'ListHubContentsRequest$MaxSchemaVersion' => 'The upper bound of the hub content schema verion.
', ], ], 'Dollars' => [ 'base' => NULL, 'refs' => [ 'USD$Dollars' => 'The whole number of dollars in the amount.
', ], ], 'DomainArn' => [ 'base' => NULL, 'refs' => [ 'CreateDomainResponse$DomainArn' => 'The Amazon Resource Name (ARN) of the created domain.
', 'DescribeDomainResponse$DomainArn' => 'The domain\'s Amazon Resource Name (ARN).
', 'DomainDetails$DomainArn' => 'The domain\'s Amazon Resource Name (ARN).
', 'UpdateDomainResponse$DomainArn' => 'The Amazon Resource Name (ARN) of the domain.
', ], ], 'DomainDetails' => [ 'base' => 'The domain\'s details.
', 'refs' => [ 'DomainList$member' => NULL, ], ], 'DomainId' => [ 'base' => NULL, 'refs' => [ 'AppDetails$DomainId' => 'The domain ID.
', 'CreateAppRequest$DomainId' => 'The domain ID.
', 'CreatePresignedDomainUrlRequest$DomainId' => 'The domain ID.
', 'CreateSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'CreateUserProfileRequest$DomainId' => 'The ID of the associated Domain.
', 'DeleteAppRequest$DomainId' => 'The domain ID.
', 'DeleteDomainRequest$DomainId' => 'The domain ID.
', 'DeleteSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'DeleteUserProfileRequest$DomainId' => 'The domain ID.
', 'DescribeAppRequest$DomainId' => 'The domain ID.
', 'DescribeAppResponse$DomainId' => 'The domain ID.
', 'DescribeDomainRequest$DomainId' => 'The domain ID.
', 'DescribeDomainResponse$DomainId' => 'The domain ID.
', 'DescribeSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'DescribeSpaceResponse$DomainId' => 'The ID of the associated Domain.
', 'DescribeUserProfileRequest$DomainId' => 'The domain ID.
', 'DescribeUserProfileResponse$DomainId' => 'The ID of the domain that contains the profile.
', 'DomainDetails$DomainId' => 'The domain ID.
', 'ListAppsRequest$DomainIdEquals' => 'A parameter to search for the domain ID.
', 'ListSpacesRequest$DomainIdEquals' => 'A parameter to search for the Domain ID.
', 'ListUserProfilesRequest$DomainIdEquals' => 'A parameter by which to filter the results.
', 'SpaceDetails$DomainId' => 'The ID of the associated Domain.
', 'UpdateDomainRequest$DomainId' => 'The ID of the domain to be updated.
', 'UpdateSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'UpdateUserProfileRequest$DomainId' => 'The domain ID.
', 'UserProfileDetails$DomainId' => 'The domain ID.
', ], ], 'DomainList' => [ 'base' => NULL, 'refs' => [ 'ListDomainsResponse$Domains' => 'The list of domains.
', ], ], 'DomainName' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$DomainName' => 'A name for the domain.
', 'DescribeDomainResponse$DomainName' => 'The domain name.
', 'DomainDetails$DomainName' => 'The domain name.
', ], ], 'DomainSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'DomainSettings$SecurityGroupIds' => 'The security groups for the Amazon Virtual Private Cloud that the Domain
uses for communication between Domain-level apps and user apps.
The security groups for the Amazon Virtual Private Cloud that the Domain
uses for communication between Domain-level apps and user apps.
A collection of settings that apply to the SageMaker Domain
. These settings are specified through the CreateDomain
API call.
A collection of Domain
settings.
A collection of Domain
settings.
A collection of Domain
configuration settings to update.
A collection of DomainSettings
configuration values to update.
The status.
', 'DomainDetails$Status' => 'The status.
', ], ], 'Double' => [ 'base' => NULL, 'refs' => [ 'TargetTrackingScalingPolicyConfiguration$TargetValue' => 'The recommended target value to specify for the metric when creating a scaling policy.
', ], ], 'DoubleParameterValue' => [ 'base' => NULL, 'refs' => [ 'TrialComponentParameterValue$NumberValue' => 'The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can\'t specify the StringValue
parameter.
Represents the drift check baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'CreateModelPackageInput$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
', 'DescribeModelPackageOutput$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
', 'ModelPackage$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckBias' => [ 'base' => 'Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$Bias' => 'Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckExplainability' => [ 'base' => 'Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$Explainability' => 'Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckModelDataQuality' => [ 'base' => 'Represents the drift check data quality baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$ModelDataQuality' => 'Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckModelQuality' => [ 'base' => 'Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$ModelQuality' => 'Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
', ], ], 'DynamicScalingConfiguration' => [ 'base' => 'An object with the recommended values for you to specify when creating an autoscaling policy.
', 'refs' => [ 'GetScalingConfigurationRecommendationResponse$DynamicScalingConfiguration' => 'An object with the recommended values for you to specify when creating an autoscaling policy.
', ], ], 'EFSFileSystem' => [ 'base' => 'A file system, created by you in Amazon EFS, that you assign to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
', 'refs' => [ 'CustomFileSystem$EFSFileSystem' => 'A custom file system in Amazon EFS.
', ], ], 'EFSFileSystemConfig' => [ 'base' => 'The settings for assigning a custom Amazon EFS file system to a user profile or space for an Amazon SageMaker Domain.
', 'refs' => [ 'CustomFileSystemConfig$EFSFileSystemConfig' => 'The settings for a custom Amazon EFS file system.
', ], ], 'EMRStepMetadata' => [ 'base' => 'The configurations and outcomes of an Amazon EMR step execution.
', 'refs' => [ 'PipelineExecutionStepMetadata$EMR' => 'The configurations and outcomes of an Amazon EMR step execution.
', ], ], 'EbsStorageSettings' => [ 'base' => 'A collection of EBS storage settings that applies to private spaces.
', 'refs' => [ 'SpaceStorageSettings$EbsStorageSettings' => 'A collection of EBS storage settings for a private space.
', ], ], 'Edge' => [ 'base' => 'A directed edge connecting two lineage entities.
', 'refs' => [ 'Edges$member' => NULL, ], ], 'EdgeDeploymentConfig' => [ 'base' => 'Contains information about the configuration of a deployment.
', 'refs' => [ 'DeploymentStage$DeploymentConfig' => 'Configuration of the deployment details.
', 'DeploymentStageStatusSummary$DeploymentConfig' => 'Configuration of the deployment details.
', ], ], 'EdgeDeploymentModelConfig' => [ 'base' => 'Contains information about the configuration of a model in a deployment.
', 'refs' => [ 'EdgeDeploymentModelConfigs$member' => NULL, ], ], 'EdgeDeploymentModelConfigs' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanRequest$ModelConfigs' => 'List of models associated with the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$ModelConfigs' => 'List of models associated with the edge deployment plan.
', ], ], 'EdgeDeploymentPlanArn' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanResponse$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPlanArn' => 'The ARN of edge deployment plan.
', 'DeviceDeploymentSummary$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', ], ], 'EdgeDeploymentPlanSummaries' => [ 'base' => NULL, 'refs' => [ 'ListEdgeDeploymentPlansResponse$EdgeDeploymentPlanSummaries' => 'List of summaries of edge deployment plans.
', ], ], 'EdgeDeploymentPlanSummary' => [ 'base' => 'Contains information summarizing an edge deployment plan.
', 'refs' => [ 'EdgeDeploymentPlanSummaries$member' => NULL, ], ], 'EdgeDeploymentStatus' => [ 'base' => 'Contains information summarizing the deployment stage results.
', 'refs' => [ 'DeploymentStageStatusSummary$DeploymentStatus' => 'General status of the current state.
', ], ], 'EdgeModel' => [ 'base' => 'The model on the edge device.
', 'refs' => [ 'EdgeModels$member' => NULL, ], ], 'EdgeModelStat' => [ 'base' => 'Status of edge devices with this model.
', 'refs' => [ 'EdgeModelStats$member' => NULL, ], ], 'EdgeModelStats' => [ 'base' => NULL, 'refs' => [ 'GetDeviceFleetReportResponse$ModelStats' => 'Status of model on device.
', ], ], 'EdgeModelSummaries' => [ 'base' => NULL, 'refs' => [ 'DeviceSummary$Models' => 'Models on the device.
', ], ], 'EdgeModelSummary' => [ 'base' => 'Summary of model on edge device.
', 'refs' => [ 'EdgeModelSummaries$member' => NULL, ], ], 'EdgeModels' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$Models' => 'Models on the device.
', ], ], 'EdgeOutputConfig' => [ 'base' => 'The output configuration.
', 'refs' => [ 'CreateDeviceFleetRequest$OutputConfig' => 'The output configuration for storing sample data collected by the fleet.
', 'CreateEdgePackagingJobRequest$OutputConfig' => 'Provides information about the output location for the packaged model.
', 'DescribeDeviceFleetResponse$OutputConfig' => 'The output configuration for storing sampled data.
', 'DescribeEdgePackagingJobResponse$OutputConfig' => 'The output configuration for the edge packaging job.
', 'GetDeviceFleetReportResponse$OutputConfig' => 'The output configuration for storing sample data collected by the fleet.
', 'UpdateDeviceFleetRequest$OutputConfig' => 'Output configuration for storing sample data collected by the fleet.
', ], ], 'EdgePackagingJobArn' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgePackagingJobResponse$EdgePackagingJobArn' => 'The Amazon Resource Name (ARN) of the edge packaging job.
', 'EdgePackagingJobSummary$EdgePackagingJobArn' => 'The Amazon Resource Name (ARN) of the edge packaging job.
', ], ], 'EdgePackagingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgePackagingJobResponse$EdgePackagingJobStatus' => 'The current status of the packaging job.
', 'EdgePackagingJobSummary$EdgePackagingJobStatus' => 'The status of the edge packaging job.
', 'ListEdgePackagingJobsRequest$StatusEquals' => 'The job status to filter for.
', ], ], 'EdgePackagingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListEdgePackagingJobsResponse$EdgePackagingJobSummaries' => 'Summaries of edge packaging jobs.
', ], ], 'EdgePackagingJobSummary' => [ 'base' => 'Summary of edge packaging job.
', 'refs' => [ 'EdgePackagingJobSummaries$member' => NULL, ], ], 'EdgePresetDeploymentArtifact' => [ 'base' => NULL, 'refs' => [ 'EdgePresetDeploymentOutput$Artifact' => 'The Amazon Resource Name (ARN) of the generated deployable resource.
', ], ], 'EdgePresetDeploymentOutput' => [ 'base' => 'The output of a SageMaker Edge Manager deployable resource.
', 'refs' => [ 'DescribeEdgePackagingJobResponse$PresetDeploymentOutput' => 'The output of a SageMaker Edge Manager deployable resource.
', ], ], 'EdgePresetDeploymentStatus' => [ 'base' => NULL, 'refs' => [ 'EdgePresetDeploymentOutput$Status' => 'The status of the deployable resource.
', ], ], 'EdgePresetDeploymentType' => [ 'base' => NULL, 'refs' => [ 'EdgeOutputConfig$PresetDeploymentType' => 'The deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
', 'EdgePresetDeploymentOutput$Type' => 'The deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
', ], ], 'EdgeVersion' => [ 'base' => NULL, 'refs' => [ 'AgentVersion$Version' => 'Version of the agent.
', 'CreateEdgePackagingJobRequest$ModelVersion' => 'The version of the model.
', 'DescribeDeviceResponse$AgentVersion' => 'Edge Manager agent version.
', 'DescribeEdgePackagingJobResponse$ModelVersion' => 'The version of the model.
', 'DeviceSummary$AgentVersion' => 'Edge Manager agent version.
', 'EdgeModel$ModelVersion' => 'The model version.
', 'EdgeModelStat$ModelVersion' => 'The model version.
', 'EdgeModelSummary$ModelVersion' => 'The version model.
', 'EdgePackagingJobSummary$ModelVersion' => 'The version of the model.
', ], ], 'Edges' => [ 'base' => NULL, 'refs' => [ 'QueryLineageResponse$Edges' => 'A list of edges that connect vertices in the response.
', ], ], 'EfsUid' => [ 'base' => NULL, 'refs' => [ 'DescribeSpaceResponse$HomeEfsFileSystemUid' => 'The ID of the space\'s profile in the Amazon Elastic File System volume.
', 'DescribeUserProfileResponse$HomeEfsFileSystemUid' => 'The ID of the user\'s profile in the Amazon Elastic File System (EFS) volume.
', ], ], 'EnableCapture' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$EnableCapture' => 'Whether data capture should be enabled or disabled (defaults to enabled).
', 'DataCaptureConfigSummary$EnableCapture' => 'Whether data capture is enabled or disabled.
', ], ], 'EnableInfraCheck' => [ 'base' => NULL, 'refs' => [ 'InfraCheckConfig$EnableInfraCheck' => 'Enables an infrastructure health check.
', ], ], 'EnableIotRoleAlias' => [ 'base' => NULL, 'refs' => [ 'CreateDeviceFleetRequest$EnableIotRoleAlias' => 'Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
', 'UpdateDeviceFleetRequest$EnableIotRoleAlias' => 'Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
', ], ], 'EnableRemoteDebug' => [ 'base' => NULL, 'refs' => [ 'RemoteDebugConfig$EnableRemoteDebug' => 'If set to True, enables remote debugging.
', 'RemoteDebugConfigForUpdate$EnableRemoteDebug' => 'If set to True, enables remote debugging.
', ], ], 'EnableSagemakerServicecatalogPortfolioInput' => [ 'base' => NULL, 'refs' => [], ], 'EnableSagemakerServicecatalogPortfolioOutput' => [ 'base' => NULL, 'refs' => [], ], 'Endpoint' => [ 'base' => 'A hosted endpoint for real-time inference.
', 'refs' => [ 'SearchRecord$Endpoint' => NULL, ], ], 'EndpointArn' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'DescribeEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'DescribeInferenceComponentOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint that hosts the inference component.
', 'Endpoint$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'EndpointSummary$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'InferenceComponentSummary$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint that hosts the inference component.
', 'ModelDashboardEndpoint$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'UpdateEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'UpdateEndpointWeightsAndCapacitiesOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the updated endpoint.
', ], ], 'EndpointConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigOutput$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', 'DescribeEndpointConfigOutput$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', 'EndpointConfigSummary$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', ], ], 'EndpointConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
', 'CreateEndpointInput$EndpointConfigName' => 'The name of an endpoint configuration. For more information, see CreateEndpointConfig.
', 'DeleteEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration that you want to delete.
', 'DescribeEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration.
', 'DescribeEndpointConfigOutput$EndpointConfigName' => 'Name of the SageMaker endpoint configuration.
', 'DescribeEndpointOutput$EndpointConfigName' => 'The name of the endpoint configuration associated with this endpoint.
', 'Endpoint$EndpointConfigName' => 'The endpoint configuration associated with the endpoint.
', 'EndpointConfigSummary$EndpointConfigName' => 'The name of the endpoint configuration.
', 'EndpointMetadata$EndpointConfigName' => 'The name of the endpoint configuration.
', 'PendingDeploymentSummary$EndpointConfigName' => 'The name of the endpoint configuration used in the deployment.
', 'UpdateEndpointInput$EndpointConfigName' => 'The name of the new endpoint configuration.
', ], ], 'EndpointConfigNameContains' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$NameContains' => 'A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.
', ], ], 'EndpointConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$SortBy' => 'The field to sort results by. The default is CreationTime
.
Provides summary information for an endpoint configuration.
', 'refs' => [ 'EndpointConfigSummaryList$member' => NULL, ], ], 'EndpointConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsOutput$EndpointConfigs' => 'An array of endpoint configurations.
', ], ], 'EndpointInfo' => [ 'base' => 'Details about a customer endpoint that was compared in an Inference Recommender job.
', 'refs' => [ 'EndpointPerformance$EndpointInfo' => NULL, 'Endpoints$member' => NULL, ], ], 'EndpointInput' => [ 'base' => 'Input object for the endpoint
', 'refs' => [ 'DataQualityJobInput$EndpointInput' => NULL, 'ModelBiasJobInput$EndpointInput' => NULL, 'ModelExplainabilityJobInput$EndpointInput' => NULL, 'ModelQualityJobInput$EndpointInput' => NULL, 'MonitoringInput$EndpointInput' => 'The endpoint for a monitoring job.
', ], ], 'EndpointInputConfiguration' => [ 'base' => 'The endpoint configuration for the load test.
', 'refs' => [ 'EndpointInputConfigurations$member' => NULL, ], ], 'EndpointInputConfigurations' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$EndpointConfigurations' => 'Specifies the endpoint configuration to use for a job.
', ], ], 'EndpointMetadata' => [ 'base' => 'The metadata of the endpoint.
', 'refs' => [ 'DescribeInferenceExperimentResponse$EndpointMetadata' => 'The metadata of the endpoint on which the inference experiment ran.
', ], ], 'EndpointName' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointInput$EndpointName' => 'The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint
, but the case is preserved and must be matched in InvokeEndpoint.
The name of an existing endpoint where you host the inference component.
', 'CreateInferenceExperimentRequest$EndpointName' => 'The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.
', 'DeleteEndpointInput$EndpointName' => 'The name of the endpoint that you want to delete.
', 'DescribeEndpointInput$EndpointName' => 'The name of the endpoint.
', 'DescribeEndpointOutput$EndpointName' => 'Name of the endpoint.
', 'DescribeInferenceComponentOutput$EndpointName' => 'The name of the endpoint that hosts the inference component.
', 'DescribeMonitoringScheduleResponse$EndpointName' => 'The name of the endpoint for the monitoring job.
', 'Endpoint$EndpointName' => 'The name of the endpoint.
', 'EndpointInfo$EndpointName' => 'The name of a customer\'s endpoint.
', 'EndpointInput$EndpointName' => 'An endpoint in customer\'s account which has enabled DataCaptureConfig
enabled.
The name of the endpoint.
', 'EndpointSummary$EndpointName' => 'The name of the endpoint.
', 'GetScalingConfigurationRecommendationRequest$EndpointName' => 'The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName
field.
Specify either this field or the RecommendationId
field.
The name of an endpoint benchmarked during a previously completed Inference Recommender job.
', 'InferenceComponentSummary$EndpointName' => 'The name of the endpoint that hosts the inference component.
', 'ListDataQualityJobDefinitionsRequest$EndpointName' => 'A filter that lists the data quality job definitions associated with the specified endpoint.
', 'ListInferenceComponentsInput$EndpointNameEquals' => 'An endpoint name to filter the listed inference components. The response includes only those inference components that are hosted at the specified endpoint.
', 'ListModelBiasJobDefinitionsRequest$EndpointName' => 'Name of the endpoint to monitor for model bias.
', 'ListModelExplainabilityJobDefinitionsRequest$EndpointName' => 'Name of the endpoint to monitor for model explainability.
', 'ListModelQualityJobDefinitionsRequest$EndpointName' => 'A filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.
', 'ListMonitoringExecutionsRequest$EndpointName' => 'Name of a specific endpoint to fetch jobs for.
', 'ListMonitoringSchedulesRequest$EndpointName' => 'Name of a specific endpoint to fetch schedules for.
', 'ModelDashboardEndpoint$EndpointName' => 'The endpoint name.
', 'ModelDashboardMonitoringSchedule$EndpointName' => 'The endpoint which is monitored.
', 'ModelDeployConfig$EndpointName' => 'Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically.
Specify the EndpointName
if and only if you set AutoGenerateEndpointName
to False
; otherwise a 400 error is thrown.
The name of the endpoint to which the model has been deployed.
If model deployment fails, this field is omitted from the response.
The name of the endpoint used to run the monitoring job.
', 'MonitoringJobDefinitionSummary$EndpointName' => 'The name of the endpoint that the job monitors.
', 'MonitoringSchedule$EndpointName' => 'The endpoint that hosts the model being monitored.
', 'MonitoringScheduleSummary$EndpointName' => 'The name of the endpoint using the monitoring schedule.
', 'UpdateEndpointInput$EndpointName' => 'The name of the endpoint whose configuration you want to update.
', 'UpdateEndpointWeightsAndCapacitiesInput$EndpointName' => 'The name of an existing SageMaker endpoint.
', ], ], 'EndpointNameContains' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsInput$NameContains' => 'A string in endpoint names. This filter returns only endpoints whose name contains the specified string.
', ], ], 'EndpointOutputConfiguration' => [ 'base' => 'The endpoint configuration made by Inference Recommender during a recommendation job.
', 'refs' => [ 'InferenceRecommendation$EndpointConfiguration' => 'Defines the endpoint configuration parameters.
', 'RecommendationJobInferenceBenchmark$EndpointConfiguration' => NULL, ], ], 'EndpointPerformance' => [ 'base' => 'The performance results from running an Inference Recommender job on an existing endpoint.
', 'refs' => [ 'EndpointPerformances$member' => NULL, ], ], 'EndpointPerformances' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$EndpointPerformances' => 'The performance results from running an Inference Recommender job on an existing endpoint.
', ], ], 'EndpointSortKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsInput$SortBy' => 'Sorts the list of results. The default is CreationTime
.
The status of the endpoint.
OutOfService
: Endpoint is not available to take incoming requests.
Creating
: CreateEndpoint is executing.
Updating
: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating
: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack
: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService
status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService
: Endpoint is available to process incoming requests.
Deleting
: DeleteEndpoint is executing.
Failed
: Endpoint could not be created, updated, or re-scaled. Use the FailureReason
value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
UpdateRollbackFailed
: Both the rolling deployment and auto-rollback failed. Your endpoint is in service with a mix of the old and new endpoint configurations. For information about how to remedy this issue and restore the endpoint\'s status to InService
, see Rolling Deployments.
The status of the endpoint.
', 'EndpointMetadata$EndpointStatus' => 'The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary.
', 'EndpointSummary$EndpointStatus' => 'The status of the endpoint.
OutOfService
: Endpoint is not available to take incoming requests.
Creating
: CreateEndpoint is executing.
Updating
: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating
: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack
: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService
status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService
: Endpoint is available to process incoming requests.
Deleting
: DeleteEndpoint is executing.
Failed
: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason
for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
To get a list of endpoints with a specified status, use the StatusEquals
filter with a call to ListEndpoints.
A filter that returns only endpoints with the specified status.
', 'ModelDashboardEndpoint$EndpointStatus' => 'The endpoint status.
', ], ], 'EndpointSummary' => [ 'base' => 'Provides summary information for an endpoint.
', 'refs' => [ 'EndpointSummaryList$member' => NULL, ], ], 'EndpointSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsOutput$Endpoints' => 'An array or endpoint objects.
', ], ], 'Endpoints' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$Endpoints' => 'Existing customer endpoints on which to run an Inference Recommender job.
', ], ], 'EntityDescription' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Description' => 'A description of the additional Inference specification
', 'AlgorithmSummary$AlgorithmDescription' => 'A brief description of the algorithm.
', 'BatchDescribeModelPackageSummary$ModelPackageDescription' => 'The description of the model package.
', 'ChannelSpecification$Description' => 'A brief description of the channel.
', 'CreateAlgorithmInput$AlgorithmDescription' => 'A description of the algorithm.
', 'CreateModelPackageGroupInput$ModelPackageGroupDescription' => 'A description for the model group.
', 'CreateModelPackageInput$ModelPackageDescription' => 'A description of the model package.
', 'CreateProjectInput$ProjectDescription' => 'A description for the project.
', 'DescribeAlgorithmOutput$AlgorithmDescription' => 'A brief summary about the algorithm.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupDescription' => 'A description of the model group.
', 'DescribeModelPackageOutput$ModelPackageDescription' => 'A brief summary of the model package.
', 'DescribeProjectOutput$ProjectDescription' => 'The description of the project.
', 'HyperParameterSpecification$Description' => 'A brief description of the hyperparameter.
', 'ModelPackage$ModelPackageDescription' => 'The description of the model package.
', 'ModelPackageGroup$ModelPackageGroupDescription' => 'The description for the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupDescription' => 'A description of the model group.
', 'ModelPackageSummary$ModelPackageDescription' => 'A brief description of the model package.
', 'Project$ProjectDescription' => 'The description of the project.
', 'ProjectSummary$ProjectDescription' => 'The description of the project.
', 'UpdateProjectInput$ProjectDescription' => 'The description for the project.
', ], ], 'EntityName' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Name' => 'A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
', 'AlgorithmStatusItem$Name' => 'The name of the algorithm for which the overall status is being reported.
', 'AlgorithmSummary$AlgorithmName' => 'The name of the algorithm that is described by the summary.
', 'AlgorithmValidationProfile$ProfileName' => 'The name of the profile for the algorithm. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'BatchDescribeModelPackageSummary$ModelPackageGroupName' => 'The group name for the model package
', 'CodeRepositorySummary$CodeRepositoryName' => 'The name of the Git repository.
', 'CompilationJobSummary$CompilationJobName' => 'The name of the model compilation job that you want a summary for.
', 'CreateAlgorithmInput$AlgorithmName' => 'The name of the algorithm.
', 'CreateCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'CreateCompilationJobRequest$CompilationJobName' => 'A name for the model compilation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.
', 'CreateDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet that the device belongs to.
', 'CreateEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'CreateEdgeDeploymentPlanRequest$DeviceFleetName' => 'The device fleet used for this edge deployment plan.
', 'CreateEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'CreateEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'CreateEdgePackagingJobRequest$CompilationJobName' => 'The name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.
', 'CreateEdgePackagingJobRequest$ModelName' => 'The name of the model.
', 'CreateModelCardExportJobRequest$ModelCardExportJobName' => 'The name of the model card export job.
', 'CreateModelCardRequest$ModelCardName' => 'The unique name of the model card.
', 'CreateModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group.
', 'CreateModelPackageInput$ModelPackageName' => 'The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
', 'DeleteAlgorithmInput$AlgorithmName' => 'The name of the algorithm to delete.
', 'DeleteCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to delete.
', 'DeleteCompilationJobRequest$CompilationJobName' => 'The name of the compilation job to delete.
', 'DeleteDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet to delete.
', 'DeleteEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to delete.
', 'DeleteEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan from which the stage will be deleted.
', 'DeleteEdgeDeploymentStageRequest$StageName' => 'The name of the stage.
', 'DeleteModelCardRequest$ModelCardName' => 'The name of the model card to delete.
', 'DeleteModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group for which to delete the policy.
', 'DeploymentStage$StageName' => 'The name of the stage.
', 'DeploymentStageStatusSummary$StageName' => 'The name of the stage.
', 'DeregisterDevicesRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', 'DescribeAlgorithmOutput$AlgorithmName' => 'The name of the algorithm being described.
', 'DescribeCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to describe.
', 'DescribeCodeRepositoryOutput$CodeRepositoryName' => 'The name of the Git repository.
', 'DescribeCompilationJobRequest$CompilationJobName' => 'The name of the model compilation job that you want information about.
', 'DescribeCompilationJobResponse$CompilationJobName' => 'The name of the model compilation job.
', 'DescribeDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet.
', 'DescribeDeviceFleetResponse$DeviceFleetName' => 'The name of the fleet.
', 'DescribeDeviceRequest$DeviceName' => 'The unique ID of the device.
', 'DescribeDeviceRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', 'DescribeDeviceResponse$DeviceName' => 'The unique identifier of the device.
', 'DescribeDeviceResponse$DeviceFleetName' => 'The name of the fleet the device belongs to.
', 'DescribeEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the deployment plan to describe.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$DeviceFleetName' => 'The device fleet used for this edge deployment plan.
', 'DescribeEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'DescribeEdgePackagingJobResponse$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'DescribeEdgePackagingJobResponse$CompilationJobName' => 'The name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged.
', 'DescribeEdgePackagingJobResponse$ModelName' => 'The name of the model.
', 'DescribeModelCardExportJobResponse$ModelCardExportJobName' => 'The name of the model card export job to describe.
', 'DescribeModelCardExportJobResponse$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card that the model export job exports.
', 'DescribeModelCardResponse$ModelCardName' => 'The name of the model card.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupName' => 'The name of the model group.
', 'DescribeModelPackageOutput$ModelPackageName' => 'The name of the model package being described.
', 'DescribeModelPackageOutput$ModelPackageGroupName' => 'If the model is a versioned model, the name of the model group that the versioned model belongs to.
', 'DeviceDeploymentSummary$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'DeviceDeploymentSummary$StageName' => 'The name of the stage in the edge deployment plan.
', 'DeviceDeploymentSummary$DeployedStageName' => 'The name of the deployed stage.
', 'DeviceDeploymentSummary$DeviceFleetName' => 'The name of the fleet to which the device belongs to.
', 'DeviceFleetSummary$DeviceFleetName' => 'Name of the device fleet.
', 'DeviceSummary$DeviceName' => 'The unique identifier of the device.
', 'DeviceSummary$DeviceFleetName' => 'The name of the fleet the device belongs to.
', 'EdgeDeploymentModelConfig$ModelHandle' => 'The name the device application uses to reference this model.
', 'EdgeDeploymentModelConfig$EdgePackagingJobName' => 'The edge packaging job associated with this deployment.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'EdgeDeploymentPlanSummary$DeviceFleetName' => 'The name of the device fleet used for the deployment.
', 'EdgeModel$ModelName' => 'The name of the model.
', 'EdgeModelStat$ModelName' => 'The name of the model.
', 'EdgeModelSummary$ModelName' => 'The name of the model.
', 'EdgePackagingJobSummary$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'EdgePackagingJobSummary$CompilationJobName' => 'The name of the SageMaker Neo compilation job.
', 'EdgePackagingJobSummary$ModelName' => 'The name of the model.
', 'GetDeviceFleetReportRequest$DeviceFleetName' => 'The name of the fleet.
', 'GetDeviceFleetReportResponse$DeviceFleetName' => 'The name of the fleet.
', 'GetModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group for which to get the resource policy.
', 'ListDevicesRequest$ModelName' => 'A filter that searches devices that contains this name in any of their models.
', 'ListDevicesRequest$DeviceFleetName' => 'Filter for fleets containing this name in their device fleet name.
', 'ListModelCardExportJobsRequest$ModelCardName' => 'List export jobs for the model card with the specified name.
', 'ListModelCardExportJobsRequest$ModelCardExportJobNameContains' => 'Only list model card export jobs with names that contain the specified string.
', 'ListModelCardsRequest$NameContains' => 'Only list model cards with names that contain the specified string.
', 'ListStageDevicesRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'ListStageDevicesRequest$StageName' => 'The name of the stage in the deployment.
', 'ModelCard$ModelCardName' => 'The unique name of the model card.
', 'ModelCardExportJobSummary$ModelCardExportJobName' => 'The name of the model card export job.
', 'ModelCardExportJobSummary$ModelCardName' => 'The name of the model card that the export job exports.
', 'ModelCardSummary$ModelCardName' => 'The name of the model card.
', 'ModelCardVersionSummary$ModelCardName' => 'The name of the model card.
', 'ModelDashboardModelCard$ModelCardName' => 'The name of a model card.
', 'ModelPackage$ModelPackageName' => 'The name of the model.
', 'ModelPackage$ModelPackageGroupName' => 'The model group to which the model belongs.
', 'ModelPackageGroup$ModelPackageGroupName' => 'The name of the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupName' => 'The name of the model group.
', 'ModelPackageStatusItem$Name' => 'The name of the model package for which the overall status is being reported.
', 'ModelPackageSummary$ModelPackageName' => 'The name of the model package.
', 'ModelPackageSummary$ModelPackageGroupName' => 'If the model package is a versioned model, the model group that the versioned model belongs to.
', 'ModelPackageValidationProfile$ProfileName' => 'The name of the profile for the model package.
', 'PutModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group to add a resource policy to.
', 'RegisterDevicesRequest$DeviceFleetName' => 'The name of the fleet.
', 'StartEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to start.
', 'StartEdgeDeploymentStageRequest$StageName' => 'The name of the stage to start.
', 'StopCompilationJobRequest$CompilationJobName' => 'The name of the model compilation job to stop.
', 'StopEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to stop.
', 'StopEdgeDeploymentStageRequest$StageName' => 'The name of the stage to stop.
', 'StopEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'UpdateCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to update.
', 'UpdateDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet.
', 'UpdateDevicesRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', ], ], 'EnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'EnvironmentMap$key' => NULL, ], ], 'EnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$Environment' => 'The environment variables to set in the container. For more information, see ContainerDefinition.
', 'ContainerDefinition$Environment' => 'The environment variables to set in the Docker container. Each key and value in the Environment
string to string map can have length of up to 1024. We support up to 16 entries in the map.
The environment variables to set in the Docker container. Each key and value in the Environment string-to-string map can have length of up to 1024. We support up to 16 entries in the map.
', 'InferenceComponentContainerSpecificationSummary$Environment' => 'The environment variables to set in the Docker container.
', 'ModelPackageContainerDefinition$Environment' => 'The environment variables to set in the Docker container. Each key and value in the Environment
string to string map can have length of up to 1024. We support up to 16 entries in the map.
The recommended environment variables to set in the model container for Real-Time Inference.
', ], ], 'EnvironmentParameter' => [ 'base' => 'A list of environment parameters suggested by the Amazon SageMaker Inference Recommender.
', 'refs' => [ 'EnvironmentParameters$member' => NULL, ], ], 'EnvironmentParameterRanges' => [ 'base' => 'Specifies the range of environment parameters
', 'refs' => [ 'EndpointInputConfiguration$EnvironmentParameterRanges' => 'The parameter you want to benchmark against.
', ], ], 'EnvironmentParameters' => [ 'base' => NULL, 'refs' => [ 'ModelConfiguration$EnvironmentParameters' => 'Defines the environment parameters that includes key, value types, and values.
', ], ], 'EnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'EnvironmentMap$value' => NULL, ], ], 'ExcludeFeaturesAttribute' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$ExcludeFeaturesAttribute' => 'The attributes of the input data to exclude from the analysis.
', 'EndpointInput$ExcludeFeaturesAttribute' => 'The attributes of the input data to exclude from the analysis.
', ], ], 'ExecutionRoleIdentityConfig' => [ 'base' => NULL, 'refs' => [ 'DomainSettings$ExecutionRoleIdentityConfig' => 'The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key.
', 'DomainSettingsForUpdate$ExecutionRoleIdentityConfig' => 'The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the InService
or Pending
state.
A filter that retrieves only jobs with a specific status.
', 'MonitoringExecutionSummary$MonitoringExecutionStatus' => 'The status of the monitoring job.
', ], ], 'ExitMessage' => [ 'base' => NULL, 'refs' => [ 'DescribeProcessingJobResponse$ExitMessage' => 'An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', 'ProcessingJob$ExitMessage' => 'A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', 'ProcessingJobSummary$ExitMessage' => 'An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', ], ], 'Experiment' => [ 'base' => 'The properties of an experiment as returned by the Search API.
', 'refs' => [ 'SearchRecord$Experiment' => 'The properties of an experiment.
', ], ], 'ExperimentArn' => [ 'base' => NULL, 'refs' => [ 'CreateExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'DeleteExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment that is being deleted.
', 'DescribeExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'Experiment$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'ExperimentSummary$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'UpdateExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', ], ], 'ExperimentConfig' => [ 'base' => 'Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
', 'refs' => [ 'CreateProcessingJobRequest$ExperimentConfig' => NULL, 'CreateTrainingJobRequest$ExperimentConfig' => NULL, 'CreateTransformJobRequest$ExperimentConfig' => NULL, 'DescribeProcessingJobResponse$ExperimentConfig' => 'The configuration information used to create an experiment.
', 'DescribeTrainingJobResponse$ExperimentConfig' => NULL, 'DescribeTransformJobResponse$ExperimentConfig' => NULL, 'ProcessingJob$ExperimentConfig' => NULL, 'TrainingJob$ExperimentConfig' => NULL, 'TransformJob$ExperimentConfig' => NULL, ], ], 'ExperimentDescription' => [ 'base' => NULL, 'refs' => [ 'CreateActionRequest$Description' => 'The description of the action.
', 'CreateContextRequest$Description' => 'The description of the context.
', 'CreateExperimentRequest$Description' => 'The description of the experiment.
', 'DescribeActionResponse$Description' => 'The description of the action.
', 'DescribeContextResponse$Description' => 'The description of the context.
', 'DescribeExperimentResponse$Description' => 'The description of the experiment.
', 'DescribeLineageGroupResponse$Description' => 'The description of the lineage group.
', 'Experiment$Description' => 'The description of the experiment.
', 'UpdateActionRequest$Description' => 'The new description for the action.
', 'UpdateContextRequest$Description' => 'The new description for the context.
', 'UpdateExperimentRequest$Description' => 'The description of the experiment.
', ], ], 'ExperimentEntityName' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$ActionName' => 'The name of the action.
', 'ArtifactSummary$ArtifactName' => 'The name of the artifact.
', 'AssociateTrialComponentRequest$TrialComponentName' => 'The name of the component to associated with the trial.
', 'AssociateTrialComponentRequest$TrialName' => 'The name of the trial to associate with.
', 'AssociationSummary$SourceName' => 'The name of the source.
', 'AssociationSummary$DestinationName' => 'The name of the destination.
', 'CreateActionRequest$ActionName' => 'The name of the action. Must be unique to your account in an Amazon Web Services Region.
', 'CreateArtifactRequest$ArtifactName' => 'The name of the artifact. Must be unique to your account in an Amazon Web Services Region.
', 'CreateExperimentRequest$ExperimentName' => 'The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateExperimentRequest$DisplayName' => 'The name of the experiment as displayed. The name doesn\'t need to be unique. If you don\'t specify DisplayName
, the value in ExperimentName
is displayed.
The name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateTrialComponentRequest$DisplayName' => 'The name of the component as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateTrialRequest$DisplayName' => 'The name of the trial as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the experiment to associate the trial with.
', 'DeleteActionRequest$ActionName' => 'The name of the action to delete.
', 'DeleteExperimentRequest$ExperimentName' => 'The name of the experiment to delete.
', 'DeleteTrialComponentRequest$TrialComponentName' => 'The name of the component to delete.
', 'DeleteTrialRequest$TrialName' => 'The name of the trial to delete.
', 'DescribeExperimentRequest$ExperimentName' => 'The name of the experiment to describe.
', 'DescribeExperimentResponse$ExperimentName' => 'The name of the experiment.
', 'DescribeExperimentResponse$DisplayName' => 'The name of the experiment as displayed. If DisplayName
isn\'t specified, ExperimentName
is displayed.
The name of the lineage group.
', 'DescribeLineageGroupResponse$LineageGroupName' => 'The name of the lineage group.
', 'DescribeLineageGroupResponse$DisplayName' => 'The display name of the lineage group.
', 'DescribeTrialComponentResponse$TrialComponentName' => 'The name of the trial component.
', 'DescribeTrialComponentResponse$DisplayName' => 'The name of the component as displayed. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the trial to describe.
', 'DescribeTrialResponse$TrialName' => 'The name of the trial.
', 'DescribeTrialResponse$DisplayName' => 'The name of the trial as displayed. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the experiment the trial is part of.
', 'DisassociateTrialComponentRequest$TrialComponentName' => 'The name of the component to disassociate from the trial.
', 'DisassociateTrialComponentRequest$TrialName' => 'The name of the trial to disassociate from.
', 'Experiment$ExperimentName' => 'The name of the experiment.
', 'Experiment$DisplayName' => 'The name of the experiment as displayed. If DisplayName
isn\'t specified, ExperimentName
is displayed.
The name of an existing experiment to associate with the trial component.
', 'ExperimentConfig$TrialName' => 'The name of an existing trial to associate the trial component with. If not specified, a new trial is created.
', 'ExperimentConfig$TrialComponentDisplayName' => 'The display name for the trial component. If this key isn\'t specified, the display name is the trial component name.
', 'ExperimentConfig$RunName' => 'The name of the experiment run to associate with the trial component.
', 'ExperimentSummary$ExperimentName' => 'The name of the experiment.
', 'ExperimentSummary$DisplayName' => 'The name of the experiment as displayed. If DisplayName
isn\'t specified, ExperimentName
is displayed.
The name or Amazon Resource Name (ARN) of the lineage group.
', 'LineageGroupSummary$DisplayName' => 'The display name of the lineage group summary.
', 'ListTrialComponentsRequest$ExperimentName' => 'A filter that returns only components that are part of the specified experiment. If you specify ExperimentName
, you can\'t filter by SourceArn
or TrialName
.
A filter that returns only components that are part of the specified trial. If you specify TrialName
, you can\'t filter by ExperimentName
or SourceArn
.
A filter that returns only trials that are part of the specified experiment.
', 'ListTrialsRequest$TrialComponentName' => 'A filter that returns only trials that are associated with the specified trial component.
', 'Parent$TrialName' => 'The name of the trial.
', 'Parent$ExperimentName' => 'The name of the experiment.
', 'PipelineExperimentConfig$ExperimentName' => 'The name of the experiment.
', 'PipelineExperimentConfig$TrialName' => 'The name of the trial.
', 'Trial$TrialName' => 'The name of the trial.
', 'Trial$DisplayName' => 'The name of the trial as displayed. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the experiment the trial is part of.
', 'TrialComponent$TrialComponentName' => 'The name of the trial component.
', 'TrialComponent$DisplayName' => 'The name of the component as displayed. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the experiment run.
', 'TrialComponentSimpleSummary$TrialComponentName' => 'The name of the trial component.
', 'TrialComponentSummary$TrialComponentName' => 'The name of the trial component.
', 'TrialComponentSummary$DisplayName' => 'The name of the component as displayed. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the trial.
', 'TrialSummary$DisplayName' => 'The name of the trial as displayed. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the action to update.
', 'UpdateArtifactRequest$ArtifactName' => 'The new name for the artifact.
', 'UpdateExperimentRequest$ExperimentName' => 'The name of the experiment to update.
', 'UpdateExperimentRequest$DisplayName' => 'The name of the experiment as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, ExperimentName
is displayed.
The name of the component to update.
', 'UpdateTrialComponentRequest$DisplayName' => 'The name of the component as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, TrialComponentName
is displayed.
The name of the trial to update.
', 'UpdateTrialRequest$DisplayName' => 'The name of the trial as displayed. The name doesn\'t need to be unique. If DisplayName
isn\'t specified, TrialName
is displayed.
The name of the action to describe.
', 'DescribeActionResponse$ActionName' => 'The name of the action.
', 'DescribeArtifactResponse$ArtifactName' => 'The name of the artifact.
', 'DescribeTrialComponentRequest$TrialComponentName' => 'The name of the trial component to describe.
', ], ], 'ExperimentSource' => [ 'base' => 'The source of the experiment.
', 'refs' => [ 'DescribeExperimentResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the type.
', 'Experiment$Source' => NULL, 'ExperimentSummary$ExperimentSource' => NULL, ], ], 'ExperimentSourceArn' => [ 'base' => NULL, 'refs' => [ 'ExperimentSource$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'ExperimentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListExperimentsResponse$ExperimentSummaries' => 'A list of the summaries of your experiments.
', ], ], 'ExperimentSummary' => [ 'base' => 'A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName
.
The number of seconds until the pre-signed URL expires. This value defaults to 300.
', ], ], 'Explainability' => [ 'base' => 'Contains explainability metrics for a model.
', 'refs' => [ 'ModelMetrics$Explainability' => 'Metrics that help explain a model.
', ], ], 'ExplainabilityLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$Explainability' => 'The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
', ], ], 'ExplainerConfig' => [ 'base' => 'A parameter to activate explainers.
', 'refs' => [ 'CreateEndpointConfigInput$ExplainerConfig' => 'A member of CreateEndpointConfig
that enables explainers.
The configuration parameters for an explainer.
', 'DescribeEndpointOutput$ExplainerConfig' => 'The configuration parameters for an explainer.
', ], ], 'FailStepMetadata' => [ 'base' => 'The container for the metadata for Fail step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Fail' => 'The configurations and outcomes of a Fail step execution.
', ], ], 'FailureHandlingPolicy' => [ 'base' => NULL, 'refs' => [ 'EdgeDeploymentConfig$FailureHandlingPolicy' => 'Toggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.
', ], ], 'FailureReason' => [ 'base' => NULL, 'refs' => [ 'ConflictException$Message' => NULL, 'DescribeAppResponse$FailureReason' => 'The failure reason.
', 'DescribeCompilationJobResponse$FailureReason' => 'If a model compilation job failed, the reason it failed.
', 'DescribeDomainResponse$FailureReason' => 'The failure reason.
', 'DescribeEndpointOutput$FailureReason' => 'If the status of the endpoint is Failed
, the reason why it failed.
The reason that the FeatureGroup
failed to be replicated in the OfflineStore
. This is failure can occur because:
The FeatureGroup
could not be created in the OfflineStore
.
The FeatureGroup
could not be deleted from the OfflineStore
.
The reason your flow definition failed.
', 'DescribeHubContentResponse$FailureReason' => 'The failure reason if importing hub content failed.
', 'DescribeHubResponse$FailureReason' => 'The failure reason if importing hub content failed.
', 'DescribeHyperParameterTuningJobResponse$FailureReason' => 'If the tuning job failed, the reason it failed.
', 'DescribeImageResponse$FailureReason' => 'When a create, update, or delete operation fails, the reason for the failure.
', 'DescribeImageVersionResponse$FailureReason' => 'When a create or delete operation fails, the reason for the failure.
', 'DescribeInferenceComponentOutput$FailureReason' => 'If the inference component status is Failed
, the reason for the failure.
If the job fails, provides information why the job failed.
', 'DescribeLabelingJobResponse$FailureReason' => 'If the job failed, the reason that it failed.
', 'DescribeModelCardExportJobResponse$FailureReason' => 'The failure reason if the model export job fails.
', 'DescribeMonitoringScheduleResponse$FailureReason' => 'A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
', 'DescribeNotebookInstanceOutput$FailureReason' => 'If status is Failed
, the reason it failed.
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'DescribeSpaceResponse$FailureReason' => 'The failure reason.
', 'DescribeTrainingJobResponse$FailureReason' => 'If the training job failed, the reason it failed.
', 'DescribeTransformJobResponse$FailureReason' => 'If the transform job failed, FailureReason
describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see Log Amazon SageMaker Events with Amazon CloudWatch.
The failure reason.
', 'Endpoint$FailureReason' => 'If the endpoint failed, the reason it failed.
', 'EndpointMetadata$FailureReason' => ' If the status of the endpoint is Failed
, or the status is InService
but update operation fails, this provides the reason why it failed.
The reason that the FeatureGroup
failed to be replicated in the OfflineStore
. This is failure may be due to a failure to create a FeatureGroup
in or delete a FeatureGroup
from the OfflineStore
.
The reason why the flow definition creation failed. A failure reason is returned only when the flow definition status is Failed
.
The reason that the training job failed.
', 'HyperParameterTuningJobSearchEntity$FailureReason' => 'The error that was created when a hyperparameter tuning job failed.
', 'Image$FailureReason' => 'When a create, update, or delete operation fails, the reason for the failure.
', 'ImageVersion$FailureReason' => 'When a create or delete operation fails, the reason for the failure.
', 'InferenceRecommendationsJob$FailureReason' => 'If the job fails, provides information why the job failed.
', 'LabelingJobSummary$FailureReason' => 'If the LabelingJobStatus
field is Failed
, this field contains a description of the error.
If the update wasn\'t successful, indicates the reason why it failed.
', 'ModelDashboardMonitoringSchedule$FailureReason' => 'If a monitoring job failed, provides the reason.
', 'MonitoringExecutionSummary$FailureReason' => 'Contains the reason a monitoring job failed, if it failed.
', 'MonitoringSchedule$FailureReason' => 'If the monitoring schedule failed, the reason it failed.
', 'PipelineExecutionStep$FailureReason' => 'The reason why the step failed execution. This is only returned if the step failed its execution.
', 'ProcessingJob$FailureReason' => 'A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'ProcessingJobSummary$FailureReason' => 'A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'ResourceInUse$Message' => NULL, 'ResourceLimitExceeded$Message' => NULL, 'ResourceNotFound$Message' => NULL, 'TrainingJob$FailureReason' => 'If the training job failed, the reason it failed.
', 'TransformJob$FailureReason' => 'If the transform job failed, the reason it failed.
', 'TransformJobSummary$FailureReason' => 'If the transform job failed, the reason it failed.
', ], ], 'FeatureAdditions' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureGroupRequest$FeatureAdditions' => 'Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you\'ve made a valid request. It takes some time after you\'ve made a valid request for Feature Store to update the feature group.
', ], ], 'FeatureDefinition' => [ 'base' => 'A list of features. You must include FeatureName
and FeatureType
. Valid feature FeatureType
s are Integral
, Fractional
and String
.
A list of Feature
names and types. Name
and Type
is compulsory per Feature
.
Valid feature FeatureType
s are Integral
, Fractional
and String
.
FeatureName
s cannot be any of the following: is_deleted
, write_time
, api_invocation_time
You can create up to 2,500 FeatureDefinition
s per FeatureGroup
.
A list of the Features
in the FeatureGroup
. Each feature is defined by a FeatureName
and FeatureType
.
A list of Feature
s. Each Feature
must include a FeatureName
and a FeatureType
.
Valid FeatureType
s are Integral
, Fractional
and String
.
FeatureName
s cannot be any of the following: is_deleted
, write_time
, api_invocation_time
.
You can create up to 2,500 FeatureDefinition
s per FeatureGroup
.
The description you added to describe the feature.
', 'FeatureMetadata$Description' => 'An optional description that you specify to better describe the feature.
', 'UpdateFeatureMetadataRequest$Description' => 'A description that you can write to better describe the feature.
', ], ], 'FeatureGroup' => [ 'base' => 'Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
', 'refs' => [ 'SearchRecord$FeatureGroup' => NULL, ], ], 'FeatureGroupArn' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupResponse$FeatureGroupArn' => 'The Amazon Resource Name (ARN) of the FeatureGroup
. This is a unique identifier for the feature group.
The Amazon Resource Name (ARN) of the FeatureGroup
.
The Amazon Resource Number (ARN) of the feature group that contains the feature.
', 'FeatureGroup$FeatureGroupArn' => 'The Amazon Resource Name (ARN) of a FeatureGroup
.
Unique identifier for the FeatureGroup
.
The Amazon Resource Number (ARN) of the feature group.
', 'UpdateFeatureGroupResponse$FeatureGroupArn' => 'The Amazon Resource Number (ARN) of the feature group that you\'re updating.
', ], ], 'FeatureGroupMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$MaxResults' => 'The maximum number of results returned by ListFeatureGroups
.
The name of the FeatureGroup
. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account. The name:
Must start and end with an alphanumeric character.
Can only contain alphanumeric character and hyphens. Spaces are not allowed.
The name of the FeatureGroup
you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
he name of the FeatureGroup
.
The name of the feature group that you\'ve specified.
', 'FeatureGroup$FeatureGroupName' => 'The name of the FeatureGroup
.
The name of FeatureGroup
.
The name of the feature group containing the feature.
', 'ProcessingFeatureStoreOutput$FeatureGroupName' => 'The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.
', ], ], 'FeatureGroupNameContains' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$NameContains' => 'A string that partially matches one or more FeatureGroup
s names. Filters FeatureGroup
s by name.
The name or Amazon Resource Name (ARN) of the FeatureGroup
you want described.
The name or Amazon Resource Name (ARN) of the feature group containing the feature.
', 'UpdateFeatureGroupRequest$FeatureGroupName' => 'The name or Amazon Resource Name (ARN) of the feature group that you\'re updating.
', 'UpdateFeatureMetadataRequest$FeatureGroupName' => 'The name or Amazon Resource Name (ARN) of the feature group containing the feature that you\'re updating.
', ], ], 'FeatureGroupSortBy' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$SortBy' => 'The value on which the feature group list is sorted.
', ], ], 'FeatureGroupSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$SortOrder' => 'The order in which feature groups are listed.
', ], ], 'FeatureGroupStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureGroupResponse$FeatureGroupStatus' => 'The status of the feature group.
', 'FeatureGroup$FeatureGroupStatus' => 'A FeatureGroup
status.
The status of a FeatureGroup. The status can be any of the following: Creating
, Created
, CreateFail
, Deleting
or DetailFail
.
A FeatureGroup
status. Filters by FeatureGroup
status.
A summary of feature groups.
', ], ], 'FeatureGroupSummary' => [ 'base' => 'The name, ARN, CreationTime
, FeatureGroup
values, LastUpdatedTime
and EnableOnlineStorage
status of a FeatureGroup
.
The metadata for a feature. It can either be metadata that you specify, or metadata that is updated automatically.
', 'refs' => [ 'SearchRecord$FeatureMetadata' => 'The feature metadata used to search through the features.
', ], ], 'FeatureName' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupRequest$RecordIdentifierFeatureName' => 'The name of the Feature
whose value uniquely identifies a Record
defined in the FeatureStore
. Only the latest record per identifier value will be stored in the OnlineStore
. RecordIdentifierFeatureName
must be one of feature definitions\' names.
You use the RecordIdentifierFeatureName
to access data in a FeatureStore
.
This name:
Must start and end with an alphanumeric character.
Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.
The name of the feature that stores the EventTime
of a Record
in a FeatureGroup
.
An EventTime
is a point in time when a new event occurs that corresponds to the creation or update of a Record
in a FeatureGroup
. All Records
in the FeatureGroup
must have a corresponding EventTime
.
An EventTime
can be a String
or Fractional
.
Fractional
: EventTime
feature values must be a Unix timestamp in seconds.
String
: EventTime
feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd\'T\'HH:mm:ssZ
and yyyy-MM-dd\'T\'HH:mm:ss.SSSZ
where yyyy
, MM
, and dd
represent the year, month, and day respectively and HH
, mm
, ss
, and if applicable, SSS
represent the hour, month, second and milliseconds respsectively. \'T\'
and Z
are constants.
The name of the Feature
used for RecordIdentifier
, whose value uniquely identifies a record stored in the feature store.
The name of the feature that stores the EventTime
of a Record in a FeatureGroup
.
An EventTime
is a point in time when a new event occurs that corresponds to the creation or update of a Record
in a FeatureGroup
. All Records
in the FeatureGroup
have a corresponding EventTime
.
The name of the feature.
', 'DescribeFeatureMetadataResponse$FeatureName' => 'The name of the feature that you\'ve specified.
', 'FeatureDefinition$FeatureName' => 'The name of a feature. The type must be a string. FeatureName
cannot be any of the following: is_deleted
, write_time
, api_invocation_time
.
The name of the Feature
whose value uniquely identifies a Record
defined in the FeatureGroup
FeatureDefinitions
.
The name of the feature that stores the EventTime
of a Record in a FeatureGroup
.
A EventTime
is point in time when a new event occurs that corresponds to the creation or update of a Record
in FeatureGroup
. All Records
in the FeatureGroup
must have a corresponding EventTime
.
The name of feature.
', 'UpdateFeatureMetadataRequest$FeatureName' => 'The name of the feature that you\'re updating.
', ], ], 'FeatureParameter' => [ 'base' => 'A key-value pair that you specify to describe the feature.
', 'refs' => [ 'FeatureParameterAdditions$member' => NULL, 'FeatureParameters$member' => NULL, ], ], 'FeatureParameterAdditions' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureMetadataRequest$ParameterAdditions' => 'A list of key-value pairs that you can add to better describe the feature.
', ], ], 'FeatureParameterKey' => [ 'base' => NULL, 'refs' => [ 'FeatureParameter$Key' => 'A key that must contain a value to describe the feature.
', 'FeatureParameterRemovals$member' => NULL, ], ], 'FeatureParameterRemovals' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureMetadataRequest$ParameterRemovals' => 'A list of parameter keys that you can specify to remove parameters that describe your feature.
', ], ], 'FeatureParameterValue' => [ 'base' => NULL, 'refs' => [ 'FeatureParameter$Value' => 'The value that belongs to a key.
', ], ], 'FeatureParameters' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureMetadataResponse$Parameters' => 'The key-value pairs that you added to describe the feature.
', 'FeatureMetadata$Parameters' => 'Optional key-value pairs that you specify to better describe the feature.
', ], ], 'FeatureStatus' => [ 'base' => NULL, 'refs' => [ 'DirectDeploySettings$Status' => 'Describes whether model deployment permissions are enabled or disabled in the Canvas application.
', 'DockerSettings$EnableDockerAccess' => 'Indicates whether the domain can access Docker.
', 'IdentityProviderOAuthSetting$Status' => 'Describes whether OAuth for a data source is enabled or disabled in the Canvas application.
', 'KendraSettings$Status' => 'Describes whether the document querying feature is enabled or disabled in the Canvas application.
', 'ModelRegisterSettings$Status' => 'Describes whether the integration to the model registry is enabled or disabled in the Canvas application.
', 'TimeSeriesForecastingSettings$Status' => 'Describes whether time series forecasting is enabled or disabled in the Canvas application.
', ], ], 'FeatureType' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureMetadataResponse$FeatureType' => 'The data type of the feature.
', 'FeatureDefinition$FeatureType' => 'The value type of a feature. Valid values are Integral, Fractional, or String.
', 'FeatureMetadata$FeatureType' => 'The data type of the feature.
', ], ], 'FileSource' => [ 'base' => 'Contains details regarding the file source.
', 'refs' => [ 'DriftCheckBias$ConfigFile' => 'The bias config file for a model.
', 'DriftCheckExplainability$ConfigFile' => 'The explainability config file for the model.
', ], ], 'FileSystemAccessMode' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemAccessMode' => 'The access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro
(read-only) or rw
(read-write) mode.
The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
', 'refs' => [ 'JupyterLabAppImageConfig$FileSystemConfig' => NULL, 'KernelGatewayImageConfig$FileSystemConfig' => 'The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
', ], ], 'FileSystemDataSource' => [ 'base' => 'Specifies a file system data source for a channel.
', 'refs' => [ 'DataSource$FileSystemDataSource' => 'The file system that is associated with a channel.
', ], ], 'FileSystemId' => [ 'base' => NULL, 'refs' => [ 'EFSFileSystem$FileSystemId' => 'The ID of your Amazon EFS file system.
', 'EFSFileSystemConfig$FileSystemId' => 'The ID of your Amazon EFS file system.
', 'FileSystemDataSource$FileSystemId' => 'The file system id.
', ], ], 'FileSystemPath' => [ 'base' => NULL, 'refs' => [ 'EFSFileSystemConfig$FileSystemPath' => 'The path to the file system directory that is accessible in Amazon SageMaker Studio. Permitted users can access only this directory and below.
', ], ], 'FileSystemType' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemType' => 'The file system type.
', ], ], 'FillingTransformationMap' => [ 'base' => NULL, 'refs' => [ 'FillingTransformations$value' => NULL, ], ], 'FillingTransformationValue' => [ 'base' => NULL, 'refs' => [ 'FillingTransformationMap$value' => NULL, ], ], 'FillingTransformations' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesTransformations$Filling' => 'A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.
The supported filling methods and their corresponding options are:
frontfill
: none
(Supported only for target column)
middlefill
: zero
, value
, median
, mean
, min
, max
backfill
: zero
, value
, median
, mean
, min
, max
futurefill
: zero
, value
, median
, mean
, min
, max
To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example "backfill" : "value"
), and define the filling value in an additional parameter prefixed with "_value". For example, to set backfill
to a value of 2
, you must include two parameters: "backfill": "value"
and "backfill_value":"2"
.
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value
, but not an Operator
, SageMaker uses the equals operator.
In search, there are several property types:
To define a metric filter, enter a value using the form "Metrics.<name>"
, where <name>
is a metric name. For example, the following filter searches for training jobs with an "accuracy"
metric greater than "0.9"
:
{
"Name": "Metrics.accuracy",
"Operator": "GreaterThan",
"Value": "0.9"
}
To define a hyperparameter filter, enter a value with the form "HyperParameters.<name>"
. Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value
is also a decimal value. If the specified Value
is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a "learning_rate"
hyperparameter that is less than "0.5"
:
{
"Name": "HyperParameters.learning_rate",
"Operator": "LessThan",
"Value": "0.5"
}
To define a tag filter, enter a value with the form Tags.<key>
.
A list of filters. Each filter acts on a property. Filters must contain at least one Filters
value. For example, a NestedFilters
call might include a filter on the PropertyName
parameter of the InputDataConfig
property: InputDataConfig.DataSource.S3DataSource.S3Uri
.
A list of filter objects.
', ], ], 'FilterValue' => [ 'base' => NULL, 'refs' => [ 'Filter$Value' => 'A value used with Name
and Operator
to determine which resources satisfy the filter\'s condition. For numerical properties, Value
must be an integer or floating-point decimal. For timestamp properties, Value
must be an ISO 8601 date-time string of the following format: YYYY-mm-dd\'T\'HH:MM:SS
.
The best candidate result from an AutoML training job.
', 'refs' => [ 'AutoMLCandidate$FinalAutoMLJobObjectiveMetric' => NULL, ], ], 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'base' => 'Shows the latest objective metric emitted by a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective
parameter of HyperParameterTuningJobConfig.
The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.
', ], ], 'FinalMetricDataList' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$FinalMetricDataList' => 'A collection of MetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
', ], ], 'FlatInvocations' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobStoppingConditions$FlatInvocations' => 'Stops a load test when the number of invocations (TPS) peaks and flattens, which means that the instance has reached capacity. The default value is Stop
. If you want the load test to continue after invocations have flattened, set the value to Continue
.
The value of the metric.
', 'MetricDatum$Value' => 'The value of the metric.
', 'RecommendationMetrics$CostPerHour' => 'Defines the cost per hour for the instance.
', 'RecommendationMetrics$CostPerInference' => 'Defines the cost per inference for the instance .
', ], ], 'FlowDefinitionArn' => [ 'base' => NULL, 'refs' => [ 'CreateFlowDefinitionResponse$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow definition you create.
', 'DescribeFlowDefinitionResponse$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow defintion.
', 'FlowDefinitionSummary$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow definition.
', ], ], 'FlowDefinitionName' => [ 'base' => NULL, 'refs' => [ 'CreateFlowDefinitionRequest$FlowDefinitionName' => 'The name of your flow definition.
', 'DeleteFlowDefinitionRequest$FlowDefinitionName' => 'The name of the flow definition you are deleting.
', 'DescribeFlowDefinitionRequest$FlowDefinitionName' => 'The name of the flow definition.
', 'DescribeFlowDefinitionResponse$FlowDefinitionName' => 'The Amazon Resource Name (ARN) of the flow definition.
', 'FlowDefinitionSummary$FlowDefinitionName' => 'The name of the flow definition.
', ], ], 'FlowDefinitionOutputConfig' => [ 'base' => 'Contains information about where human output will be stored.
', 'refs' => [ 'CreateFlowDefinitionRequest$OutputConfig' => 'An object containing information about where the human review results will be uploaded.
', 'DescribeFlowDefinitionResponse$OutputConfig' => 'An object containing information about the output file.
', ], ], 'FlowDefinitionStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeFlowDefinitionResponse$FlowDefinitionStatus' => 'The status of the flow definition. Valid values are listed below.
', 'FlowDefinitionSummary$FlowDefinitionStatus' => 'The status of the flow definition. Valid values:
', ], ], 'FlowDefinitionSummaries' => [ 'base' => NULL, 'refs' => [ 'ListFlowDefinitionsResponse$FlowDefinitionSummaries' => 'An array of objects describing the flow definitions.
', ], ], 'FlowDefinitionSummary' => [ 'base' => 'Contains summary information about the flow definition.
', 'refs' => [ 'FlowDefinitionSummaries$member' => NULL, ], ], 'FlowDefinitionTaskAvailabilityLifetimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskAvailabilityLifetimeInSeconds' => 'The length of time that a task remains available for review by human workers.
', ], ], 'FlowDefinitionTaskCount' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskCount' => 'The number of distinct workers who will perform the same task on each object. For example, if TaskCount
is set to 3
for an image classification labeling job, three workers will classify each input image. Increasing TaskCount
can improve label accuracy.
A description for the human worker task.
', ], ], 'FlowDefinitionTaskKeyword' => [ 'base' => NULL, 'refs' => [ 'FlowDefinitionTaskKeywords$member' => NULL, ], ], 'FlowDefinitionTaskKeywords' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskKeywords' => 'Keywords used to describe the task so that workers can discover the task.
', ], ], 'FlowDefinitionTaskTimeLimitInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskTimeLimitInSeconds' => 'The amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).
', ], ], 'FlowDefinitionTaskTitle' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskTitle' => 'A title for the human worker task.
', ], ], 'ForecastFrequency' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$ForecastFrequency' => 'The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, 1D
indicates every day and 15min
indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of 1H
instead of 60min
.
The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.
', ], ], 'ForecastQuantile' => [ 'base' => NULL, 'refs' => [ 'ForecastQuantiles$member' => NULL, ], ], 'ForecastQuantiles' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$ForecastQuantiles' => 'The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01
(p1) to 0.99
(p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles
is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.
Identifies the framework in which the model was trained. For example: TENSORFLOW.
', ], ], 'FrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'InputConfig$FrameworkVersion' => 'Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
For information about framework versions supported for cloud targets and edge devices, see Cloud Supported Instance Types and Frameworks and Edge Supported Frameworks.
', ], ], 'GenerateCandidateDefinitionsOnly' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobRequest$GenerateCandidateDefinitionsOnly' => 'Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
', 'DescribeAutoMLJobResponse$GenerateCandidateDefinitionsOnly' => 'Indicates whether the output for an AutoML job generates candidate definitions only.
', 'TabularJobConfig$GenerateCandidateDefinitionsOnly' => 'Generates possible candidates without training the models. A model candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
', ], ], 'GetDeviceFleetReportRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetDeviceFleetReportResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetLineageGroupPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetLineageGroupPolicyResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetModelPackageGroupPolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'GetModelPackageGroupPolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetSagemakerServicecatalogPortfolioStatusInput' => [ 'base' => NULL, 'refs' => [], ], 'GetSagemakerServicecatalogPortfolioStatusOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetScalingConfigurationRecommendationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetScalingConfigurationRecommendationResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetSearchSuggestionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetSearchSuggestionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'Gid' => [ 'base' => NULL, 'refs' => [ 'CustomPosixUserConfig$Gid' => 'The POSIX group ID.
', ], ], 'GitConfig' => [ 'base' => 'Specifies configuration details for a Git repository in your Amazon Web Services account.
', 'refs' => [ 'CodeRepositorySummary$GitConfig' => 'Configuration details for the Git repository, including the URL where it is located and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
', 'CreateCodeRepositoryInput$GitConfig' => 'Specifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.
', 'DescribeCodeRepositoryOutput$GitConfig' => 'Configuration details about the repository, including the URL where the repository is located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
', ], ], 'GitConfigForUpdate' => [ 'base' => 'Specifies configuration details for a Git repository when the repository is updated.
', 'refs' => [ 'UpdateCodeRepositoryInput$GitConfig' => 'The configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of AWSCURRENT
and must be in the following format:
{"username": UserName, "password": Password}
The URL where the Git repository is located.
', ], ], 'Group' => [ 'base' => NULL, 'refs' => [ 'Groups$member' => NULL, ], ], 'GroupingAttributeName' => [ 'base' => NULL, 'refs' => [ 'GroupingAttributeNames$member' => NULL, ], ], 'GroupingAttributeNames' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$GroupingAttributeNames' => 'A set of columns names that can be grouped with the item identifier column to create a composite key for which a target value is predicted.
', ], ], 'Groups' => [ 'base' => NULL, 'refs' => [ 'OidcMemberDefinition$Groups' => 'A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.
', ], ], 'HolidayConfig' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$HolidayConfig' => 'The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
', ], ], 'HolidayConfigAttributes' => [ 'base' => 'Stores the holiday featurization attributes applicable to each item of time-series datasets during the training of a forecasting model. This allows the model to identify patterns associated with specific holidays.
', 'refs' => [ 'HolidayConfig$member' => NULL, ], ], 'HookParameters' => [ 'base' => NULL, 'refs' => [ 'DebugHookConfig$HookParameters' => 'Configuration information for the Amazon SageMaker Debugger hook parameters.
', ], ], 'Horovod' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$Horovod' => 'Indicates Horovod compatibility.
', 'DescribeImageVersionResponse$Horovod' => 'Indicates Horovod compatibility.
', 'UpdateImageVersionRequest$Horovod' => 'Indicates Horovod compatibility.
', ], ], 'HubArn' => [ 'base' => NULL, 'refs' => [ 'CreateHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'DescribeHubContentResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub that contains the content.
', 'DescribeHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'HubInfo$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'ImportHubContentResponse$HubArn' => 'The ARN of the hub that the content was imported into.
', 'UpdateHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the updated hub.
', ], ], 'HubContentArn' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentArn' => 'The Amazon Resource Name (ARN) of the hub content.
', 'HubContentInfo$HubContentArn' => 'The Amazon Resource Name (ARN) of the hub content.
', 'ImportHubContentResponse$HubContentArn' => 'The ARN of the hub content that was imported.
', ], ], 'HubContentDependency' => [ 'base' => 'Any dependencies related to hub content, such as scripts, model artifacts, datasets, or notebooks.
', 'refs' => [ 'HubContentDependencyList$member' => NULL, ], ], 'HubContentDependencyList' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDependencies' => 'The location of any dependencies that the hub content has, such as scripts, model artifacts, datasets, or notebooks.
', ], ], 'HubContentDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDescription' => 'A description of the hub content.
', 'HubContentInfo$HubContentDescription' => 'A description of the hub content.
', 'ImportHubContentRequest$HubContentDescription' => 'A description of the hub content to import.
', ], ], 'HubContentDisplayName' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDisplayName' => 'The display name of the hub content.
', 'HubContentInfo$HubContentDisplayName' => 'The display name of the hub content.
', 'ImportHubContentRequest$HubContentDisplayName' => 'The display name of the hub content to import.
', ], ], 'HubContentDocument' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDocument' => 'The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
', 'ImportHubContentRequest$HubContentDocument' => 'The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
', ], ], 'HubContentInfo' => [ 'base' => 'Information about hub content.
', 'refs' => [ 'HubContentInfoList$member' => NULL, ], ], 'HubContentInfoList' => [ 'base' => NULL, 'refs' => [ 'ListHubContentVersionsResponse$HubContentSummaries' => 'The summaries of the listed hub content versions.
', 'ListHubContentsResponse$HubContentSummaries' => 'The summaries of the listed hub content.
', ], ], 'HubContentMarkdown' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentMarkdown' => 'A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
', 'ImportHubContentRequest$HubContentMarkdown' => 'A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
', ], ], 'HubContentName' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentName' => 'The name of the content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentName' => 'The name of the content to describe.
', 'DescribeHubContentResponse$HubContentName' => 'The name of the hub content.
', 'HubContentInfo$HubContentName' => 'The name of the hub content.
', 'ImportHubContentRequest$HubContentName' => 'The name of the hub content to import.
', 'ListHubContentVersionsRequest$HubContentName' => 'The name of the hub content.
', ], ], 'HubContentSearchKeywordList' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentSearchKeywords' => 'The searchable keywords for the hub content.
', 'HubContentInfo$HubContentSearchKeywords' => 'The searchable keywords for the hub content.
', 'ImportHubContentRequest$HubContentSearchKeywords' => 'The searchable keywords of the hub content.
', ], ], 'HubContentSortBy' => [ 'base' => NULL, 'refs' => [ 'ListHubContentVersionsRequest$SortBy' => 'Sort hub content versions by either name or creation time.
', 'ListHubContentsRequest$SortBy' => 'Sort hub content versions by either name or creation time.
', ], ], 'HubContentStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentStatus' => 'The status of the hub content.
', 'HubContentInfo$HubContentStatus' => 'The status of the hub content.
', ], ], 'HubContentType' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentType' => 'The type of content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentType' => 'The type of content in the hub.
', 'DescribeHubContentResponse$HubContentType' => 'The type of hub content.
', 'HubContentInfo$HubContentType' => 'The type of hub content.
', 'ImportHubContentRequest$HubContentType' => 'The type of hub content to import.
', 'ListHubContentVersionsRequest$HubContentType' => 'The type of hub content to list versions of.
', 'ListHubContentsRequest$HubContentType' => 'The type of hub content to list.
', ], ], 'HubContentVersion' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentVersion' => 'The version of the content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentVersion' => 'The version of the content to describe.
', 'DescribeHubContentResponse$HubContentVersion' => 'The version of the hub content.
', 'HubContentInfo$HubContentVersion' => 'The version of the hub content.
', 'ImportHubContentRequest$HubContentVersion' => 'The version of the hub content to import.
', 'ListHubContentVersionsRequest$MinVersion' => 'The lower bound of the hub content versions to list.
', ], ], 'HubDescription' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubDescription' => 'A description of the hub.
', 'DescribeHubResponse$HubDescription' => 'A description of the hub.
', 'HubInfo$HubDescription' => 'A description of the hub.
', 'UpdateHubRequest$HubDescription' => 'A description of the updated hub.
', ], ], 'HubDisplayName' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubDisplayName' => 'The display name of the hub.
', 'DescribeHubResponse$HubDisplayName' => 'The display name of the hub.
', 'HubInfo$HubDisplayName' => 'The display name of the hub.
', 'UpdateHubRequest$HubDisplayName' => 'The display name of the hub.
', ], ], 'HubInfo' => [ 'base' => 'Information about a hub.
', 'refs' => [ 'HubInfoList$member' => NULL, ], ], 'HubInfoList' => [ 'base' => NULL, 'refs' => [ 'ListHubsResponse$HubSummaries' => 'The summaries of the listed hubs.
', ], ], 'HubName' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubName' => 'The name of the hub to create.
', 'DeleteHubContentRequest$HubName' => 'The name of the hub that you want to delete content in.
', 'DeleteHubRequest$HubName' => 'The name of the hub to delete.
', 'DescribeHubContentRequest$HubName' => 'The name of the hub that contains the content to describe.
', 'DescribeHubContentResponse$HubName' => 'The name of the hub that contains the content.
', 'DescribeHubRequest$HubName' => 'The name of the hub to describe.
', 'DescribeHubResponse$HubName' => 'The name of the hub.
', 'HubInfo$HubName' => 'The name of the hub.
', 'ImportHubContentRequest$HubName' => 'The name of the hub to import content into.
', 'ListHubContentVersionsRequest$HubName' => 'The name of the hub to list the content versions of.
', 'ListHubContentsRequest$HubName' => 'The name of the hub to list the contents of.
', 'UpdateHubRequest$HubName' => 'The name of the hub to update.
', ], ], 'HubS3StorageConfig' => [ 'base' => 'The Amazon S3 storage configuration of a hub.
', 'refs' => [ 'CreateHubRequest$S3StorageConfig' => 'The Amazon S3 storage configuration for the hub.
', 'DescribeHubResponse$S3StorageConfig' => 'The Amazon S3 storage configuration for the hub.
', ], ], 'HubSearchKeyword' => [ 'base' => NULL, 'refs' => [ 'HubContentSearchKeywordList$member' => NULL, 'HubSearchKeywordList$member' => NULL, ], ], 'HubSearchKeywordList' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'DescribeHubResponse$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'HubInfo$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'UpdateHubRequest$HubSearchKeywords' => 'The searchable keywords for the hub.
', ], ], 'HubSortBy' => [ 'base' => NULL, 'refs' => [ 'ListHubsRequest$SortBy' => 'Sort hubs by either name or creation time.
', ], ], 'HubStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHubResponse$HubStatus' => 'The status of the hub.
', 'HubInfo$HubStatus' => 'The status of the hub.
', ], ], 'HumanLoopActivationConditions' => [ 'base' => NULL, 'refs' => [ 'HumanLoopActivationConditionsConfig$HumanLoopActivationConditions' => 'JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker Developer Guide.
', ], ], 'HumanLoopActivationConditionsConfig' => [ 'base' => 'Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required format of activation conditions.
', 'refs' => [ 'HumanLoopActivationConfig$HumanLoopActivationConditionsConfig' => 'Container structure for defining under what conditions SageMaker creates a human loop.
', ], ], 'HumanLoopActivationConfig' => [ 'base' => 'Provides information about how and under what conditions SageMaker creates a human loop. If HumanLoopActivationConfig
is not given, then all requests go to humans.
An object containing information about the events that trigger a human workflow.
', 'DescribeFlowDefinitionResponse$HumanLoopActivationConfig' => 'An object containing information about what triggers a human review workflow.
', ], ], 'HumanLoopConfig' => [ 'base' => 'Describes the work to be performed by human workers.
', 'refs' => [ 'CreateFlowDefinitionRequest$HumanLoopConfig' => 'An object containing information about the tasks the human reviewers will perform.
', 'DescribeFlowDefinitionResponse$HumanLoopConfig' => 'An object containing information about who works on the task, the workforce task price, and other task details.
', ], ], 'HumanLoopRequestSource' => [ 'base' => 'Container for configuring the source of human task requests.
', 'refs' => [ 'CreateFlowDefinitionRequest$HumanLoopRequestSource' => 'Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
', 'DescribeFlowDefinitionResponse$HumanLoopRequestSource' => 'Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
', ], ], 'HumanTaskConfig' => [ 'base' => 'Information required for human workers to complete a labeling task.
', 'refs' => [ 'CreateLabelingJobRequest$HumanTaskConfig' => 'Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).
', 'DescribeLabelingJobResponse$HumanTaskConfig' => 'Configuration information required for human workers to complete a labeling task.
', ], ], 'HumanTaskUiArn' => [ 'base' => NULL, 'refs' => [ 'CreateHumanTaskUiResponse$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human review workflow user interface you create.
', 'DescribeHumanTaskUiResponse$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface (worker task template).
', 'HumanLoopConfig$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface.
You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.
To learn how to create a custom HTML template, see Create Custom Worker Task Template.
To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see Create and Delete a Worker Task Templates.
', 'HumanTaskUiSummary$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface.
', 'RenderUiTemplateRequest$HumanTaskUiArn' => 'The HumanTaskUiArn
of the worker UI that you want to render. Do not provide a HumanTaskUiArn
if you use the UiTemplate
parameter.
See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
', 'UiConfig$HumanTaskUiArn' => 'The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace aws-region
with the Amazon Web Services Region you are creating your labeling job in. For example, replace aws-region
with us-west-1
if you create a labeling job in US West (N. California).
Named Entity Recognition
Use the following HumanTaskUiArn
for named entity recognition labeling jobs:
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
3D Point Cloud HumanTaskUiArns
Use this HumanTaskUiArn
for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn
for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn
for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArns
Use this HumanTaskUiArn
for video frame object detection and video frame object detection adjustment labeling jobs.
arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this HumanTaskUiArn
for video frame object tracking and video frame object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
The name of the user interface you are creating.
', 'DeleteHumanTaskUiRequest$HumanTaskUiName' => 'The name of the human task user interface (work task template) you want to delete.
', 'DescribeHumanTaskUiRequest$HumanTaskUiName' => 'The name of the human task user interface (worker task template) you want information about.
', 'DescribeHumanTaskUiResponse$HumanTaskUiName' => 'The name of the human task user interface (worker task template).
', 'HumanTaskUiSummary$HumanTaskUiName' => 'The name of the human task user interface.
', ], ], 'HumanTaskUiStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHumanTaskUiResponse$HumanTaskUiStatus' => 'The status of the human task user interface (worker task template). Valid values are listed below.
', ], ], 'HumanTaskUiSummaries' => [ 'base' => NULL, 'refs' => [ 'ListHumanTaskUisResponse$HumanTaskUiSummaries' => 'An array of objects describing the human task user interfaces.
', ], ], 'HumanTaskUiSummary' => [ 'base' => 'Container for human task user interface information.
', 'refs' => [ 'HumanTaskUiSummaries$member' => NULL, ], ], 'HyperParameterAlgorithmSpecification' => [ 'base' => 'Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
', 'refs' => [ 'HyperParameterTrainingJobDefinition$AlgorithmSpecification' => 'The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
', ], ], 'HyperParameterKey' => [ 'base' => NULL, 'refs' => [ 'HyperParameters$key' => NULL, ], ], 'HyperParameterScalingType' => [ 'base' => NULL, 'refs' => [ 'ContinuousParameterRange$ScalingType' => 'The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.
Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.
The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Defines a hyperparameter to be used by an algorithm.
', 'refs' => [ 'HyperParameterSpecifications$member' => NULL, ], ], 'HyperParameterSpecifications' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$SupportedHyperParameters' => 'A list of the HyperParameterSpecification
objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
Defines the training jobs launched by a hyperparameter tuning job.
', 'refs' => [ 'CreateHyperParameterTuningJobRequest$TrainingJobDefinition' => 'The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
', 'DescribeHyperParameterTuningJobResponse$TrainingJobDefinition' => 'The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.
', 'HyperParameterTrainingJobDefinitions$member' => NULL, 'HyperParameterTuningJobSearchEntity$TrainingJobDefinition' => NULL, ], ], 'HyperParameterTrainingJobDefinitionName' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobDefinition$DefinitionName' => 'The job definition name.
', 'HyperParameterTrainingJobSummary$TrainingJobDefinitionName' => 'The training job definition name.
', ], ], 'HyperParameterTrainingJobDefinitions' => [ 'base' => NULL, 'refs' => [ 'CreateHyperParameterTuningJobRequest$TrainingJobDefinitions' => 'A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
', 'DescribeHyperParameterTuningJobResponse$TrainingJobDefinitions' => 'A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
', 'HyperParameterTuningJobSearchEntity$TrainingJobDefinitions' => 'The job definitions included in a hyperparameter tuning job.
', ], ], 'HyperParameterTrainingJobEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobEnvironmentMap$key' => NULL, ], ], 'HyperParameterTrainingJobEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobDefinition$Environment' => 'An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.
The maximum number of items specified for Map Entries
refers to the maximum number of environment variables for each TrainingJobDefinition
and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can\'t exceed the maximum number specified.
A list of TrainingJobSummary objects that describe the training jobs that the ListTrainingJobsForHyperParameterTuningJob
request returned.
The container for the summary information about a training job.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$BestTrainingJob' => 'A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.
', 'DescribeHyperParameterTuningJobResponse$OverallBestTrainingJob' => 'If the hyperparameter tuning job is an warm start tuning job with a WarmStartType
of IDENTICAL_DATA_AND_ALGORITHM
, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.
The strategy that determines the order of preference for resources specified in InstanceConfigs
used in hyperparameter optimization.
The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These resources include compute instances and storage volumes. Specify one or more compute instance configurations and allocation strategies to select resources (optional).
', 'refs' => [ 'HyperParameterTuningInstanceConfigs$member' => NULL, ], ], 'HyperParameterTuningInstanceConfigs' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningResourceConfig$InstanceConfigs' => 'A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The AllocationStrategy
controls the order in which multiple configurations provided in InstanceConfigs
are used.
If you only want to use a single instance configuration inside the HyperParameterTuningResourceConfig
API, do not provide a value for InstanceConfigs
. Instead, use InstanceType
, VolumeSizeInGB
and InstanceCount
. If you use InstanceConfigs
, do not provide values for InstanceType
, VolumeSizeInGB
or InstanceCount
.
The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of the tuning job.
', 'DescribeTrainingJobResponse$TuningJobArn' => 'The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of the tuning job.
', 'TrainingJob$TuningJobArn' => 'The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
', 'TuningJobStepMetaData$Arn' => 'The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
', ], ], 'HyperParameterTuningJobCompletionDetails' => [ 'base' => 'A structure that contains runtime information about both current and completed hyperparameter tuning jobs.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$TuningJobCompletionDetails' => 'Tuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.
', 'HyperParameterTuningJobSearchEntity$TuningJobCompletionDetails' => 'Information about either a current or completed hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobConfig' => [ 'base' => 'Configures a hyperparameter tuning job.
', 'refs' => [ 'CreateHyperParameterTuningJobRequest$HyperParameterTuningJobConfig' => 'The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobConfig' => 'The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobConfig' => NULL, ], ], 'HyperParameterTuningJobConsumedResources' => [ 'base' => 'The total resources consumed by your hyperparameter tuning job.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$ConsumedResources' => NULL, 'HyperParameterTuningJobSearchEntity$ConsumedResources' => 'The total amount of resources consumed by a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobName' => [ 'base' => NULL, 'refs' => [ 'CreateHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
', 'DeleteHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job that you want to delete.
', 'DescribeHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job.
', 'HyperParameterTrainingJobSummary$TuningJobName' => 'The HyperParameter tuning job that launched the training job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobName' => 'The name of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobName' => 'The name of the tuning job.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job whose training jobs you want to list.
', 'ParentHyperParameterTuningJob$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
', 'StopHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job to stop.
', ], ], 'HyperParameterTuningJobObjective' => [ 'base' => 'Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type
parameter. If you want to define a custom objective metric, see Define metrics and environment variables.
The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
', 'HyperParameterTuningJobObjectives$member' => NULL, ], ], 'HyperParameterTuningJobObjectiveType' => [ 'base' => NULL, 'refs' => [ 'FinalHyperParameterTuningJobObjectiveMetric$Type' => 'Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
', 'HyperParameterTuningJobObjective$Type' => 'Whether to minimize or maximize the objective metric.
', ], ], 'HyperParameterTuningJobObjectives' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$SupportedTuningJobObjectiveMetrics' => 'A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobSearchEntity' => [ 'base' => 'An entity returned by the SearchRecord API containing the properties of a hyperparameter tuning job.
', 'refs' => [ 'SearchRecord$HyperParameterTuningJob' => 'The properties of a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListHyperParameterTuningJobsRequest$SortBy' => 'The field to sort results by. The default is Name
.
The status of the tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobStatus' => 'The status of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobStatus' => 'The status of the tuning job.
', 'ListHyperParameterTuningJobsRequest$StatusEquals' => 'A filter that returns only tuning jobs with the specified status.
', ], ], 'HyperParameterTuningJobStrategyConfig' => [ 'base' => 'The configuration for a training job launched by a hyperparameter tuning job. Choose Bayesian
for Bayesian optimization, and Random
for random search optimization. For more advanced use cases, use Hyperband
, which evaluates objective metrics for training jobs after every epoch. For more information about strategies, see How Hyperparameter Tuning Works.
The configuration for the Hyperband
optimization strategy. This parameter should be provided only if Hyperband
is selected as the strategy for HyperParameterTuningJobConfig
.
The strategy hyperparameter tuning uses to find the best combination of hyperparameters for your model.
', 'refs' => [ 'HyperParameterTuningJobConfig$Strategy' => 'Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.
', 'HyperParameterTuningJobSummary$Strategy' => 'Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to evaluate at each iteration.
', ], ], 'HyperParameterTuningJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListHyperParameterTuningJobsResponse$HyperParameterTuningJobSummaries' => 'A list of HyperParameterTuningJobSummary objects that describe the tuning jobs that the ListHyperParameterTuningJobs
request returned.
Provides summary information about a hyperparameter tuning job.
', 'refs' => [ 'HyperParameterTuningJobSummaries$member' => NULL, ], ], 'HyperParameterTuningJobWarmStartConfig' => [ 'base' => 'Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM
as the WarmStartType
value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
', 'HyperParameterTuningJobSearchEntity$WarmStartConfig' => NULL, ], ], 'HyperParameterTuningJobWarmStartType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningJobWarmStartConfig$WarmStartType' => 'Specifies one of the following:
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The maximum time in seconds that a hyperparameter tuning job can run.
', ], ], 'HyperParameterTuningResourceConfig' => [ 'base' => 'The configuration of resources, including compute instances and storage volumes for use in training jobs launched by hyperparameter tuning jobs. HyperParameterTuningResourceConfig
is similar to ResourceConfig
, but has the additional InstanceConfigs
and AllocationStrategy
fields to allow for flexible instance management. Specify one or more instance types, count, and the allocation strategy for instance selection.
HyperParameterTuningResourceConfig
supports the capabilities of ResourceConfig
with the exception of KeepAlivePeriodInSeconds
. Hyperparameter tuning jobs use warm pools by default, which reuse clusters between training jobs.
The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File
for TrainingInputMode
in the AlgorithmSpecification
parameter to additionally store training data in the storage volume (optional).
The default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.
', 'HyperParameters$value' => NULL, ], ], 'HyperParameters' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$HyperParameters' => 'Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint
.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Algorithm-specific parameters.
', 'HyperParameterTrainingJobDefinition$StaticHyperParameters' => 'Specifies the values of hyperparameters that do not change for the tuning job.
', 'HyperParameterTrainingJobSummary$TunedHyperParameters' => 'A list of the hyperparameters for which you specified ranges to search.
', 'TrainingJob$HyperParameters' => 'Algorithm-specific parameters.
', 'TrainingJobDefinition$HyperParameters' => 'The hyperparameters used for the training job.
', ], ], 'HyperbandStrategyConfig' => [ 'base' => 'The configuration for Hyperband
, a multi-fidelity based hyperparameter tuning strategy. Hyperband
uses the final and intermediate results of a training job to dynamically allocate resources to utilized hyperparameter configurations while automatically stopping under-performing configurations. This parameter should be provided only if Hyperband
is selected as the StrategyConfig
under the HyperParameterTuningJobConfig
API.
The configuration for the object that specifies the Hyperband
strategy. This parameter is only supported for the Hyperband
selection for Strategy
within the HyperParameterTuningJobConfig
API.
The maximum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. Once a job reaches the MaxResource
value, it is stopped. If a value for MaxResource
is not provided, and Hyperband
is selected as the hyperparameter tuning strategy, HyperbandTrainingJ
attempts to infer MaxResource
from the following keys (if present) in StaticsHyperParameters:
epochs
numepochs
n-epochs
n_epochs
num_epochs
If HyperbandStrategyConfig
is unable to infer a value for MaxResource
, it generates a validation error. The maximum value is 20,000 epochs. All metrics that correspond to an objective metric are used to derive early stopping decisions. For distributive training jobs, ensure that duplicate metrics are not printed in the logs across the individual nodes in a training job. If multiple nodes are publishing duplicate or incorrect metrics, training jobs may make an incorrect stopping decision and stop the job prematurely.
The minimum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. If the value for MinResource
has not been reached, the training job is not stopped by Hyperband
.
The IAM Identity details associated with the user. These details are associated with model package groups, model packages and project entities only.
', 'refs' => [ 'UserContext$IamIdentity' => 'The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
', ], ], 'IdempotencyToken' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'DeletePipelineRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'RetryPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', 'SendPipelineExecutionStepFailureRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'SendPipelineExecutionStepSuccessRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'StartPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', 'StopPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', ], ], 'IdentityProviderOAuthSetting' => [ 'base' => 'The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external data source, such as Snowflake.
', 'refs' => [ 'IdentityProviderOAuthSettings$member' => NULL, ], ], 'IdentityProviderOAuthSettings' => [ 'base' => NULL, 'refs' => [ 'CanvasAppSettings$IdentityProviderOAuthSettings' => 'The settings for connecting to an external data source with OAuth.
', ], ], 'Image' => [ 'base' => 'A SageMaker image. A SageMaker image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker ImageVersion
.
The ARN of the image.
', 'DescribeImageResponse$ImageArn' => 'The ARN of the image.
', 'DescribeImageVersionResponse$ImageArn' => 'The ARN of the image the version is based on.
', 'Image$ImageArn' => 'The ARN of the image.
', 'ImageVersion$ImageArn' => 'The ARN of the image the version is based on.
', 'ResourceSpec$SageMakerImageArn' => 'The ARN of the SageMaker image that the image version belongs to.
', 'UpdateImageResponse$ImageArn' => 'The ARN of the image.
', ], ], 'ImageBaseImage' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$BaseImage' => 'The registry path of the container image to use as the starting point for this version. The path is an Amazon Elastic Container Registry (ECR) URI in the following format:
<acct-id>.dkr.ecr.<region>.amazonaws.com/<repo-name[:tag] or [@digest]>
The registry path of the container image on which this image version is based.
', ], ], 'ImageClassificationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the image classification problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$ImageClassificationJobConfig' => 'Settings used to configure an AutoML job V2 for the image classification problem type.
', ], ], 'ImageConfig' => [ 'base' => 'Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
', 'refs' => [ 'ContainerDefinition$ImageConfig' => 'Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The registry path of the container image that contains this image version.
', ], ], 'ImageDeleteProperty' => [ 'base' => NULL, 'refs' => [ 'ImageDeletePropertyList$member' => NULL, ], ], 'ImageDeletePropertyList' => [ 'base' => NULL, 'refs' => [ 'UpdateImageRequest$DeleteProperties' => 'A list of properties to delete. Only the Description
and DisplayName
properties can be deleted.
The description of the image.
', 'DescribeImageResponse$Description' => 'The description of the image.
', 'Image$Description' => 'The description of the image.
', 'UpdateImageRequest$Description' => 'The new description for the image.
', ], ], 'ImageDigest' => [ 'base' => NULL, 'refs' => [ 'ModelPackageContainerDefinition$ImageDigest' => 'An MD5 hash of the training algorithm that identifies the Docker image used for training.
', 'TrainingSpecification$TrainingImageDigest' => 'An MD5 hash of the training algorithm that identifies the Docker image used for training.
', ], ], 'ImageDisplayName' => [ 'base' => NULL, 'refs' => [ 'CreateImageRequest$DisplayName' => 'The display name of the image. If not provided, ImageName
is displayed.
The name of the image as displayed.
', 'Image$DisplayName' => 'The name of the image as displayed.
', 'UpdateImageRequest$DisplayName' => 'The new display name for the image.
', ], ], 'ImageName' => [ 'base' => NULL, 'refs' => [ 'CreateImageRequest$ImageName' => 'The name of the image. Must be unique to your account.
', 'CreateImageVersionRequest$ImageName' => 'The ImageName
of the Image
to create a version of.
The name of the CustomImage. Must be unique to your account.
', 'DeleteImageRequest$ImageName' => 'The name of the image to delete.
', 'DeleteImageVersionRequest$ImageName' => 'The name of the image to delete.
', 'DescribeImageRequest$ImageName' => 'The name of the image to describe.
', 'DescribeImageResponse$ImageName' => 'The name of the image.
', 'DescribeImageVersionRequest$ImageName' => 'The name of the image.
', 'Image$ImageName' => 'The name of the image.
', 'ListAliasesRequest$ImageName' => 'The name of the image.
', 'ListImageVersionsRequest$ImageName' => 'The name of the image to list the versions of.
', 'UpdateImageRequest$ImageName' => 'The name of the image to update.
', 'UpdateImageVersionRequest$ImageName' => 'The name of the image.
', ], ], 'ImageNameContains' => [ 'base' => NULL, 'refs' => [ 'ListImagesRequest$NameContains' => 'A filter that returns only images whose name contains the specified string.
', ], ], 'ImageSortBy' => [ 'base' => NULL, 'refs' => [ 'ListImagesRequest$SortBy' => 'The property used to sort results. The default value is CREATION_TIME
.
The sort order. The default value is DESCENDING
.
The status of the image.
', 'Image$ImageStatus' => 'The status of the image.
', ], ], 'ImageUri' => [ 'base' => NULL, 'refs' => [ 'AppSpecification$ImageUri' => 'The container image to be run by the processing job.
', 'DataQualityAppSpecification$ImageUri' => 'The container image that the data quality monitoring job runs.
', 'ModelBiasAppSpecification$ImageUri' => 'The container image to be run by the model bias job.
', 'ModelExplainabilityAppSpecification$ImageUri' => 'The container image to be run by the model explainability job.
', 'ModelQualityAppSpecification$ImageUri' => 'The address of the container image that the monitoring job runs.
', 'MonitoringAppSpecification$ImageUri' => 'The container image to be run by the monitoring job.
', ], ], 'ImageVersion' => [ 'base' => 'A version of a SageMaker Image
. A version represents an existing container image.
The SageMakerImageVersionAlias of the image to launch with. This value is in SemVer 2.0.0 versioning format.
', ], ], 'ImageVersionArn' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionResponse$ImageVersionArn' => 'The ARN of the image version.
', 'DescribeImageVersionResponse$ImageVersionArn' => 'The ARN of the version.
', 'ImageVersion$ImageVersionArn' => 'The ARN of the version.
', 'ResourceSpec$SageMakerImageVersionArn' => 'The ARN of the image version created on the instance.
', 'UpdateImageVersionResponse$ImageVersionArn' => 'The ARN of the image version.
', ], ], 'ImageVersionNumber' => [ 'base' => NULL, 'refs' => [ 'CustomImage$ImageVersionNumber' => 'The version number of the CustomImage.
', 'DeleteImageVersionRequest$Version' => 'The version to delete.
', 'DescribeImageVersionRequest$Version' => 'The version of the image. If not specified, the latest version is described.
', 'DescribeImageVersionResponse$Version' => 'The version number.
', 'ImageVersion$Version' => 'The version number.
', 'ListAliasesRequest$Version' => 'The version of the image. If image version is not specified, the aliases of all versions of the image are listed.
', 'UpdateImageVersionRequest$Version' => 'The version of the image.
', ], ], 'ImageVersionSortBy' => [ 'base' => NULL, 'refs' => [ 'ListImageVersionsRequest$SortBy' => 'The property used to sort results. The default value is CREATION_TIME
.
The sort order. The default value is DESCENDING
.
The status of the version.
', 'ImageVersion$ImageVersionStatus' => 'The status of the version.
', ], ], 'ImageVersions' => [ 'base' => NULL, 'refs' => [ 'ListImageVersionsResponse$ImageVersions' => 'A list of versions and their properties.
', ], ], 'Images' => [ 'base' => NULL, 'refs' => [ 'ListImagesResponse$Images' => 'A list of images and their properties.
', ], ], 'ImportHubContentRequest' => [ 'base' => NULL, 'refs' => [], ], 'ImportHubContentResponse' => [ 'base' => NULL, 'refs' => [], ], 'InferenceComponentArn' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceComponentOutput$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', 'DescribeInferenceComponentOutput$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', 'InferenceComponentSummary$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', 'UpdateInferenceComponentOutput$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', 'UpdateInferenceComponentRuntimeConfigOutput$InferenceComponentArn' => 'The Amazon Resource Name (ARN) of the inference component.
', ], ], 'InferenceComponentComputeResourceRequirements' => [ 'base' => 'Defines the compute resources to allocate to run a model that you assign to an inference component. These resources include CPU cores, accelerators, and memory.
', 'refs' => [ 'InferenceComponentSpecification$ComputeResourceRequirements' => 'The compute resources allocated to run the model assigned to the inference component.
', 'InferenceComponentSpecificationSummary$ComputeResourceRequirements' => 'The compute resources allocated to run the model assigned to the inference component.
', ], ], 'InferenceComponentContainerSpecification' => [ 'base' => 'Defines a container that provides the runtime environment for a model that you deploy with an inference component.
', 'refs' => [ 'InferenceComponentSpecification$Container' => 'Defines a container that provides the runtime environment for a model that you deploy with an inference component.
', ], ], 'InferenceComponentContainerSpecificationSummary' => [ 'base' => 'Details about the resources that are deployed with this inference component.
', 'refs' => [ 'InferenceComponentSpecificationSummary$Container' => 'Details about the container that provides the runtime environment for the model that is deployed with the inference component.
', ], ], 'InferenceComponentCopyCount' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentRuntimeConfig$CopyCount' => 'The number of runtime copies of the model container to deploy with the inference component. Each copy can serve inference requests.
', 'InferenceComponentRuntimeConfigSummary$DesiredCopyCount' => 'The number of runtime copies of the model container that you requested to deploy with the inference component.
', 'InferenceComponentRuntimeConfigSummary$CurrentCopyCount' => 'The number of runtime copies of the model container that are currently deployed.
', ], ], 'InferenceComponentName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceComponentInput$InferenceComponentName' => 'A unique name to assign to the inference component.
', 'DeleteInferenceComponentInput$InferenceComponentName' => 'The name of the inference component to delete.
', 'DescribeInferenceComponentInput$InferenceComponentName' => 'The name of the inference component.
', 'DescribeInferenceComponentOutput$InferenceComponentName' => 'The name of the inference component.
', 'InferenceComponentSummary$InferenceComponentName' => 'The name of the inference component.
', 'UpdateInferenceComponentInput$InferenceComponentName' => 'The name of the inference component.
', 'UpdateInferenceComponentRuntimeConfigInput$InferenceComponentName' => 'The name of the inference component to update.
', ], ], 'InferenceComponentNameContains' => [ 'base' => NULL, 'refs' => [ 'ListInferenceComponentsInput$NameContains' => 'Filters the results to only those inference components with a name that contains the specified string.
', ], ], 'InferenceComponentRuntimeConfig' => [ 'base' => 'Runtime settings for a model that is deployed with an inference component.
', 'refs' => [ 'CreateInferenceComponentInput$RuntimeConfig' => 'Runtime settings for a model that is deployed with an inference component.
', 'UpdateInferenceComponentInput$RuntimeConfig' => 'Runtime settings for a model that is deployed with an inference component.
', 'UpdateInferenceComponentRuntimeConfigInput$DesiredRuntimeConfig' => 'Runtime settings for a model that is deployed with an inference component.
', ], ], 'InferenceComponentRuntimeConfigSummary' => [ 'base' => 'Details about the runtime settings for the model that is deployed with the inference component.
', 'refs' => [ 'DescribeInferenceComponentOutput$RuntimeConfig' => 'Details about the runtime settings for the model that is deployed with the inference component.
', ], ], 'InferenceComponentSortKey' => [ 'base' => NULL, 'refs' => [ 'ListInferenceComponentsInput$SortBy' => 'The field by which to sort the inference components in the response. The default is CreationTime
.
Details about the resources to deploy with this inference component, including the model, container, and compute resources.
', 'refs' => [ 'CreateInferenceComponentInput$Specification' => 'Details about the resources to deploy with this inference component, including the model, container, and compute resources.
', 'UpdateInferenceComponentInput$Specification' => 'Details about the resources to deploy with this inference component, including the model, container, and compute resources.
', ], ], 'InferenceComponentSpecificationSummary' => [ 'base' => 'Details about the resources that are deployed with this inference component.
', 'refs' => [ 'DescribeInferenceComponentOutput$Specification' => 'Details about the resources that are deployed with this inference component.
', ], ], 'InferenceComponentStartupParameters' => [ 'base' => 'Settings that take effect while the model container starts up.
', 'refs' => [ 'InferenceComponentSpecification$StartupParameters' => 'Settings that take effect while the model container starts up.
', 'InferenceComponentSpecificationSummary$StartupParameters' => 'Settings that take effect while the model container starts up.
', ], ], 'InferenceComponentStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceComponentOutput$InferenceComponentStatus' => 'The status of the inference component.
', 'InferenceComponentSummary$InferenceComponentStatus' => 'The status of the inference component.
', 'ListInferenceComponentsInput$StatusEquals' => 'Filters the results to only those inference components with the specified status.
', ], ], 'InferenceComponentSummary' => [ 'base' => 'A summary of the properties of an inference component.
', 'refs' => [ 'InferenceComponentSummaryList$member' => NULL, ], ], 'InferenceComponentSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListInferenceComponentsOutput$InferenceComponents' => 'A list of inference components and their properties that matches any of the filters you specified in the request.
', ], ], 'InferenceExecutionConfig' => [ 'base' => 'Specifies details about how containers in a multi-container endpoint are run.
', 'refs' => [ 'CreateModelInput$InferenceExecutionConfig' => 'Specifies details of how containers in a multi-container endpoint are called.
', 'DescribeModelOutput$InferenceExecutionConfig' => 'Specifies details of how containers in a multi-container endpoint are called.
', 'Model$InferenceExecutionConfig' => NULL, ], ], 'InferenceExecutionMode' => [ 'base' => NULL, 'refs' => [ 'InferenceExecutionConfig$Mode' => 'How containers in a multi-container are run. The following values are valid.
SERIAL
- Containers run as a serial pipeline.
DIRECT
- Only the individual container that you specify is run.
The ARN for your inference experiment.
', 'DeleteInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the deleted inference experiment.
', 'DescribeInferenceExperimentResponse$Arn' => 'The ARN of the inference experiment being described.
', 'StartInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the started inference experiment to start.
', 'StopInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the stopped inference experiment.
', 'UpdateInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the updated inference experiment.
', ], ], 'InferenceExperimentDataStorageConfig' => [ 'base' => 'The Amazon S3 location and configuration for storing inference request and response data.
', 'refs' => [ 'CreateInferenceExperimentRequest$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
', 'DescribeInferenceExperimentResponse$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
', 'UpdateInferenceExperimentRequest$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
', ], ], 'InferenceExperimentDescription' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Description' => 'A description for the inference experiment.
', 'DescribeInferenceExperimentResponse$Description' => 'The description of the inference experiment.
', 'InferenceExperimentSummary$Description' => 'The description of the inference experiment.
', 'UpdateInferenceExperimentRequest$Description' => 'The description of the inference experiment.
', ], ], 'InferenceExperimentList' => [ 'base' => NULL, 'refs' => [ 'ListInferenceExperimentsResponse$InferenceExperiments' => 'List of inference experiments.
', ], ], 'InferenceExperimentName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Name' => 'The name for the inference experiment.
', 'DeleteInferenceExperimentRequest$Name' => 'The name of the inference experiment you want to delete.
', 'DescribeInferenceExperimentRequest$Name' => 'The name of the inference experiment to describe.
', 'DescribeInferenceExperimentResponse$Name' => 'The name of the inference experiment.
', 'InferenceExperimentSummary$Name' => 'The name of the inference experiment.
', 'StartInferenceExperimentRequest$Name' => 'The name of the inference experiment to start.
', 'StopInferenceExperimentRequest$Name' => 'The name of the inference experiment to stop.
', 'UpdateInferenceExperimentRequest$Name' => 'The name of the inference experiment to be updated.
', ], ], 'InferenceExperimentSchedule' => [ 'base' => 'The start and end times of an inference experiment.
The maximum duration that you can set for an inference experiment is 30 days.
', 'refs' => [ 'CreateInferenceExperimentRequest$Schedule' => 'The duration for which you want the inference experiment to run. If you don\'t specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
', 'DescribeInferenceExperimentResponse$Schedule' => 'The duration for which the inference experiment ran or will run.
', 'InferenceExperimentSummary$Schedule' => 'The duration for which the inference experiment ran or will run.
The maximum duration that you can set for an inference experiment is 30 days.
', 'UpdateInferenceExperimentRequest$Schedule' => ' The duration for which the inference experiment will run. If the status of the inference experiment is Created
, then you can update both the start and end dates. If the status of the inference experiment is Running
, then you can update only the end date.
The status of the inference experiment. The following are the possible statuses for an inference experiment:
Creating
- Amazon SageMaker is creating your experiment.
Created
- Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.
Updating
- When you make changes to your experiment, your experiment shows as updating.
Starting
- Amazon SageMaker is beginning your experiment.
Running
- Your experiment is in progress.
Stopping
- Amazon SageMaker is stopping your experiment.
Completed
- Your experiment has completed.
Cancelled
- When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.
The status of the inference experiment.
', 'ListInferenceExperimentsRequest$StatusEquals' => 'Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment.
', ], ], 'InferenceExperimentStatusReason' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceExperimentResponse$StatusReason' => ' The error message or client-specified Reason
from the StopInferenceExperiment API, that explains the status of the inference experiment.
The error message for the inference experiment status result.
', 'StopInferenceExperimentRequest$Reason' => 'The reason for stopping the experiment.
', ], ], 'InferenceExperimentStopDesiredState' => [ 'base' => NULL, 'refs' => [ 'StopInferenceExperimentRequest$DesiredState' => 'The desired state of the experiment after stopping. The possible states are the following:
Completed
: The experiment completed successfully
Cancelled
: The experiment was canceled
Lists a summary of properties of an inference experiment.
', 'refs' => [ 'InferenceExperimentList$member' => NULL, ], ], 'InferenceExperimentType' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Type' => 'The type of the inference experiment that you want to run. The following types of experiments are possible:
ShadowMode
: You can use this type to validate a shadow variant. For more information, see Shadow tests.
The type of the inference experiment.
', 'InferenceExperimentSummary$Type' => 'The type of the inference experiment.
', 'ListInferenceExperimentsRequest$Type' => 'Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment.
', ], ], 'InferenceImage' => [ 'base' => NULL, 'refs' => [ 'DescribeCompilationJobResponse$InferenceImage' => 'The inference image to use when compiling a model. Specify an image only if the target device is a cloud instance.
', ], ], 'InferenceMetrics' => [ 'base' => 'The metrics for an existing endpoint compared in an Inference Recommender job.
', 'refs' => [ 'EndpointPerformance$Metrics' => 'The metrics for an existing endpoint.
', 'RecommendationJobInferenceBenchmark$EndpointMetrics' => NULL, ], ], 'InferenceRecommendation' => [ 'base' => 'A list of recommendations made by Amazon SageMaker Inference Recommender.
', 'refs' => [ 'InferenceRecommendations$member' => NULL, ], ], 'InferenceRecommendations' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$InferenceRecommendations' => 'The recommendations made by Inference Recommender.
', ], ], 'InferenceRecommendationsJob' => [ 'base' => 'A structure that contains a list of recommendation jobs.
', 'refs' => [ 'InferenceRecommendationsJobs$member' => NULL, ], ], 'InferenceRecommendationsJobStep' => [ 'base' => 'A returned array object for the Steps
response field in the ListInferenceRecommendationsJobSteps API command.
A list of all subtask details in Inference Recommender.
', ], ], 'InferenceRecommendationsJobs' => [ 'base' => NULL, 'refs' => [ 'ListInferenceRecommendationsJobsResponse$InferenceRecommendationsJobs' => 'The recommendations created from the Amazon SageMaker Inference Recommender job.
', ], ], 'InferenceSpecification' => [ 'base' => 'Defines how to perform inference generation after a training job is run.
', 'refs' => [ 'BatchDescribeModelPackageSummary$InferenceSpecification' => NULL, 'CreateAlgorithmInput$InferenceSpecification' => 'Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
Specifies details about inference jobs that can be run with models based on this model package, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the model package supports for inference.
Details about inference jobs that the algorithm runs.
', 'DescribeModelPackageOutput$InferenceSpecification' => 'Details about inference jobs that can be run with models based on this model package.
', 'ModelPackage$InferenceSpecification' => 'Defines how to perform inference generation after a training job is run.
', ], ], 'InferenceSpecificationName' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$InferenceSpecificationName' => 'The inference specification name in the model package version.
', 'EndpointInputConfiguration$InferenceSpecificationName' => 'The inference specification name in the model package version.
', 'ModelConfiguration$InferenceSpecificationName' => 'The inference specification name in the model package version.
', ], ], 'InfraCheckConfig' => [ 'base' => 'Configuration information for the infrastructure health check of a training job. A SageMaker-provided health check tests the health of instance hardware and cluster network connectivity.
', 'refs' => [ 'CreateTrainingJobRequest$InfraCheckConfig' => 'Contains information about the infrastructure health check configuration for the training job.
', 'DescribeTrainingJobResponse$InfraCheckConfig' => 'Contains information about the infrastructure health check configuration for the training job.
', ], ], 'InitialInstanceCount' => [ 'base' => NULL, 'refs' => [ 'EndpointOutputConfiguration$InitialInstanceCount' => 'The number of instances recommended to launch initially.
', ], ], 'InitialNumberOfUsers' => [ 'base' => NULL, 'refs' => [ 'Phase$InitialNumberOfUsers' => 'Specifies how many concurrent users to start with. The value should be between 1 and 3.
', ], ], 'InitialTaskCount' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$InitialInstanceCount' => 'Number of instances to launch initially.
', ], ], 'InputConfig' => [ 'base' => 'Contains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', 'refs' => [ 'CreateCompilationJobRequest$InputConfig' => 'Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', 'DescribeCompilationJobResponse$InputConfig' => 'Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', ], ], 'InputDataConfig' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$InputDataConfig' => 'An array of Channel
objects. Each channel is a named input source. InputDataConfig
describes the input data and its location.
Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data, training_data
and validation_data
. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.
Your input must be in the same Amazon Web Services region as your training job.
', 'DescribeTrainingJobResponse$InputDataConfig' => 'An array of Channel
objects that describes each data input channel.
An array of Channel objects that specify the input for the training jobs that the tuning job launches.
', 'TrainingJob$InputDataConfig' => 'An array of Channel
objects that describes each data input channel.
Your input must be in the same Amazon Web Services region as your training job.
', 'TrainingJobDefinition$InputDataConfig' => 'An array of Channel
objects, each of which specifies an input source.
Whether to use File
or Pipe
input mode. In File
(default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe
mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
The allowed input mode, either FILE or PIPE.
In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.
In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
', ], ], 'InstanceGroup' => [ 'base' => 'Defines an instance group for heterogeneous cluster training. When requesting a training job using the CreateTrainingJob API, you can configure multiple instance groups .
', 'refs' => [ 'InstanceGroups$member' => NULL, ], ], 'InstanceGroupName' => [ 'base' => NULL, 'refs' => [ 'InstanceGroup$InstanceGroupName' => 'Specifies the name of the instance group.
', 'InstanceGroupNames$member' => NULL, ], ], 'InstanceGroupNames' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$InstanceGroupNames' => 'A list of names of instance groups that get data from the S3 data source.
', ], ], 'InstanceGroups' => [ 'base' => NULL, 'refs' => [ 'ResourceConfig$InstanceGroups' => 'The configuration of a heterogeneous cluster in JSON format.
', ], ], 'InstanceMetadataServiceConfiguration' => [ 'base' => 'Information on the IMDS configuration of the notebook instance
', 'refs' => [ 'CreateNotebookInstanceInput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', 'DescribeNotebookInstanceOutput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', 'UpdateNotebookInstanceInput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', ], ], 'InstanceType' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$InstanceType' => 'The type of ML compute instance to launch for the notebook instance.
', 'DescribeNotebookInstanceOutput$InstanceType' => 'The type of ML compute instance running on the notebook instance.
', 'NotebookInstanceSummary$InstanceType' => 'The type of ML compute instance that the notebook instance is running on.
', 'RealTimeInferenceConfig$InstanceType' => 'The instance type the model is deployed to.
', 'UpdateNotebookInstanceInput$InstanceType' => 'The Amazon ML compute instance type.
', ], ], 'Integer' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobRequest$ModelCardVersion' => 'The version of the model card to export. If a version is not provided, then the latest version of the model card is exported.
', 'DescribeDeviceResponse$MaxModels' => 'The maximum number of models.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentSuccess' => 'The number of edge devices with the successful deployment.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPending' => 'The number of edge devices yet to pick up deployment, or in progress.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentFailed' => 'The number of edge devices that failed the deployment.
', 'DescribeModelCardExportJobResponse$ModelCardVersion' => 'The version of the model card that the model export job exports.
', 'DescribeModelCardRequest$ModelCardVersion' => 'The version of the model card to describe. If a version is not provided, then the latest version of the model card is described.
', 'DescribeModelCardResponse$ModelCardVersion' => 'The version of the model card.
', 'DynamicScalingConfiguration$MinCapacity' => 'The recommended minimum capacity to specify for your autoscaling policy.
', 'DynamicScalingConfiguration$MaxCapacity' => 'The recommended maximum capacity to specify for your autoscaling policy.
', 'DynamicScalingConfiguration$ScaleInCooldown' => 'The recommended scale in cooldown time for your autoscaling policy.
', 'DynamicScalingConfiguration$ScaleOutCooldown' => 'The recommended scale out cooldown time for your autoscaling policy.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentSuccess' => 'The number of edge devices with the successful deployment.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPending' => 'The number of edge devices yet to pick up the deployment, or in progress.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentFailed' => 'The number of edge devices that failed the deployment.
', 'EdgeDeploymentStatus$EdgeDeploymentSuccessInStage' => 'The number of edge devices with the successful deployment in the current stage.
', 'EdgeDeploymentStatus$EdgeDeploymentPendingInStage' => 'The number of edge devices yet to pick up the deployment in current stage, or in progress.
', 'EdgeDeploymentStatus$EdgeDeploymentFailedInStage' => 'The number of edge devices that failed the deployment in current stage.
', 'HyperParameterTuningJobCompletionDetails$NumberOfTrainingJobsObjectiveNotImproving' => 'The number of training jobs launched by a tuning job that are not improving (1% or less) as measured by model performance evaluated against an objective function.
', 'HyperParameterTuningJobConsumedResources$RuntimeInSeconds' => 'The wall clock runtime in seconds used by your hyperparameter tuning job.
', 'InferenceMetrics$MaxInvocations' => 'The expected maximum number of requests per minute for the instance.
', 'InferenceMetrics$ModelLatency' => 'The expected model latency at maximum invocations per minute for the instance.
', 'ListModelCardExportJobsRequest$ModelCardVersion' => 'List export jobs for the model card with the specified version.
', 'ModelCard$ModelCardVersion' => 'The version of the model card.
', 'ModelCardExportJobSummary$ModelCardVersion' => 'The version of the model card that the export job exports.
', 'ModelCardVersionSummary$ModelCardVersion' => 'A version of the model card.
', 'ModelDashboardModelCard$ModelCardVersion' => 'The model card version.
', 'ModelLatencyThreshold$ValueInMilliseconds' => 'The model latency percentile value in milliseconds.
', 'PipelineExecutionStep$AttemptCount' => 'The current attempt of the execution step. For more information, see Retry Policy for SageMaker Pipelines steps.
', 'RecommendationJobStoppingConditions$MaxInvocations' => 'The maximum number of requests per minute expected for the endpoint.
', 'RecommendationMetrics$MaxInvocations' => 'The expected maximum number of requests per minute for the instance.
', 'RecommendationMetrics$ModelLatency' => 'The expected model latency at maximum invocation per minute for the instance.
', 'ScalingPolicyMetric$InvocationsPerInstance' => 'The number of invocations sent to a model, normalized by InstanceCount
in each ProductionVariant. 1/numberOfInstances
is sent as the value on each request, where numberOfInstances
is the number of active instances for the ProductionVariant behind the endpoint at the time of the request.
The interval of time taken by a model to respond as viewed from SageMaker. This interval includes the local communication times taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
', 'ScalingPolicyObjective$MinInvocationsPerMinute' => 'The minimum number of expected requests to your endpoint per minute.
', 'ScalingPolicyObjective$MaxInvocationsPerMinute' => 'The maximum number of expected requests to your endpoint per minute.
', ], ], 'IntegerParameterRange' => [ 'base' => 'For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
', 'refs' => [ 'IntegerParameterRanges$member' => NULL, ], ], 'IntegerParameterRangeSpecification' => [ 'base' => 'Defines the possible values for an integer hyperparameter.
', 'refs' => [ 'ParameterRange$IntegerParameterRangeSpecification' => 'A IntegerParameterRangeSpecification
object that defines the possible values for an integer hyperparameter.
The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.
', ], ], 'InvocationEndTime' => [ 'base' => NULL, 'refs' => [ 'InferenceRecommendation$InvocationEndTime' => 'A timestamp that shows when the benchmark completed.
', 'RecommendationJobInferenceBenchmark$InvocationEndTime' => 'A timestamp that shows when the benchmark completed.
', ], ], 'InvocationStartTime' => [ 'base' => NULL, 'refs' => [ 'InferenceRecommendation$InvocationStartTime' => 'A timestamp that shows when the benchmark started.
', 'RecommendationJobInferenceBenchmark$InvocationStartTime' => 'A timestamp that shows when the benchmark started.
', ], ], 'InvocationsMaxRetries' => [ 'base' => NULL, 'refs' => [ 'ModelClientConfig$InvocationsMaxRetries' => 'The maximum number of retries when invocation requests are failing. The default value is 3.
', ], ], 'InvocationsTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'ModelClientConfig$InvocationsTimeoutInSeconds' => 'The timeout value in seconds for an invocation request. The default value is 600.
', ], ], 'IotRoleAlias' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceFleetResponse$IotRoleAlias' => 'The Amazon Resource Name (ARN) alias created in Amazon Web Services Internet of Things (IoT).
', ], ], 'ItemIdentifierAttributeName' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$ItemIdentifierAttributeName' => 'The name of the column that represents the set of item identifiers for which you want to predict the target value.
', ], ], 'JobDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$JobDurationInSeconds' => 'Specifies the maximum duration of the job, in seconds. The maximum value is 18,000 seconds.
', ], ], 'JobReferenceCode' => [ 'base' => NULL, 'refs' => [ 'DescribeLabelingJobResponse$JobReferenceCode' => 'A unique identifier for work done as part of a labeling job.
', 'LabelingJobForWorkteamSummary$JobReferenceCode' => 'A unique identifier for a labeling job. You can use this to refer to a specific labeling job.
', ], ], 'JobReferenceCodeContains' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamRequest$JobReferenceCodeContains' => 'A filter the limits jobs to only the ones whose job reference code contains the specified string.
', ], ], 'JobType' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$JobType' => 'Indicates SageMaker job type compatibility.
TRAINING
: The image version is compatible with SageMaker training jobs.
INFERENCE
: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
Indicates SageMaker job type compatibility.
TRAINING
: The image version is compatible with SageMaker training jobs.
INFERENCE
: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
Indicates SageMaker job type compatibility.
TRAINING
: The image version is compatible with SageMaker training jobs.
INFERENCE
: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
Specifies the source of the data to join with the transformed data. The valid values are None
and Input
. The default value is None
, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set JoinSource
to Input
. You can specify OutputFilter
as an additional filter to select a portion of the joined dataset and store it in the output file.
For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput
. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput
key and the results are stored in SageMakerOutput
.
For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.
For information on how joining in applied, see Workflow for Associating Inferences with Input Records.
', ], ], 'JsonContentType' => [ 'base' => NULL, 'refs' => [ 'JsonContentTypes$member' => NULL, ], ], 'JsonContentTypes' => [ 'base' => NULL, 'refs' => [ 'CaptureContentTypeHeader$JsonContentTypes' => 'The list of all content type headers that SageMaker will treat as JSON and capture accordingly.
', ], ], 'JsonPath' => [ 'base' => NULL, 'refs' => [ 'DataProcessing$InputFilter' => 'A JSONPath expression used to select a portion of the input data to pass to the algorithm. Use the InputFilter
parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $
.
Examples: "$"
, "$[1:]"
, "$.features"
A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $
. If you specify indexes that aren\'t within the dimension size of the joined dataset, you get an error.
Examples: "$"
, "$[0,5:]"
, "$[\'id\',\'SageMakerOutput\']"
The configuration for the file system and kernels in a SageMaker image running as a JupyterLab app.
', 'refs' => [ 'AppImageConfigDetails$JupyterLabAppImageConfig' => 'The configuration for the file system and the runtime, such as the environment variables and entry point.
', 'CreateAppImageConfigRequest$JupyterLabAppImageConfig' => 'The JupyterLabAppImageConfig
. You can only specify one image kernel in the AppImageConfig
API. This kernel is shown to users before the image starts. After the image runs, all kernels are visible in JupyterLab.
The configuration of the JupyterLab app.
', 'UpdateAppImageConfigRequest$JupyterLabAppImageConfig' => 'The JupyterLab app running on the image.
', ], ], 'JupyterLabAppSettings' => [ 'base' => 'The settings for the JupyterLab application.
', 'refs' => [ 'UserSettings$JupyterLabAppSettings' => 'The settings for the JupyterLab application.
', ], ], 'JupyterServerAppSettings' => [ 'base' => 'The JupyterServer app settings.
', 'refs' => [ 'DefaultSpaceSettings$JupyterServerAppSettings' => NULL, 'SpaceSettings$JupyterServerAppSettings' => NULL, 'UserSettings$JupyterServerAppSettings' => 'The Jupyter server\'s app settings.
', ], ], 'KeepAlivePeriodInSeconds' => [ 'base' => 'Optional. Customer requested period in seconds for which the Training cluster is kept alive after the job is finished.', 'refs' => [ 'ResourceConfig$KeepAlivePeriodInSeconds' => 'The duration of time in seconds to retain configured resources in a warm pool for subsequent training jobs.
', 'ResourceConfigForUpdate$KeepAlivePeriodInSeconds' => 'The KeepAlivePeriodInSeconds
value specified in the ResourceConfig
to update.
The Amazon SageMaker Canvas application setting where you configure document querying.
', 'refs' => [ 'CanvasAppSettings$KendraSettings' => 'The settings for document querying.
', ], ], 'KernelDisplayName' => [ 'base' => NULL, 'refs' => [ 'KernelSpec$DisplayName' => 'The display name of the kernel.
', ], ], 'KernelGatewayAppSettings' => [ 'base' => 'The KernelGateway app settings.
', 'refs' => [ 'DefaultSpaceSettings$KernelGatewayAppSettings' => NULL, 'SpaceSettings$KernelGatewayAppSettings' => NULL, 'UserSettings$KernelGatewayAppSettings' => 'The kernel gateway app settings.
', ], ], 'KernelGatewayImageConfig' => [ 'base' => 'The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.
', 'refs' => [ 'AppImageConfigDetails$KernelGatewayImageConfig' => 'The configuration for the file system and kernels in the SageMaker image.
', 'CreateAppImageConfigRequest$KernelGatewayImageConfig' => 'The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.
', 'DescribeAppImageConfigResponse$KernelGatewayImageConfig' => 'The configuration of a KernelGateway app.
', 'UpdateAppImageConfigRequest$KernelGatewayImageConfig' => 'The new KernelGateway app to run on the image.
', ], ], 'KernelName' => [ 'base' => NULL, 'refs' => [ 'KernelSpec$Name' => 'The name of the Jupyter kernel in the image. This value is case sensitive.
', ], ], 'KernelSpec' => [ 'base' => 'The specification of a Jupyter kernel.
', 'refs' => [ 'KernelSpecs$member' => NULL, ], ], 'KernelSpecs' => [ 'base' => NULL, 'refs' => [ 'KernelGatewayImageConfig$KernelSpecs' => 'The specification of the Jupyter kernels in the image.
', ], ], 'Key' => [ 'base' => NULL, 'refs' => [ 'PipelineDefinitionS3Location$ObjectKey' => 'The object key (or key name) uniquely identifies the object in an S3 bucket.
', ], ], 'KmsKeyId' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
', 'AthenaDatasetDefinition$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
', 'AutoMLOutputDataConfig$KmsKeyId' => 'The Key Management Service (KMS) encryption key ID.
', 'AutoMLSecurityConfig$VolumeKmsKeyId' => 'The key used to encrypt stored data.
', 'BatchDataCaptureConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Use KmsKeyId
.
SageMaker uses Amazon Web Services KMS to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.
', 'CreateEdgePackagingJobRequest$ResourceKey' => 'The Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on.
', 'CreateEndpointConfigInput$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint
, UpdateEndpoint
requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a KmsKeyId
when using an instance type with local storage. If any of the models that you specify in the ProductionVariants
parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId
parameter. If you specify a value for KmsKeyId
when using any nitro-based instances with local storage, the call to CreateEndpointConfig
fails.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey
can be any of the following formats:
KMS key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
KMS key Alias
"alias/ExampleAlias"
Amazon Resource Name (ARN) of a KMS key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call kms:Encrypt
. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig
. If you use a bucket policy with an s3:PutObject
permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption
to "aws:kms"
. For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint
and UpdateEndpoint
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.
', 'DataCaptureConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key being used to encrypt the data in Amazon S3.
', 'DescribeDomainResponse$HomeEfsFileSystemKmsKeyId' => 'Use KmsKeyId
.
The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.
', 'DescribeEdgePackagingJobResponse$ResourceKey' => 'The Amazon Web Services KMS key to use when encrypting the EBS volume the job run on.
', 'DescribeEndpointConfigOutput$KmsKeyId' => 'Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
', 'DescribeInferenceExperimentResponse$KmsKey' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.
', 'DescribeNotebookInstanceOutput$KmsKeyId' => 'The Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
', 'EdgeOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account.
', 'FlowDefinitionOutputConfig$KmsKeyId' => 'The Amazon Key Management Service (KMS) key ID for server-side encryption.
', 'HyperParameterTuningResourceConfig$VolumeKmsKeyId' => 'A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a VolumeKmsKeyId
. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information.
The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3 server-side encryption.
', 'LabelingJobOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
If you provide your own KMS key ID, you must add the required permissions to your KMS key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
If you don\'t provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role\'s account to encrypt your output data.
If you use a bucket policy with an s3:PutObject
permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption
to "aws:kms"
. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.
You can only specify a VolumeKmsKeyId
when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob
. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see Output Data and Storage Volume Encryption.
The VolumeKmsKeyId
can be any of the following formats:
KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
A Key Management Service key ID to use for encrypting a model card.
', 'MonitoringClusterConfig$VolumeKmsKeyId' => 'The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
', 'MonitoringOutputConfig$KmsKeyId' => 'The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
', 'OnlineStoreSecurityConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side encryption.
The caller (either user or IAM role) of CreateFeatureGroup
must have below permissions to the OnlineStore
KmsKeyId
:
"kms:Encrypt"
"kms:Decrypt"
"kms:DescribeKey"
"kms:CreateGrant"
"kms:RetireGrant"
"kms:ReEncryptFrom"
"kms:ReEncryptTo"
"kms:GenerateDataKey"
"kms:ListAliases"
"kms:ListGrants"
"kms:RevokeGrant"
The caller (either user or IAM role) to all DataPlane operations (PutRecord
, GetRecord
, DeleteRecord
) must have the following permissions to the KmsKeyId
:
"kms:Decrypt"
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId
can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt
. If you don\'t provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide. If the output data is stored in Amazon S3 Express One Zone, it is encrypted with server-side encryption with Amazon S3 managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One Zone
The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob
, CreateTransformJob
, or CreateHyperParameterTuningJob
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId
when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId
can be an ID of a KMS key, ARN of a KMS key, alias of a KMS key, or alias of a KMS key. The KmsKeyId
is applied to all outputs.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId
can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt
. If you don\'t provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role\'s account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig
. If you use a bucket policy with an s3:PutObject
permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption
to "aws:kms"
. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint
and UpdateEndpoint
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.
The SageMaker execution role must have kms:CreateGrant
permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant
permission.
The KmsKeyId
can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
', 'RecommendationJobOutputConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey
permission.
The KmsKeyId
can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
', 'RedshiftDatasetDefinition$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
', 'ResourceConfig$VolumeKmsKeyId' => 'The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId
when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId
can be in any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt any objects written into the OfflineStore
S3 location.
The IAM roleARN
that is passed as a parameter to CreateFeatureGroup
must have below permissions to the KmsKeyId
:
"kms:GenerateDataKey"
When NotebookOutputOption
is Allowed
, the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId
can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateModel request. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
', 'TransformResources$VolumeKmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId
when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId
can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The Amazon Web Services Key Management Service (KMS) encryption key ID that is used to encrypt artifacts generated by Canvas in the Amazon S3 bucket.
', ], ], 'LabelAttributeName' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobRequest$LabelAttributeName' => 'The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName
must meet the following requirements.
The name can\'t end with "-metadata".
If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
Image semantic segmentation (SemanticSegmentation)
, and adjustment (AdjustmentSemanticSegmentation
) and verification (VerificationSemanticSegmentation
) labeling jobs for this task type.
Video frame object detection (VideoObjectDetection
), and adjustment and verification (AdjustmentVideoObjectDetection
) labeling jobs for this task type.
Video frame object tracking (VideoObjectTracking
), and adjustment and verification (AdjustmentVideoObjectTracking
) labeling jobs for this task type.
3D point cloud semantic segmentation (3DPointCloudSemanticSegmentation
), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation
) labeling jobs for this task type.
3D point cloud object tracking (3DPointCloudObjectTracking
), and adjustment and verification (Adjustment3DPointCloudObjectTracking
) labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a different LabelAttributeName
than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.
The attribute used as the label in the output manifest file.
', ], ], 'LabelCounter' => [ 'base' => NULL, 'refs' => [ 'LabelCounters$TotalLabeled' => 'The total number of objects labeled.
', 'LabelCounters$HumanLabeled' => 'The total number of objects labeled by a human worker.
', 'LabelCounters$MachineLabeled' => 'The total number of objects labeled by automated data labeling.
', 'LabelCounters$FailedNonRetryableError' => 'The total number of objects that could not be labeled due to an error.
', 'LabelCounters$Unlabeled' => 'The total number of objects not yet labeled.
', 'LabelCountersForWorkteam$HumanLabeled' => 'The total number of data objects labeled by a human worker.
', 'LabelCountersForWorkteam$PendingHuman' => 'The total number of data objects that need to be labeled by a human worker.
', 'LabelCountersForWorkteam$Total' => 'The total number of tasks in the labeling job.
', ], ], 'LabelCounters' => [ 'base' => 'Provides a breakdown of the number of objects labeled.
', 'refs' => [ 'DescribeLabelingJobResponse$LabelCounters' => 'Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn\'t be labeled, and the total number of objects labeled.
', 'LabelingJobSummary$LabelCounters' => 'Counts showing the progress of the labeling job.
', ], ], 'LabelCountersForWorkteam' => [ 'base' => 'Provides counts for human-labeled tasks in the labeling job.
', 'refs' => [ 'LabelingJobForWorkteamSummary$LabelCounters' => 'Provides information about the progress of a labeling job.
', ], ], 'LabelingJobAlgorithmSpecificationArn' => [ 'base' => NULL, 'refs' => [ 'LabelingJobAlgorithmsConfig$LabelingJobAlgorithmSpecificationArn' => 'Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
Text classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
Object detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
Semantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig
object must be supplied in order to use auto-labeling.
Configures the information required to perform automated data labeling.
', 'DescribeLabelingJobResponse$LabelingJobAlgorithmsConfig' => 'Configuration information for automated data labeling.
', ], ], 'LabelingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.
', 'DescribeLabelingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job.
', 'DescribeTrainingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
', 'DescribeTransformJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
', 'LabelingJobSummary$LabelingJobArn' => 'The Amazon Resource Name (ARN) assigned to the labeling job when it was created.
', 'TrainingJob$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job.
', 'TransformJob$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job that created the transform job.
', ], ], 'LabelingJobDataAttributes' => [ 'base' => 'Attributes of the data specified by the customer. Use these to describe the data to be labeled.
', 'refs' => [ 'LabelingJobInputConfig$DataAttributes' => 'Attributes of the data specified by the customer.
', ], ], 'LabelingJobDataSource' => [ 'base' => 'Provides information about the location of input data.
You must specify at least one of the following: S3DataSource
or SnsDataSource
.
Use SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource
is optional if you use SnsDataSource
to create a streaming labeling job.
The location of the input data.
', ], ], 'LabelingJobForWorkteamSummary' => [ 'base' => 'Provides summary information for a work team.
', 'refs' => [ 'LabelingJobForWorkteamSummaryList$member' => NULL, ], ], 'LabelingJobForWorkteamSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamResponse$LabelingJobSummaryList' => 'An array of LabelingJobSummary
objects, each describing a labeling job.
Input configuration information for a labeling job.
', 'refs' => [ 'CreateLabelingJobRequest$InputConfig' => 'Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following: S3DataSource
or SnsDataSource
.
Use SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.
Use S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource
is optional if you use SnsDataSource
to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers
to specify that your data is free of personally identifiable information and adult content.
Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
', 'LabelingJobSummary$InputConfig' => 'Input configuration for the labeling job.
', ], ], 'LabelingJobName' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobRequest$LabelingJobName' => 'The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName
is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.
The name of the labeling job to return information for.
', 'DescribeLabelingJobResponse$LabelingJobName' => 'The name assigned to the labeling job when it was created.
', 'LabelingJobForWorkteamSummary$LabelingJobName' => 'The name of the labeling job that the work team is assigned to.
', 'LabelingJobSummary$LabelingJobName' => 'The name of the labeling job.
', 'StopLabelingJobRequest$LabelingJobName' => 'The name of the labeling job to stop.
', ], ], 'LabelingJobOutput' => [ 'base' => 'Specifies the location of the output produced by the labeling job.
', 'refs' => [ 'DescribeLabelingJobResponse$LabelingJobOutput' => 'The location of the output produced by the labeling job.
', 'LabelingJobSummary$LabelingJobOutput' => 'The location of the output produced by the labeling job.
', ], ], 'LabelingJobOutputConfig' => [ 'base' => 'Output configuration information for a labeling job.
', 'refs' => [ 'CreateLabelingJobRequest$OutputConfig' => 'The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
', 'DescribeLabelingJobResponse$OutputConfig' => 'The location of the job\'s output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
', ], ], 'LabelingJobResourceConfig' => [ 'base' => 'Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.
', 'refs' => [ 'LabelingJobAlgorithmsConfig$LabelingJobResourceConfig' => 'Provides configuration information for a labeling job.
', ], ], 'LabelingJobS3DataSource' => [ 'base' => 'The Amazon S3 location of the input data objects.
', 'refs' => [ 'LabelingJobDataSource$S3DataSource' => 'The Amazon S3 location of the input data objects.
', ], ], 'LabelingJobSnsDataSource' => [ 'base' => 'An Amazon SNS data source used for streaming labeling jobs.
', 'refs' => [ 'LabelingJobDataSource$SnsDataSource' => 'An Amazon SNS data source used for streaming labeling jobs. To learn more, see Send Data to a Streaming Labeling Job.
', ], ], 'LabelingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeLabelingJobResponse$LabelingJobStatus' => 'The processing status of the labeling job.
', 'LabelingJobSummary$LabelingJobStatus' => 'The current status of the labeling job.
', 'ListLabelingJobsRequest$StatusEquals' => 'A filter that retrieves only labeling jobs with a specific status.
', ], ], 'LabelingJobStoppingConditions' => [ 'base' => 'A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
Labeling jobs fail after 30 days with an appropriate client error message.
A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
', 'DescribeLabelingJobResponse$StoppingConditions' => 'A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
', ], ], 'LabelingJobSummary' => [ 'base' => 'Provides summary information about a labeling job.
', 'refs' => [ 'LabelingJobSummaryList$member' => NULL, ], ], 'LabelingJobSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsResponse$LabelingJobSummaryList' => 'An array of LabelingJobSummary
objects, each describing a labeling job.
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn
. For custom labeling workflows, see Post-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Bounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn
. For custom labeling workflows, see Pre-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.
', 'LabelingJobSummary$AnnotationConsolidationLambdaArn' => 'The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see Annotation Consolidation.
', ], ], 'LambdaStepMetadata' => [ 'base' => 'Metadata for a Lambda step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Lambda' => 'The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.
', ], ], 'LandingUri' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlRequest$LandingUri' => 'The landing page that the user is directed to when accessing the presigned URL. Using this value, users can access Studio or Studio Classic, even if it is not the default experience for the domain. The supported values are:
studio::relative/path
: Directs users to the relative path in Studio.
app:JupyterServer:relative/path
: Directs users to the relative path in the Studio Classic application.
app:JupyterLab:relative/path
: Directs users to the relative path in the JupyterLab application.
app:RStudioServerPro:relative/path
: Directs users to the relative path in the RStudio application.
app:CodeEditor:relative/path
: Directs users to the relative path in the Code Editor, based on Code-OSS, Visual Studio Code - Open Source application.
app:Canvas:relative/path
: Directs users to the relative path in the Canvas application.
The default experience that the user is directed to when accessing the domain. The supported values are:
studio::
: Indicates that Studio is the default experience. This value can only be passed if StudioWebPortal
is set to ENABLED
.
app:JupyterServer:
: Indicates that Studio Classic is the default experience.
The date and time that the Git repository was last modified.
', 'CompilationJobSummary$LastModifiedTime' => 'The time when the model compilation job was last modified.
', 'DescribeCodeRepositoryOutput$LastModifiedTime' => 'The date and time that the repository was last changed.
', 'DescribeCompilationJobResponse$LastModifiedTime' => 'The time that the status of the model compilation job was last modified.
', 'DescribeDomainResponse$LastModifiedTime' => 'The last modified time.
', 'DescribeFeatureGroupResponse$LastModifiedTime' => 'A timestamp indicating when the feature group was last updated.
', 'DescribeFeatureMetadataResponse$LastModifiedTime' => 'A timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time you
', 'DescribeInferenceRecommendationsJobResponse$LastModifiedTime' => 'A timestamp that shows when the job was last modified.
', 'DescribeNotebookInstanceLifecycleConfigOutput$LastModifiedTime' => 'A timestamp that tells when the lifecycle configuration was last modified.
', 'DescribeNotebookInstanceOutput$LastModifiedTime' => 'A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
', 'DescribeSpaceResponse$LastModifiedTime' => 'The last modified time.
', 'DescribeUserProfileResponse$LastModifiedTime' => 'The last modified time.
', 'DomainDetails$LastModifiedTime' => 'The last modified time.
', 'FeatureGroup$LastModifiedTime' => 'A timestamp indicating the last time you updated the feature group.
', 'FeatureMetadata$LastModifiedTime' => 'A timestamp indicating when the feature was last modified.
', 'InferenceRecommendationsJob$LastModifiedTime' => 'A timestamp that shows when the job was last modified.
', 'ListCompilationJobsRequest$LastModifiedTimeAfter' => 'A filter that returns the model compilation jobs that were modified after a specified time.
', 'ListCompilationJobsRequest$LastModifiedTimeBefore' => 'A filter that returns the model compilation jobs that were modified before a specified time.
', 'ListInferenceRecommendationsJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only jobs that were last modified after the specified time (timestamp).
', 'ListInferenceRecommendationsJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only jobs that were last modified before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$LastModifiedTimeBefore' => 'A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$LastModifiedTimeAfter' => 'A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).
', 'ListNotebookInstancesInput$LastModifiedTimeBefore' => 'A filter that returns only notebook instances that were modified before the specified time (timestamp).
', 'ListNotebookInstancesInput$LastModifiedTimeAfter' => 'A filter that returns only notebook instances that were modified after the specified time (timestamp).
', 'NotebookInstanceLifecycleConfigSummary$LastModifiedTime' => 'A timestamp that tells when the lifecycle configuration was last modified.
', 'NotebookInstanceSummary$LastModifiedTime' => 'A timestamp that shows when the notebook instance was last modified.
', 'SpaceDetails$LastModifiedTime' => 'The last modified time.
', 'UserProfileDetails$LastModifiedTime' => 'The last modified time.
', ], ], 'LastUpdateStatus' => [ 'base' => 'A value that indicates whether the update was successful.
', 'refs' => [ 'DescribeFeatureGroupResponse$LastUpdateStatus' => 'A value indicating whether the update made to the feature group was successful.
', 'FeatureGroup$LastUpdateStatus' => 'A value that indicates whether the feature group was updated successfully.
', ], ], 'LastUpdateStatusValue' => [ 'base' => NULL, 'refs' => [ 'LastUpdateStatus$Status' => 'A value that indicates whether the update was made successful.
', ], ], 'LifecycleConfigArns' => [ 'base' => NULL, 'refs' => [ 'CodeEditorAppSettings$LifecycleConfigArns' => 'The Amazon Resource Name (ARN) of the Code Editor application lifecycle configuration.
', 'JupyterLabAppSettings$LifecycleConfigArns' => 'The Amazon Resource Name (ARN) of the lifecycle configurations attached to the user profile or domain. To remove a lifecycle config, you must set LifecycleConfigArns
to an empty list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec
parameter is also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns
to an empty list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
To remove a Lifecycle Config, you must set LifecycleConfigArns
to an empty list.
A list of properties to add to the action.
', 'CreateContextRequest$Properties' => 'A list of properties to add to the context.
', 'DescribeActionResponse$Properties' => 'A list of the action\'s properties.
', 'DescribeArtifactResponse$Properties' => 'A list of the artifact\'s properties.
', 'DescribeContextResponse$Properties' => 'A list of the context\'s properties.
', 'UpdateActionRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', 'UpdateContextRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', ], ], 'LineageGroupArn' => [ 'base' => NULL, 'refs' => [ 'DescribeActionResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeArtifactResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeContextResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeLineageGroupResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeTrialComponentResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'GetLineageGroupPolicyResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'LineageGroupSummary$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group resource.
', 'TrialComponent$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group resource.
', ], ], 'LineageGroupNameOrArn' => [ 'base' => NULL, 'refs' => [ 'GetLineageGroupPolicyRequest$LineageGroupName' => 'The name or Amazon Resource Name (ARN) of the lineage group.
', ], ], 'LineageGroupSummaries' => [ 'base' => NULL, 'refs' => [ 'ListLineageGroupsResponse$LineageGroupSummaries' => 'A list of lineage groups and their properties.
', ], ], 'LineageGroupSummary' => [ 'base' => 'Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity resources.
', 'refs' => [ 'LineageGroupSummaries$member' => NULL, ], ], 'LineageType' => [ 'base' => NULL, 'refs' => [ 'QueryLineageTypes$member' => NULL, 'Vertex$LineageType' => 'The type of resource of the lineage entity.
', ], ], 'ListActionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListActionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAlgorithmsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListAlgorithmsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListAliasesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAliasesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAppImageConfigsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAppImageConfigsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAppsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAppsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListArtifactsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListArtifactsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAssociationsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAssociationsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAutoMLJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAutoMLJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCandidatesForAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCandidatesForAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListClusterNodesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListClusterNodesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListClustersRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListClustersResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCodeRepositoriesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListCodeRepositoriesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCompilationJobsRequest$SortBy' => 'The field by which to sort results. The default is CreationTime
.
The column to sort by.
', ], ], 'ListDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListDevicesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListDomainsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListDomainsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansSortBy' => [ 'base' => NULL, 'refs' => [ 'ListEdgeDeploymentPlansRequest$SortBy' => 'The column by which to sort the edge deployment plans. Can be one of NAME
, DEVICEFLEETNAME
, CREATIONTIME
, LASTMODIFIEDTIME
.
Use to specify what column to sort by.
', ], ], 'ListEndpointConfigsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointConfigsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListExperimentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListExperimentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListFeatureGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListFeatureGroupsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListFlowDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListFlowDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHumanTaskUisRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHumanTaskUisResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHyperParameterTuningJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHyperParameterTuningJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListImageVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListImageVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListImagesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListImagesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceComponentsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceComponentsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceExperimentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceExperimentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobStepsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobStepsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListInferenceRecommendationsJobsRequest$SortBy' => 'The parameter by which to sort the results.
', ], ], 'ListLabelingJobsForWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListLabelingJobsForWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListLabelingJobsForWorkteamSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamRequest$SortBy' => 'The field to sort results by. The default is CreationTime
.
A list of properties to remove.
', 'UpdateArtifactRequest$PropertiesToRemove' => 'A list of properties to remove.
', 'UpdateContextRequest$PropertiesToRemove' => 'A list of properties to remove.
', ], ], 'ListLineageGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListLineageGroupsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListDeviceFleetsRequest$MaxResults' => 'The maximum number of results to select.
', 'ListDevicesRequest$MaxResults' => 'Maximum number of results to select.
', 'ListEdgeDeploymentPlansRequest$MaxResults' => 'The maximum number of results to select (50 by default).
', 'ListEdgePackagingJobsRequest$MaxResults' => 'Maximum number of results to select.
', 'ListStageDevicesRequest$MaxResults' => 'The maximum number of requests to select.
', ], ], 'ListModelBiasJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelBiasJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardExportJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardExportJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelExplainabilityJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelExplainabilityJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelMetadataResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackageGroupsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackageGroupsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackagesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackagesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelQualityJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelQualityJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertHistoryRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertHistoryResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringExecutionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringExecutionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringSchedulesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringSchedulesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstanceLifecycleConfigsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstanceLifecycleConfigsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstancesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstancesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionStepsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionStepsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineParametersForExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineParametersForExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelinesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelinesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListProcessingJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListProcessingJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListProjectsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListProjectsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListResourceCatalogsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListResourceCatalogsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListSpacesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListSpacesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListStageDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStageDevicesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListStudioLifecycleConfigsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStudioLifecycleConfigsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListSubscribedWorkteamsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListSubscribedWorkteamsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListTagsInput$MaxResults' => 'Maximum number of tags to return.
', ], ], 'ListTagsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsForHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsForHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTransformJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTransformJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialComponentKey256' => [ 'base' => NULL, 'refs' => [ 'UpdateTrialComponentRequest$ParametersToRemove' => 'The hyperparameters to remove from the component.
', 'UpdateTrialComponentRequest$InputArtifactsToRemove' => 'The input artifacts to remove from the component.
', 'UpdateTrialComponentRequest$OutputArtifactsToRemove' => 'The output artifacts to remove from the component.
', ], ], 'ListTrialComponentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialComponentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListUserProfilesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListUserProfilesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListWorkforcesRequest$SortBy' => 'Sort workforces using the workforce name or creation date.
', ], ], 'ListWorkteamsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkteamsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkteamsSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListWorkteamsRequest$SortBy' => 'The field to sort results by. The default is CreationTime
.
The number of Edge Manager agents.
', 'DeviceStats$ConnectedDeviceCount' => 'The number of devices connected with a heartbeat.
', 'DeviceStats$RegisteredDeviceCount' => 'The number of registered devices.
', 'EdgeModelStat$OfflineDeviceCount' => 'The number of devices that have this model version and do not have a heart beat.
', 'EdgeModelStat$ConnectedDeviceCount' => 'The number of devices that have this model version and have a heart beat.
', 'EdgeModelStat$ActiveDeviceCount' => 'The number of devices that have this model version, a heart beat, and are currently running.
', 'EdgeModelStat$SamplingDeviceCount' => 'The number of devices with this model version and are producing sample data.
', ], ], 'MLFramework' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$MLFramework' => 'The machine learning framework vended in the image version.
', 'DescribeImageVersionResponse$MLFramework' => 'The machine learning framework vended in the image version.
', 'UpdateImageVersionRequest$MLFramework' => 'The machine learning framework vended in the image version.
', ], ], 'ManagedInstanceScalingMaxInstanceCount' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantManagedInstanceScaling$MaxInstanceCount' => 'The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic.
', ], ], 'ManagedInstanceScalingMinInstanceCount' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantManagedInstanceScaling$MinInstanceCount' => 'The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic.
', ], ], 'ManagedInstanceScalingStatus' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantManagedInstanceScaling$Status' => 'Indicates whether managed instance scaling is enabled.
', ], ], 'MaxAutoMLJobRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobCompletionCriteria$MaxAutoMLJobRuntimeInSeconds' => 'The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, are not completed.
', ], ], 'MaxCandidates' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobCompletionCriteria$MaxCandidates' => 'The maximum number of times a training job is allowed to run.
For text and image classification, time-series forecasting, as well as text generation (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the maximum value is 750.
', ], ], 'MaxConcurrentInvocationsPerInstance' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceClientConfig$MaxConcurrentInvocationsPerInstance' => 'The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
', ], ], 'MaxConcurrentTaskCount' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$MaxConcurrentTaskCount' => 'Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
', ], ], 'MaxConcurrentTransforms' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$MaxConcurrentTransforms' => 'The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms
is set to 0
or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1
. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms
.
The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.
', 'TransformJob$MaxConcurrentTransforms' => 'The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms
is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms
.
The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
', ], ], 'MaxHumanLabeledObjectCount' => [ 'base' => NULL, 'refs' => [ 'LabelingJobStoppingConditions$MaxHumanLabeledObjectCount' => 'The maximum number of objects that can be labeled by human workers.
', ], ], 'MaxNumberOfTests' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobResourceLimit$MaxNumberOfTests' => 'Defines the maximum number of load tests.
', ], ], 'MaxNumberOfTrainingJobs' => [ 'base' => NULL, 'refs' => [ 'ResourceLimits$MaxNumberOfTrainingJobs' => 'The maximum number of training jobs that a hyperparameter tuning job can launch.
', ], ], 'MaxNumberOfTrainingJobsNotImproving' => [ 'base' => NULL, 'refs' => [ 'BestObjectiveNotImproving$MaxNumberOfTrainingJobsNotImproving' => 'The number of training jobs that have failed to improve model performance by 1% or greater over prior training jobs as evaluated against an objective function.
', ], ], 'MaxParallelExecutionSteps' => [ 'base' => NULL, 'refs' => [ 'ParallelismConfiguration$MaxParallelExecutionSteps' => 'The max number of steps that can be executed in parallel.
', ], ], 'MaxParallelOfTests' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobResourceLimit$MaxParallelOfTests' => 'Defines the maximum number of parallel load tests.
', ], ], 'MaxParallelTrainingJobs' => [ 'base' => NULL, 'refs' => [ 'ResourceLimits$MaxParallelTrainingJobs' => 'The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.
', ], ], 'MaxPayloadInMB' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$MaxPayloadInMB' => 'The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB
must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6
MB.
The value of MaxPayloadInMB
cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms
parameter, the value of (MaxConcurrentTransforms * MaxPayloadInMB)
also cannot exceed 100 MB.
For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0
. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.
The maximum payload size, in MB, used in the transform job.
', 'TransformJob$MaxPayloadInMB' => 'The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB
must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.
The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
', ], ], 'MaxPendingTimeInSeconds' => [ 'base' => 'Maximum job scheduler pending time in seconds.', 'refs' => [ 'StoppingCondition$MaxPendingTimeInSeconds' => 'The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.
', ], ], 'MaxPercentageOfInputDatasetLabeled' => [ 'base' => NULL, 'refs' => [ 'LabelingJobStoppingConditions$MaxPercentageOfInputDatasetLabeled' => 'The maximum number of input data objects that should be labeled.
', ], ], 'MaxResults' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$MaxResults' => 'The maximum number of actions to return in the response. The default value is 10.
', 'ListAlgorithmsInput$MaxResults' => 'The maximum number of algorithms to return in the response.
', 'ListAliasesRequest$MaxResults' => 'The maximum number of aliases to return.
', 'ListAppImageConfigsRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The maximum number of artifacts to return in the response. The default value is 10.
', 'ListAssociationsRequest$MaxResults' => 'The maximum number of associations to return in the response. The default value is 10.
', 'ListClusterNodesRequest$MaxResults' => 'The maximum number of nodes to return in the response.
', 'ListClustersRequest$MaxResults' => 'Set the maximum number of SageMaker HyperPod clusters to list.
', 'ListCodeRepositoriesInput$MaxResults' => 'The maximum number of Git repositories to return in the response.
', 'ListCompilationJobsRequest$MaxResults' => 'The maximum number of model compilation jobs to return in the response.
', 'ListContextsRequest$MaxResults' => 'The maximum number of contexts to return in the response. The default value is 10.
', 'ListDataQualityJobDefinitionsRequest$MaxResults' => 'The maximum number of data quality monitoring job definitions to return in the response.
', 'ListDomainsRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The maximum number of training jobs to return in the response.
', 'ListEndpointsInput$MaxResults' => 'The maximum number of endpoints to return in the response. This value defaults to 10.
', 'ListExperimentsRequest$MaxResults' => 'The maximum number of experiments to return in the response. The default value is 10.
', 'ListFlowDefinitionsRequest$MaxResults' => 'The total number of items to return. If the total number of available items is more than the value specified in MaxResults
, then a NextToken
will be provided in the output that you can use to resume pagination.
The maximum number of hub content versions to list.
', 'ListHubContentsRequest$MaxResults' => 'The maximum amount of hub content to list.
', 'ListHubsRequest$MaxResults' => 'The maximum number of hubs to list.
', 'ListHumanTaskUisRequest$MaxResults' => 'The total number of items to return. If the total number of available items is more than the value specified in MaxResults
, then a NextToken
will be provided in the output that you can use to resume pagination.
The maximum number of tuning jobs to return. The default value is 10.
', 'ListImageVersionsRequest$MaxResults' => 'The maximum number of versions to return in the response. The default value is 10.
', 'ListImagesRequest$MaxResults' => 'The maximum number of images to return in the response. The default value is 10.
', 'ListInferenceComponentsInput$MaxResults' => 'The maximum number of inference components to return in the response. This value defaults to 10.
', 'ListInferenceExperimentsRequest$MaxResults' => 'The maximum number of results to select.
', 'ListInferenceRecommendationsJobStepsRequest$MaxResults' => 'The maximum number of results to return.
', 'ListInferenceRecommendationsJobsRequest$MaxResults' => 'The maximum number of recommendations to return in the response.
', 'ListLabelingJobsForWorkteamRequest$MaxResults' => 'The maximum number of labeling jobs to return in each page of the response.
', 'ListLabelingJobsRequest$MaxResults' => 'The maximum number of labeling jobs to return in each page of the response.
', 'ListLineageGroupsRequest$MaxResults' => 'The maximum number of endpoints to return in the response. This value defaults to 10.
', 'ListModelBiasJobDefinitionsRequest$MaxResults' => 'The maximum number of model bias jobs to return in the response. The default value is 10.
', 'ListModelCardExportJobsRequest$MaxResults' => 'The maximum number of model card export jobs to list.
', 'ListModelCardVersionsRequest$MaxResults' => 'The maximum number of model card versions to list.
', 'ListModelCardsRequest$MaxResults' => 'The maximum number of model cards to list.
', 'ListModelExplainabilityJobDefinitionsRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListModelMetadataRequest$MaxResults' => 'The maximum number of models to return in the response.
', 'ListModelPackageGroupsInput$MaxResults' => 'The maximum number of results to return in the response.
', 'ListModelPackagesInput$MaxResults' => 'The maximum number of model packages to return in the response.
', 'ListModelQualityJobDefinitionsRequest$MaxResults' => 'The maximum number of results to return in a call to ListModelQualityJobDefinitions
.
The maximum number of models to return in the response.
', 'ListMonitoringAlertHistoryRequest$MaxResults' => 'The maximum number of results to display. The default is 100.
', 'ListMonitoringAlertsRequest$MaxResults' => 'The maximum number of results to display. The default is 100.
', 'ListMonitoringExecutionsRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListMonitoringSchedulesRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListNotebookInstanceLifecycleConfigsInput$MaxResults' => 'The maximum number of lifecycle configurations to return in the response.
', 'ListNotebookInstancesInput$MaxResults' => 'The maximum number of notebook instances to return.
', 'ListPipelineExecutionStepsRequest$MaxResults' => 'The maximum number of pipeline execution steps to return in the response.
', 'ListPipelineExecutionsRequest$MaxResults' => 'The maximum number of pipeline executions to return in the response.
', 'ListPipelineParametersForExecutionRequest$MaxResults' => 'The maximum number of parameters to return in the response.
', 'ListPipelinesRequest$MaxResults' => 'The maximum number of pipelines to return in the response.
', 'ListProcessingJobsRequest$MaxResults' => 'The maximum number of processing jobs to return in the response.
', 'ListProjectsInput$MaxResults' => 'The maximum number of projects to return in the response.
', 'ListResourceCatalogsRequest$MaxResults' => ' The maximum number of results returned by ListResourceCatalogs
.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The maximum number of work teams to return in each page of the response.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$MaxResults' => 'The maximum number of training jobs to return. The default value is 10.
', 'ListTrainingJobsRequest$MaxResults' => 'The maximum number of training jobs to return in the response.
', 'ListTransformJobsRequest$MaxResults' => 'The maximum number of transform jobs to return in the response. The default value is 10
.
The maximum number of components to return in the response. The default value is 10.
', 'ListTrialsRequest$MaxResults' => 'The maximum number of trials to return in the response. The default value is 10.
', 'ListUserProfilesRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken
is provided in the response. To resume pagination, provide the NextToken
value in the as part of a subsequent call. The default value is 10.
The maximum number of workforces returned in the response.
', 'ListWorkteamsRequest$MaxResults' => 'The maximum number of work teams to return in each page of the response.
', 'SearchRequest$MaxResults' => 'The maximum number of results to return.
', ], ], 'MaxRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'StoppingCondition$MaxRuntimeInSeconds' => 'The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.
For compilation jobs, if the job does not complete during this time, a TimeOut
error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.
For all other jobs, if the job does not complete during this time, SageMaker ends the job. When RetryStrategy
is specified in the job request, MaxRuntimeInSeconds
specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.
The maximum time that a TrainingJob
can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.
The maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the StoppingCondition used by the CreateHyperParameterTuningJob action.
For job V2s (jobs created by calling CreateAutoMLJobV2
), this field controls the runtime of the job candidate.
For TextGenerationJobConfig problem types, the maximum time defaults to 72 hours (259200 seconds).
', ], ], 'MaxWaitTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'StoppingCondition$MaxWaitTimeInSeconds' => 'The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds
. If the job does not complete during this time, SageMaker ends the job.
When RetryStrategy
is specified in the job request, MaxWaitTimeInSeconds
specifies the maximum time for all of the attempts in total, not each individual attempt.
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in TerminationWaitInSeconds
and WaitIntervalInSeconds
.
The time limit for the total deployment. Exceeding this limit causes a timeout.
', ], ], 'MaximumRetryAttempts' => [ 'base' => NULL, 'refs' => [ 'RetryStrategy$MaximumRetryAttempts' => 'The number of times to retry the job. When the job is retried, it\'s SecondaryStatus
is changed to STARTING
.
The media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.
', ], ], 'MemberDefinition' => [ 'base' => 'Defines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.
', 'refs' => [ 'MemberDefinitions$member' => NULL, ], ], 'MemberDefinitions' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$MemberDefinitions' => 'A list of MemberDefinition
objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition
. Do not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition
objects that make up the member definition must have the same ClientId
and UserPool
values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition
by listing those groups in Groups
.
A list of MemberDefinition
objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition
. You should not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition
objects that make up the member definition must have the same ClientId
and UserPool
values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition
by listing those groups in Groups
. Be aware that user groups that are already in the work team must also be listed in Groups
when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.
A list of MemberDefinition
objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition
.
The minimum MB of memory to allocate to run a model that you assign to an inference component.
', 'InferenceComponentComputeResourceRequirements$MaxMemoryRequiredInMb' => 'The maximum MB of memory to allocate to run a model that you assign to an inference component.
', ], ], 'MetadataProperties' => [ 'base' => 'Metadata properties of the tracking entity, trial, or trial component.
', 'refs' => [ 'CreateActionRequest$MetadataProperties' => NULL, 'CreateArtifactRequest$MetadataProperties' => NULL, 'CreateModelPackageInput$MetadataProperties' => NULL, 'CreateTrialComponentRequest$MetadataProperties' => NULL, 'CreateTrialRequest$MetadataProperties' => NULL, 'DescribeActionResponse$MetadataProperties' => NULL, 'DescribeArtifactResponse$MetadataProperties' => NULL, 'DescribeModelPackageOutput$MetadataProperties' => NULL, 'DescribeTrialComponentResponse$MetadataProperties' => NULL, 'DescribeTrialResponse$MetadataProperties' => NULL, 'ModelPackage$MetadataProperties' => 'Metadata properties of the tracking entity, trial, or trial component.
', 'Trial$MetadataProperties' => NULL, 'TrialComponent$MetadataProperties' => NULL, ], ], 'MetadataPropertyValue' => [ 'base' => NULL, 'refs' => [ 'MetadataProperties$CommitId' => 'The commit ID.
', 'MetadataProperties$Repository' => 'The repository.
', 'MetadataProperties$GeneratedBy' => 'The entity this entity was generated by.
', 'MetadataProperties$ProjectId' => 'The project ID.
', ], ], 'MetricData' => [ 'base' => 'The name, value, and date and time of a metric that was emitted to Amazon CloudWatch.
', 'refs' => [ 'FinalMetricDataList$member' => NULL, ], ], 'MetricDataList' => [ 'base' => NULL, 'refs' => [ 'CandidateProperties$CandidateMetrics' => 'Information about the candidate metrics for an AutoML job.
', ], ], 'MetricDatum' => [ 'base' => 'Information about the metric for a candidate produced by an AutoML job.
', 'refs' => [ 'MetricDataList$member' => NULL, ], ], 'MetricDefinition' => [ 'base' => 'Specifies a metric that the training algorithm writes to stderr
or stdout
. You can view these logs to understand how your training job performs and check for any errors encountered during training. SageMaker hyperparameter tuning captures all defined metrics. Specify one of the defined metrics to use as an objective metric using the TuningObjective parameter in the HyperParameterTrainingJobDefinition
API to evaluate job performance during hyperparameter tuning.
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
', 'HyperParameterAlgorithmSpecification$MetricDefinitions' => 'An array of MetricDefinition objects that specify the metrics that the algorithm emits.
', 'TrainingSpecification$MetricDefinitions' => 'A list of MetricDefinition
objects, which are used for parsing metrics generated by the algorithm.
The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the metrics for XGBoost as an example. You can also use a custom algorithm for training and define your own metrics. For more information, see Define metrics and environment variables.
', 'HyperParameterTuningJobObjective$MetricName' => 'The name of the metric to use for the objective metric.
', 'MetricData$MetricName' => 'The name of the metric.
', 'MetricDefinition$Name' => 'The name of the metric.
', 'TrialComponentMetricSummary$MetricName' => 'The name of the metric.
', ], ], 'MetricRegex' => [ 'base' => NULL, 'refs' => [ 'MetricDefinition$Regex' => 'A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see Defining metrics and environment variables.
', ], ], 'MetricSetSource' => [ 'base' => NULL, 'refs' => [ 'MetricDatum$Set' => 'The dataset split from which the AutoML job produced the metric.
', ], ], 'MetricSpecification' => [ 'base' => 'An object containing information about a metric.
', 'refs' => [ 'TargetTrackingScalingPolicyConfiguration$MetricSpecification' => 'An object containing information about a metric.
', ], ], 'MetricValue' => [ 'base' => NULL, 'refs' => [ 'FinalAutoMLJobObjectiveMetric$Value' => 'The value of the metric with the best result.
', 'FinalHyperParameterTuningJobObjectiveMetric$Value' => 'The value of the objective metric.
', ], ], 'MetricsSource' => [ 'base' => 'Details about the metrics source.
', 'refs' => [ 'Bias$Report' => 'The bias report for a model
', 'Bias$PreTrainingReport' => 'The pre-training bias report for a model.
', 'Bias$PostTrainingReport' => 'The post-training bias report for a model.
', 'DriftCheckBias$PreTrainingConstraints' => 'The pre-training constraints.
', 'DriftCheckBias$PostTrainingConstraints' => 'The post-training constraints.
', 'DriftCheckExplainability$Constraints' => 'The drift check explainability constraints.
', 'DriftCheckModelDataQuality$Statistics' => 'The drift check model data quality statistics.
', 'DriftCheckModelDataQuality$Constraints' => 'The drift check model data quality constraints.
', 'DriftCheckModelQuality$Statistics' => 'The drift check model quality statistics.
', 'DriftCheckModelQuality$Constraints' => 'The drift check model quality constraints.
', 'Explainability$Report' => 'The explainability report for a model.
', 'ModelDataQuality$Statistics' => 'Data quality statistics for a model.
', 'ModelDataQuality$Constraints' => 'Data quality constraints for a model.
', 'ModelQuality$Statistics' => 'Model quality statistics.
', 'ModelQuality$Constraints' => 'Model quality constraints.
', ], ], 'MinimumInstanceMetadataServiceVersion' => [ 'base' => NULL, 'refs' => [ 'InstanceMetadataServiceConfiguration$MinimumInstanceMetadataServiceVersion' => 'Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance
, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance
, there is no default.
The properties of a model as returned by the Search API.
', 'refs' => [ 'ModelDashboardModel$Model' => 'A model displayed in the Model Dashboard.
', ], ], 'ModelAccessConfig' => [ 'base' => 'The access configuration file to control access to the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig
.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
If you are an AutoML user, see the Optional Parameters section of Create an AutoML job to fine-tune text generation models using the API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML API.
Specifies the access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig
. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The approval status of the model.
', 'CreateModelPackageInput$ModelApprovalStatus' => 'Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to Approved
to deploy the model.
The approval status of the model package.
', 'ListModelPackagesInput$ModelApprovalStatus' => 'A filter that returns only the model packages with the specified approval status.
', 'ModelPackage$ModelApprovalStatus' => 'The approval status of the model. This can be one of the following values.
APPROVED
- The model is approved
REJECTED
- The model is rejected.
PENDING_MANUAL_APPROVAL
- The model is waiting for manual approval.
The approval status of the model. This can be one of the following values.
APPROVED
- The model is approved
REJECTED
- The model is rejected.
PENDING_MANUAL_APPROVAL
- The model is waiting for manual approval.
The approval status of the model.
', ], ], 'ModelArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelOutput$ModelArn' => 'The ARN of the model created in SageMaker.
', 'DescribeModelOutput$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', 'LabelingJobAlgorithmsConfig$InitialActiveLearningModelArn' => 'At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
', 'LabelingJobOutput$FinalActiveLearningModelArn' => 'The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.
', 'Model$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', 'ModelSummary$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', ], ], 'ModelArtifacts' => [ 'base' => 'Provides information about the location that is configured for storing model artifacts.
Model artifacts are the output that results from training a model, and typically consist of trained parameters, a model definition that describes how to compute inferences, and other metadata.
', 'refs' => [ 'DescribeCompilationJobResponse$ModelArtifacts' => 'Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.
', 'DescribeTrainingJobResponse$ModelArtifacts' => 'Information about the Amazon S3 location that is configured for storing model artifacts.
', 'TrainingJob$ModelArtifacts' => 'Information about the Amazon S3 location that is configured for storing model artifacts.
', ], ], 'ModelBiasAppSpecification' => [ 'base' => 'Docker container image configuration object for the model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasAppSpecification' => 'Configures the model bias job to run a specified Docker container image.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasAppSpecification' => 'Configures the model bias job to run a specified Docker container image.
', ], ], 'ModelBiasBaselineConfig' => [ 'base' => 'The configuration for a baseline model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasBaselineConfig' => 'The baseline configuration for a model bias job.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasBaselineConfig' => 'The baseline configuration for a model bias job.
', ], ], 'ModelBiasJobInput' => [ 'base' => 'Inputs for the model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasJobInput' => 'Inputs for the model bias job.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasJobInput' => 'Inputs for the model bias job.
', ], ], 'ModelCacheSetting' => [ 'base' => NULL, 'refs' => [ 'MultiModelConfig$ModelCacheSetting' => 'Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to Disabled
.
An Amazon SageMaker Model Card.
', 'refs' => [ 'SearchRecord$ModelCard' => 'An Amazon SageMaker Model Card that documents details about a machine learning model.
', ], ], 'ModelCardArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the successfully created model card.
', 'DescribeModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCard$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCardSummary$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCardVersionSummary$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelDashboardModelCard$ModelCardArn' => 'The Amazon Resource Name (ARN) for a model card.
', 'UpdateModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the updated model card.
', ], ], 'ModelCardContent' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardRequest$Content' => 'The content of the model card. Content must be in model card JSON schema and provided as a string.
', 'DescribeModelCardResponse$Content' => 'The content of the model card.
', 'ModelCard$Content' => 'The content of the model card. Content uses the model card JSON schema and provided as a string.
', 'UpdateModelCardRequest$Content' => 'The updated model card content. Content must be in model card JSON schema and provided as a string.
When updating model card content, be sure to include the full content and not just updated content.
', ], ], 'ModelCardExportArtifacts' => [ 'base' => 'The artifacts of the model card export job.
', 'refs' => [ 'DescribeModelCardExportJobResponse$ExportArtifacts' => 'The exported model card artifacts.
', ], ], 'ModelCardExportJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobResponse$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', 'DescribeModelCardExportJobRequest$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job to describe.
', 'DescribeModelCardExportJobResponse$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', 'ModelCardExportJobSummary$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', ], ], 'ModelCardExportJobSortBy' => [ 'base' => 'Attribute by which to sort returned export jobs.', 'refs' => [ 'ListModelCardExportJobsRequest$SortBy' => 'Sort model card export jobs by either name or creation time. Sorts by creation time by default.
', ], ], 'ModelCardExportJobSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListModelCardExportJobsRequest$SortOrder' => 'Sort model card export jobs by ascending or descending order.
', ], ], 'ModelCardExportJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeModelCardExportJobResponse$Status' => 'The completion status of the model card export job.
InProgress
: The model card export job is in progress.
Completed
: The model card export job is complete.
Failed
: The model card export job failed. To see the reason for the failure, see the FailureReason
field in the response to a DescribeModelCardExportJob
call.
Only list model card export jobs with the specified status.
', 'ModelCardExportJobSummary$Status' => 'The completion status of the model card export job.
', ], ], 'ModelCardExportJobSummary' => [ 'base' => 'The summary of the Amazon SageMaker Model Card export job.
', 'refs' => [ 'ModelCardExportJobSummaryList$member' => NULL, ], ], 'ModelCardExportJobSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardExportJobsResponse$ModelCardExportJobSummaries' => 'The summaries of the listed model card export jobs.
', ], ], 'ModelCardExportOutputConfig' => [ 'base' => 'Configure the export output details for an Amazon SageMaker Model Card.
', 'refs' => [ 'CreateModelCardExportJobRequest$OutputConfig' => 'The model card output configuration that specifies the Amazon S3 path for exporting.
', 'DescribeModelCardExportJobResponse$OutputConfig' => 'The export output details for the model card.
', ], ], 'ModelCardNameOrArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to export.
', 'DescribeModelCardRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to describe.
', 'ListModelCardVersionsRequest$ModelCardName' => 'List model card versions for the model card with the specified name or Amazon Resource Name (ARN).
', 'UpdateModelCardRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to update.
', ], ], 'ModelCardProcessingStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeModelCardResponse$ModelCardProcessingStatus' => 'The processing status of model card deletion. The ModelCardProcessingStatus
updates throughout the different deletion steps.
DeletePending
: Model card deletion request received.
DeleteInProgress
: Model card deletion is in progress.
ContentDeleted
: Deleted model card content.
ExportJobsDeleted
: Deleted all export jobs associated with the model card.
DeleteCompleted
: Successfully deleted the model card.
DeleteFailed
: The model card failed to delete.
Configure the security settings to protect model card data.
', 'refs' => [ 'CreateModelCardRequest$SecurityConfig' => 'An optional Key Management Service key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with highly sensitive data.
', 'DescribeModelCardResponse$SecurityConfig' => 'The security configuration used to protect model card content.
', 'ModelCard$SecurityConfig' => 'The security configuration used to protect model card data.
', 'ModelDashboardModelCard$SecurityConfig' => 'The KMS Key ID (KMSKeyId
) for encryption of model card information.
Sort model cards by either name or creation time. Sorts by creation time by default.
', ], ], 'ModelCardSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsRequest$SortOrder' => 'Sort model card versions by ascending or descending order.
', 'ListModelCardsRequest$SortOrder' => 'Sort model cards by ascending or descending order.
', ], ], 'ModelCardStatus' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardRequest$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
Only list model card versions with the specified approval status.
', 'ListModelCardsRequest$ModelCardStatus' => 'Only list model cards with the specified approval status.
', 'ModelCard$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The model card status.
', 'UpdateModelCardRequest$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft
: The model card is a work in progress.
PendingReview
: The model card is pending review.
Approved
: The model card is approved.
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
A summary of the model card.
', 'refs' => [ 'ModelCardSummaryList$member' => NULL, ], ], 'ModelCardSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardsResponse$ModelCardSummaries' => 'The summaries of the listed model cards.
', ], ], 'ModelCardVersionSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsRequest$SortBy' => 'Sort listed model card versions by version. Sorts by version by default.
', ], ], 'ModelCardVersionSummary' => [ 'base' => 'A summary of a specific version of the model card.
', 'refs' => [ 'ModelCardVersionSummaryList$member' => NULL, ], ], 'ModelCardVersionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsResponse$ModelCardVersionSummaryList' => 'The summaries of the listed versions of the model card.
', ], ], 'ModelClientConfig' => [ 'base' => 'Configures the timeout and maximum number of retries for processing a transform job invocation.
', 'refs' => [ 'CreateTransformJobRequest$ModelClientConfig' => 'Configures the timeout and maximum number of retries for processing a transform job invocation.
', 'DescribeTransformJobResponse$ModelClientConfig' => 'The timeout and maximum number of retries for processing a transform job invocation.
', 'TransformJob$ModelClientConfig' => NULL, ], ], 'ModelCompressionType' => [ 'base' => NULL, 'refs' => [ 'S3ModelDataSource$CompressionType' => 'Specifies how the ML model data is prepared.
If you choose Gzip
and choose S3Object
as the value of S3DataType
, S3Uri
identifies an object that is a gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during model deployment.
If you choose None
and chooose S3Object
as the value of S3DataType
, S3Uri
identifies an object that represents an uncompressed ML model to deploy.
If you choose None and choose S3Prefix
as the value of S3DataType
, S3Uri
identifies a key name prefix, under which all objects represents the uncompressed ML model to deploy.
If you choose None, then SageMaker will follow rules below when creating model data files under /opt/ml/model directory for use by your inference code:
If you choose S3Object
as the value of S3DataType
, then SageMaker will split the key of the S3 object referenced by S3Uri
by slash (/), and use the last part as the filename of the file holding the content of the S3 object.
If you choose S3Prefix
as the value of S3DataType
, then for each S3 object under the key name pefix referenced by S3Uri
, SageMaker will trim its key by the prefix, and use the remainder as the path (relative to /opt/ml/model
) of the file holding the content of the S3 object. SageMaker will split the remainder by slash (/), using intermediate parts as directory names and the last part as filename of the file holding the content of the S3 object.
Do not use any of the following as file names or directory names:
An empty or blank string
A string which contains null bytes
A string longer than 255 bytes
A single dot (.
)
A double dot (..
)
Ambiguous file names will result in model deployment failure. For example, if your uncompressed ML model consists of two S3 objects s3://mybucket/model/weights
and s3://mybucket/model/weights/part1
and you specify s3://mybucket/model/
as the value of S3Uri
and S3Prefix
as the value of S3DataType
, then it will result in name clash between /opt/ml/model/weights
(a regular file) and /opt/ml/model/weights/
(a directory).
Do not organize the model artifacts in S3 console using folders. When you create a folder in S3 console, S3 creates a 0-byte object with a key set to the folder name you provide. They key of the 0-byte object ends with a slash (/) which violates SageMaker restrictions on model artifact file names, leading to model deployment failure.
Defines the model configuration. Includes the specification name and environment parameters.
', 'refs' => [ 'InferenceRecommendation$ModelConfiguration' => 'Defines the model configuration.
', 'RecommendationJobInferenceBenchmark$ModelConfiguration' => NULL, ], ], 'ModelDashboardEndpoint' => [ 'base' => 'An endpoint that hosts a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardEndpoints$member' => NULL, ], ], 'ModelDashboardEndpoints' => [ 'base' => NULL, 'refs' => [ 'ModelDashboardModel$Endpoints' => 'The endpoints that host a model.
', ], ], 'ModelDashboardIndicatorAction' => [ 'base' => 'An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into InAlert
status.
An alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert
status.
A model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'SearchRecord$Model' => NULL, ], ], 'ModelDashboardModelCard' => [ 'base' => 'The model card for a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardModel$ModelCard' => 'The model card for a model.
', ], ], 'ModelDashboardMonitoringSchedule' => [ 'base' => 'A monitoring schedule for a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardMonitoringSchedules$member' => NULL, ], ], 'ModelDashboardMonitoringSchedules' => [ 'base' => NULL, 'refs' => [ 'ModelDashboardModel$MonitoringSchedules' => 'The monitoring schedules for a model.
', ], ], 'ModelDataQuality' => [ 'base' => 'Data quality constraints and statistics for a model.
', 'refs' => [ 'ModelMetrics$ModelDataQuality' => 'Metrics that measure the quality of the input data for a model.
', ], ], 'ModelDataSource' => [ 'base' => 'Specifies the location of ML model data to deploy. If specified, you must specify one and only one of the available data sources.
', 'refs' => [ 'ContainerDefinition$ModelDataSource' => 'Specifies the location of ML model data to deploy.
Currently you cannot use ModelDataSource
in conjunction with SageMaker batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker Marketplace.
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'refs' => [ 'CreateAutoMLJobRequest$ModelDeployConfig' => 'Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'CreateAutoMLJobV2Request$ModelDeployConfig' => 'Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'DescribeAutoMLJobResponse$ModelDeployConfig' => 'Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
', 'DescribeAutoMLJobV2Response$ModelDeployConfig' => 'Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
', ], ], 'ModelDeployResult' => [ 'base' => 'Provides information about the endpoint of the model deployment.
', 'refs' => [ 'DescribeAutoMLJobResponse$ModelDeployResult' => 'Provides information about endpoint for the model deployment.
', 'DescribeAutoMLJobV2Response$ModelDeployResult' => 'Provides information about endpoint for the model deployment.
', ], ], 'ModelDigests' => [ 'base' => 'Provides information to verify the integrity of stored model artifacts.
', 'refs' => [ 'DescribeCompilationJobResponse$ModelDigests' => 'Provides a BLAKE2 hash value that identifies the compiled model artifacts in Amazon S3.
', ], ], 'ModelExplainabilityAppSpecification' => [ 'base' => 'Docker container image configuration object for the model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityAppSpecification' => 'Configures the model explainability job to run a specified Docker container image.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityAppSpecification' => 'Configures the model explainability job to run a specified Docker container image.
', ], ], 'ModelExplainabilityBaselineConfig' => [ 'base' => 'The configuration for a baseline model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityBaselineConfig' => 'The baseline configuration for a model explainability job.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityBaselineConfig' => 'The baseline configuration for a model explainability job.
', ], ], 'ModelExplainabilityJobInput' => [ 'base' => 'Inputs for the model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityJobInput' => 'Inputs for the model explainability job.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityJobInput' => 'Inputs for the model explainability job.
', ], ], 'ModelInfrastructureConfig' => [ 'base' => 'The configuration for the infrastructure that the model will be deployed to.
', 'refs' => [ 'ModelVariantConfig$InfrastructureConfig' => 'The configuration for the infrastructure that the model will be deployed to.
', 'ModelVariantConfigSummary$InfrastructureConfig' => 'The configuration of the infrastructure that the model has been deployed to.
', ], ], 'ModelInfrastructureType' => [ 'base' => NULL, 'refs' => [ 'ModelInfrastructureConfig$InfrastructureType' => 'The inference option to which to deploy your model. Possible values are the following:
RealTime
: Deploy to real-time inference.
Input object for the model.
', 'refs' => [ 'ModelPackageContainerDefinition$ModelInput' => 'A structure with Model Input details.
', ], ], 'ModelInsightsLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$ModelInsights' => 'The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
', ], ], 'ModelLatencyThreshold' => [ 'base' => 'The model latency threshold.
', 'refs' => [ 'ModelLatencyThresholds$member' => NULL, ], ], 'ModelLatencyThresholds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobStoppingConditions$ModelLatencyThresholds' => 'The interval of time taken by a model to respond as viewed from SageMaker. The interval includes the local communication time taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
', ], ], 'ModelMetadataFilter' => [ 'base' => 'Part of the search expression. You can specify the name and value (domain, task, framework, framework version, task, and model).
', 'refs' => [ 'ModelMetadataFilters$member' => NULL, ], ], 'ModelMetadataFilterType' => [ 'base' => NULL, 'refs' => [ 'ModelMetadataFilter$Name' => 'The name of the of the model to filter by.
', ], ], 'ModelMetadataFilters' => [ 'base' => NULL, 'refs' => [ 'ModelMetadataSearchExpression$Filters' => 'A list of filter objects.
', ], ], 'ModelMetadataSearchExpression' => [ 'base' => 'One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results
', 'refs' => [ 'ListModelMetadataRequest$SearchExpression' => 'One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results. Specify the Framework, FrameworkVersion, Domain or Task to filter supported. Filter names and values are case-sensitive.
', ], ], 'ModelMetadataSummaries' => [ 'base' => NULL, 'refs' => [ 'ListModelMetadataResponse$ModelMetadataSummaries' => 'A structure that holds model metadata.
', ], ], 'ModelMetadataSummary' => [ 'base' => 'A summary of the model metadata.
', 'refs' => [ 'ModelMetadataSummaries$member' => NULL, ], ], 'ModelMetrics' => [ 'base' => 'Contains metrics captured from a model.
', 'refs' => [ 'CreateModelPackageInput$ModelMetrics' => 'A structure that contains model metrics reports.
', 'DescribeModelPackageOutput$ModelMetrics' => 'Metrics for the model.
', 'ModelPackage$ModelMetrics' => 'Metrics for the model.
', ], ], 'ModelName' => [ 'base' => NULL, 'refs' => [ 'CreateModelInput$ModelName' => 'The name of the new model.
', 'CreateTransformJobRequest$ModelName' => 'The name of the model that you want to use for the transform job. ModelName
must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.
The name of the model to delete.
', 'DescribeModelInput$ModelName' => 'The name of the model.
', 'DescribeModelOutput$ModelName' => 'Name of the SageMaker model.
', 'DescribeTransformJobResponse$ModelName' => 'The name of the model used in the transform job.
', 'InferenceComponentSpecification$ModelName' => 'The name of an existing SageMaker model object in your account that you want to deploy with the inference component.
', 'InferenceComponentSpecificationSummary$ModelName' => 'The name of the SageMaker model object that is deployed with the inference component.
', 'InferenceRecommendationsJob$ModelName' => 'The name of the created model.
', 'ListInferenceRecommendationsJobsRequest$ModelNameEquals' => 'A filter that returns only jobs that were created for this model.
', 'Model$ModelName' => 'The name of the model.
', 'ModelSummary$ModelName' => 'The name of the model that you want a summary for.
', 'ModelVariantConfig$ModelName' => 'The name of the Amazon SageMaker Model entity.
', 'ModelVariantConfigSummary$ModelName' => 'The name of the Amazon SageMaker Model entity.
', 'ProductionVariant$ModelName' => 'The name of the model that you want to host. This is the name that you specified when creating the model.
', 'RecommendationJobInputConfig$ModelName' => 'The name of the created model.
', 'TransformJob$ModelName' => 'The name of the model associated with the transform job.
', ], ], 'ModelNameContains' => [ 'base' => NULL, 'refs' => [ 'ListModelsInput$NameContains' => 'A string in the model name. This filter returns only models whose name contains the specified string.
', ], ], 'ModelPackage' => [ 'base' => 'A versioned model that can be deployed for SageMaker inference.
', 'refs' => [ 'SearchRecord$ModelPackage' => NULL, ], ], 'ModelPackageArn' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageErrorMap$key' => NULL, 'BatchDescribeModelPackageSummary$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'CreateCompilationJobRequest$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn
or an InputConfig
object in the request syntax. The presence of both objects in the CreateCompilationJob
request will return an exception.
The Amazon Resource Name (ARN) of the new model package.
', 'DescribeCompilationJobResponse$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of the versioned model package that was provided to SageMaker Neo when you initiated a compilation job.
', 'DescribeModelPackageOutput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'InferenceRecommendationsJob$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package.
', 'ListInferenceRecommendationsJobsRequest$ModelPackageVersionArnEquals' => 'A filter that returns only jobs that were created for this versioned model package.
', 'ModelPackage$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'ModelPackageArnList$member' => NULL, 'ModelPackageSummaries$key' => NULL, 'ModelPackageSummary$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'RecommendationJobInputConfig$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package.
', 'UpdateModelPackageInput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'UpdateModelPackageOutput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model.
', ], ], 'ModelPackageArnList' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageInput$ModelPackageArnList' => 'The list of Amazon Resource Name (ARN) of the model package groups.
', ], ], 'ModelPackageContainerDefinition' => [ 'base' => 'Describes the Docker container for the model package.
', 'refs' => [ 'ModelPackageContainerDefinitionList$member' => NULL, ], ], 'ModelPackageContainerDefinitionList' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Containers' => 'The Amazon ECR registry path of the Docker image that contains the inference code.
', 'InferenceSpecification$Containers' => 'The Amazon ECR registry path of the Docker image that contains the inference code.
', ], ], 'ModelPackageFrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'ModelPackageContainerDefinition$FrameworkVersion' => 'The framework version of the Model Package Container Image.
', ], ], 'ModelPackageGroup' => [ 'base' => 'A group of versioned models in the model registry.
', 'refs' => [ 'SearchRecord$ModelPackageGroup' => NULL, ], ], 'ModelPackageGroupArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageGroupOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'ModelPackageGroup$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'PutModelPackageGroupPolicyOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model package group.
', ], ], 'ModelPackageGroupSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelPackageGroupsInput$SortBy' => 'The field to sort results by. The default is CreationTime
.
The status of the model group.
', 'ModelPackageGroup$ModelPackageGroupStatus' => 'The status of the model group. This can be one of the following values.
PENDING
- The model group is pending being created.
IN_PROGRESS
- The model group is in the process of being created.
COMPLETED
- The model group was successfully created.
FAILED
- The model group failed.
DELETING
- The model group is in the process of being deleted.
DELETE_FAILED
- SageMaker failed to delete the model group.
The status of the model group.
', ], ], 'ModelPackageGroupSummary' => [ 'base' => 'Summary information about a model group.
', 'refs' => [ 'ModelPackageGroupSummaryList$member' => NULL, ], ], 'ModelPackageGroupSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelPackageGroupsOutput$ModelPackageGroupSummaryList' => 'A list of summaries of the model groups in your Amazon Web Services account.
', ], ], 'ModelPackageSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelPackagesInput$SortBy' => 'The parameter by which to sort the results. The default is CreationTime
.
The status of the mortgage package.
', 'DescribeModelPackageOutput$ModelPackageStatus' => 'The current status of the model package.
', 'ModelPackage$ModelPackageStatus' => 'The status of the model package. This can be one of the following values.
PENDING
- The model package is pending being created.
IN_PROGRESS
- The model package is in the process of being created.
COMPLETED
- The model package was successfully created.
FAILED
- The model package failed.
DELETING
- The model package is in the process of being deleted.
The overall status of the model package.
', ], ], 'ModelPackageStatusDetails' => [ 'base' => 'Specifies the validation and image scan statuses of the model package.
', 'refs' => [ 'DescribeModelPackageOutput$ModelPackageStatusDetails' => 'Details about the current status of the model package.
', 'ModelPackage$ModelPackageStatusDetails' => 'Specifies the validation and image scan statuses of the model package.
', ], ], 'ModelPackageStatusItem' => [ 'base' => 'Represents the overall status of a model package.
', 'refs' => [ 'ModelPackageStatusItemList$member' => NULL, ], ], 'ModelPackageStatusItemList' => [ 'base' => NULL, 'refs' => [ 'ModelPackageStatusDetails$ValidationStatuses' => 'The validation status of the model package.
', 'ModelPackageStatusDetails$ImageScanStatuses' => 'The status of the scan of the Docker image container for the model package.
', ], ], 'ModelPackageSummaries' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageOutput$ModelPackageSummaries' => 'The summaries for the model package versions
', ], ], 'ModelPackageSummary' => [ 'base' => 'Provides summary information about a model package.
', 'refs' => [ 'ModelPackageSummaryList$member' => NULL, ], ], 'ModelPackageSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelPackagesOutput$ModelPackageSummaryList' => 'An array of ModelPackageSummary
objects, each of which lists a model package.
A filter that returns only the model packages of the specified type. This can be one of the following values.
UNVERSIONED
- List only unversioined models. This is the default value if no ModelPackageType
is specified.
VERSIONED
- List only versioned models.
BOTH
- List both versioned and unversioned models.
Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
', 'refs' => [ 'ModelPackageValidationProfiles$member' => NULL, ], ], 'ModelPackageValidationProfiles' => [ 'base' => NULL, 'refs' => [ 'ModelPackageValidationSpecification$ValidationProfiles' => 'An array of ModelPackageValidationProfile
objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
Specifies batch transform jobs that SageMaker runs to validate your model package.
', 'refs' => [ 'CreateModelPackageInput$ValidationSpecification' => 'Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
', 'DescribeModelPackageOutput$ValidationSpecification' => 'Configurations for one or more transform jobs that SageMaker runs to test the model package.
', 'ModelPackage$ValidationSpecification' => 'Specifies batch transform jobs that SageMaker runs to validate your model package.
', ], ], 'ModelPackageVersion' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageSummary$ModelPackageVersion' => 'The version number of a versioned model.
', 'DescribeModelPackageOutput$ModelPackageVersion' => 'The version of the model package.
', 'ModelPackage$ModelPackageVersion' => 'The version number of a versioned model.
', 'ModelPackageSummary$ModelPackageVersion' => 'If the model package is a versioned model, the version of the model.
', ], ], 'ModelQuality' => [ 'base' => 'Model quality statistics and constraints.
', 'refs' => [ 'ModelMetrics$ModelQuality' => 'Metrics that measure the quality of a model.
', ], ], 'ModelQualityAppSpecification' => [ 'base' => 'Container image configuration object for the monitoring job.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityAppSpecification' => 'The container that runs the monitoring job.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityAppSpecification' => 'Configures the model quality job to run a specified Docker container image.
', ], ], 'ModelQualityBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityBaselineConfig' => 'Specifies the constraints and baselines for the monitoring job.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityBaselineConfig' => 'The baseline configuration for a model quality job.
', ], ], 'ModelQualityJobInput' => [ 'base' => 'The input for the model quality monitoring job. Currently endpoints are supported for input for model quality monitoring jobs.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityJobInput' => 'A list of the inputs that are monitored. Currently endpoints are supported.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityJobInput' => 'Inputs for the model quality job.
', ], ], 'ModelRegisterSettings' => [ 'base' => 'The model registry settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$ModelRegisterSettings' => 'The model registry settings for the SageMaker Canvas application.
', ], ], 'ModelSetupTime' => [ 'base' => NULL, 'refs' => [ 'RecommendationMetrics$ModelSetupTime' => 'The time it takes to launch new compute resources for a serverless endpoint. The time can vary depending on the model size, how long it takes to download the model, and the start-up time of the container.
NaN
indicates that the value is not available.
Sorts the list of results. The default is CreationTime
.
Metadata for Model steps.
', 'refs' => [ 'PipelineExecutionStepMetadata$Model' => 'The Amazon Resource Name (ARN) of the model that was created by this step execution.
', ], ], 'ModelSummary' => [ 'base' => 'Provides summary information about a model.
', 'refs' => [ 'ModelSummaryList$member' => NULL, ], ], 'ModelSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelsOutput$Models' => 'An array of ModelSummary
objects, each of which lists a model.
Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:
Promote
- Promote the shadow variant to a production variant
Remove
- Delete the variant
Retain
- Keep the variant as it is
Contains information about the deployment options of a model.
', 'refs' => [ 'ModelVariantConfigList$member' => NULL, ], ], 'ModelVariantConfigList' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$ModelVariants' => ' An array of ModelVariantConfig
objects. There is one for each variant in the inference experiment. Each ModelVariantConfig
object in the array describes the infrastructure configuration for the corresponding variant.
An array of ModelVariantConfig
objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig
describes the infrastructure configuration for deploying the corresponding variant.
An array of ModelVariantConfig
objects. There is one for each variant, whose infrastructure configuration you want to update.
Summary of the deployment configuration of a model.
', 'refs' => [ 'ModelVariantConfigSummaryList$member' => NULL, ], ], 'ModelVariantConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceExperimentResponse$ModelVariants' => ' An array of ModelVariantConfigSummary
objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary
object in the array describes the infrastructure configuration for deploying the corresponding variant.
The name of the variant.
', 'ModelVariantConfigSummary$VariantName' => 'The name of the variant.
', 'ShadowModeConfig$SourceModelVariantName' => 'The name of the production variant, which takes all the inference requests.
', 'ShadowModelVariantConfig$ShadowModelVariantName' => 'The name of the shadow variant.
', ], ], 'ModelVariantStatus' => [ 'base' => NULL, 'refs' => [ 'ModelVariantConfigSummary$Status' => 'The status of deployment for the model variant on the hosted inference endpoint.
Creating
- Amazon SageMaker is preparing the model variant on the hosted inference endpoint.
InService
- The model variant is running on the hosted inference endpoint.
Updating
- Amazon SageMaker is updating the model variant on the hosted inference endpoint.
Deleting
- Amazon SageMaker is deleting the model variant on the hosted inference endpoint.
Deleted
- The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.
A list of alert actions taken in response to an alert going into InAlert
status.
A list of alert actions taken in response to an alert going into InAlert
status.
An alert history for a model monitoring schedule.
', ], ], 'MonitoringAlertHistorySortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$SortBy' => 'The field used to sort results. The default is CreationTime
.
Provides summary information of an alert\'s history.
', 'refs' => [ 'MonitoringAlertHistoryList$member' => NULL, ], ], 'MonitoringAlertName' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$MonitoringAlertName' => 'The name of a monitoring alert.
', 'MonitoringAlertHistorySummary$MonitoringAlertName' => 'The name of a monitoring alert.
', 'MonitoringAlertSummary$MonitoringAlertName' => 'The name of a monitoring alert.
', 'UpdateMonitoringAlertRequest$MonitoringAlertName' => 'The name of a monitoring alert.
', 'UpdateMonitoringAlertResponse$MonitoringAlertName' => 'The name of a monitoring alert.
', ], ], 'MonitoringAlertStatus' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$StatusEquals' => 'A filter that retrieves only alerts with a specific status.
', 'MonitoringAlertHistorySummary$AlertStatus' => 'The current alert status of an alert.
', 'MonitoringAlertSummary$AlertStatus' => 'The current status of an alert.
', ], ], 'MonitoringAlertSummary' => [ 'base' => 'Provides summary information about a monitor alert.
', 'refs' => [ 'MonitoringAlertSummaryList$member' => NULL, ], ], 'MonitoringAlertSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertsResponse$MonitoringAlertSummaries' => 'A JSON array where each element is a summary for a monitoring alert.
', 'ModelDashboardMonitoringSchedule$MonitoringAlertSummaries' => 'A JSON array where each element is a summary for a monitoring alert.
', ], ], 'MonitoringAppSpecification' => [ 'base' => 'Container image configuration object for the monitoring job.
', 'refs' => [ 'MonitoringJobDefinition$MonitoringAppSpecification' => 'Configures the monitoring job to run a specified Docker container image.
', ], ], 'MonitoringBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'MonitoringJobDefinition$BaselineConfig' => 'Baseline configuration used to validate that the data conforms to the specified constraints and statistics
', ], ], 'MonitoringClusterConfig' => [ 'base' => 'Configuration for the cluster used to run model monitoring jobs.
', 'refs' => [ 'MonitoringResources$ClusterConfig' => 'The configuration for the cluster resources used to run the processing job.
', ], ], 'MonitoringConstraintsResource' => [ 'base' => 'The constraints resource for a monitoring job.
', 'refs' => [ 'DataQualityBaselineConfig$ConstraintsResource' => NULL, 'ModelBiasBaselineConfig$ConstraintsResource' => NULL, 'ModelExplainabilityBaselineConfig$ConstraintsResource' => NULL, 'ModelQualityBaselineConfig$ConstraintsResource' => NULL, 'MonitoringBaselineConfig$ConstraintsResource' => 'The baseline constraint file in Amazon S3 that the current monitoring job should validated against.
', ], ], 'MonitoringContainerArguments' => [ 'base' => NULL, 'refs' => [ 'DataQualityAppSpecification$ContainerArguments' => 'The arguments to send to the container that the monitoring job runs.
', 'ModelQualityAppSpecification$ContainerArguments' => 'An array of arguments for the container used to run the monitoring job.
', 'MonitoringAppSpecification$ContainerArguments' => 'An array of arguments for the container used to run the monitoring job.
', ], ], 'MonitoringCsvDatasetFormat' => [ 'base' => 'Represents the CSV dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Csv' => 'The CSV dataset used in the monitoring job.
', ], ], 'MonitoringDatapointsToAlert' => [ 'base' => NULL, 'refs' => [ 'MonitoringAlertSummary$DatapointsToAlert' => 'Within EvaluationPeriod
, how many execution failures will raise an alert.
Within EvaluationPeriod
, how many execution failures will raise an alert.
Represents the dataset format used when running a monitoring job.
', 'refs' => [ 'BatchTransformInput$DatasetFormat' => 'The dataset format for your batch transform job.
', ], ], 'MonitoringEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'DataQualityAppSpecification$Environment' => 'Sets the environment variables in the container that the monitoring job runs.
', 'ModelBiasAppSpecification$Environment' => 'Sets the environment variables in the Docker container.
', 'ModelExplainabilityAppSpecification$Environment' => 'Sets the environment variables in the Docker container.
', 'ModelQualityAppSpecification$Environment' => 'Sets the environment variables in the container that the monitoring job runs.
', 'MonitoringJobDefinition$Environment' => 'Sets the environment variables in the Docker container.
', ], ], 'MonitoringEvaluationPeriod' => [ 'base' => NULL, 'refs' => [ 'MonitoringAlertSummary$EvaluationPeriod' => 'The number of most recent monitoring executions to consider when evaluating alert status.
', 'UpdateMonitoringAlertRequest$EvaluationPeriod' => 'The number of most recent monitoring executions to consider when evaluating alert status.
', ], ], 'MonitoringExecutionSortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringExecutionsRequest$SortBy' => 'Whether to sort the results by the Status
, CreationTime
, or ScheduledTime
field. The default is CreationTime
.
Summary of information about the last monitoring job to run.
', 'refs' => [ 'DescribeMonitoringScheduleResponse$LastMonitoringExecutionSummary' => 'Describes metadata on the last execution to run, if there was one.
', 'ModelDashboardMonitoringSchedule$LastMonitoringExecutionSummary' => NULL, 'MonitoringExecutionSummaryList$member' => NULL, 'MonitoringSchedule$LastMonitoringExecutionSummary' => NULL, ], ], 'MonitoringExecutionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringExecutionsResponse$MonitoringExecutionSummaries' => 'A JSON array in which each element is a summary for a monitoring execution.
', ], ], 'MonitoringGroundTruthS3Input' => [ 'base' => 'The ground truth labels for the dataset used for the monitoring job.
', 'refs' => [ 'ModelBiasJobInput$GroundTruthS3Input' => 'Location of ground truth labels to use in model bias job.
', 'ModelQualityJobInput$GroundTruthS3Input' => 'The ground truth label provided for the model.
', ], ], 'MonitoringInput' => [ 'base' => 'The inputs for a monitoring job.
', 'refs' => [ 'MonitoringInputs$member' => NULL, ], ], 'MonitoringInputs' => [ 'base' => NULL, 'refs' => [ 'MonitoringJobDefinition$MonitoringInputs' => 'The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
', ], ], 'MonitoringJobDefinition' => [ 'base' => 'Defines the monitoring job.
', 'refs' => [ 'MonitoringScheduleConfig$MonitoringJobDefinition' => 'Defines the monitoring job.
', ], ], 'MonitoringJobDefinitionArn' => [ 'base' => NULL, 'refs' => [ 'CreateDataQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the job definition.
', 'CreateModelBiasJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model bias job.
', 'CreateModelExplainabilityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model explainability job.
', 'CreateModelQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model quality monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the data quality monitoring job definition.
', 'DescribeModelBiasJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model bias job.
', 'DescribeModelExplainabilityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model explainability job.
', 'DescribeModelQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model quality job.
', 'MonitoringJobDefinitionSummary$MonitoringJobDefinitionArn' => 'The Amazon Resource Name (ARN) of the monitoring job.
', ], ], 'MonitoringJobDefinitionName' => [ 'base' => NULL, 'refs' => [ 'CreateDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name for the monitoring job definition.
', 'CreateModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'CreateModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'CreateModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the monitoring job definition.
', 'DeleteDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the data quality monitoring job definition to delete.
', 'DeleteModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the model bias job definition to delete.
', 'DeleteModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition to delete.
', 'DeleteModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the model quality monitoring job definition to delete.
', 'DescribeDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the data quality monitoring job definition to describe.
', 'DescribeDataQualityJobDefinitionResponse$JobDefinitionName' => 'The name of the data quality monitoring job definition.
', 'DescribeModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelBiasJobDefinitionResponse$JobDefinitionName' => 'The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelExplainabilityJobDefinitionResponse$JobDefinitionName' => 'The name of the explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelQualityJobDefinitionResponse$JobDefinitionName' => 'The name of the quality job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'ListMonitoringExecutionsRequest$MonitoringJobDefinitionName' => 'Gets a list of the monitoring job runs of the specified monitoring job definitions.
', 'ListMonitoringSchedulesRequest$MonitoringJobDefinitionName' => 'Gets a list of the monitoring schedules for the specified monitoring job definition.
', 'MonitoringExecutionSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job.
', 'MonitoringJobDefinitionSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job.
', 'MonitoringScheduleConfig$MonitoringJobDefinitionName' => 'The name of the monitoring job definition to schedule.
', 'MonitoringScheduleSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job definition that the schedule is for.
', ], ], 'MonitoringJobDefinitionSortKey' => [ 'base' => NULL, 'refs' => [ 'ListDataQualityJobDefinitionsRequest$SortBy' => 'The field to sort results by. The default is CreationTime
.
Whether to sort results by the Name
or CreationTime
field. The default is CreationTime
.
Whether to sort results by the Name
or CreationTime
field. The default is CreationTime
.
The field to sort results by. The default is CreationTime
.
Summary information about a monitoring job.
', 'refs' => [ 'MonitoringJobDefinitionSummaryList$member' => NULL, ], ], 'MonitoringJobDefinitionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListDataQualityJobDefinitionsResponse$JobDefinitionSummaries' => 'A list of data quality monitoring job definitions.
', 'ListModelBiasJobDefinitionsResponse$JobDefinitionSummaries' => 'A JSON array in which each element is a summary for a model bias jobs.
', 'ListModelExplainabilityJobDefinitionsResponse$JobDefinitionSummaries' => 'A JSON array in which each element is a summary for a explainability bias jobs.
', 'ListModelQualityJobDefinitionsResponse$JobDefinitionSummaries' => 'A list of summaries of model quality monitoring job definitions.
', ], ], 'MonitoringJsonDatasetFormat' => [ 'base' => 'Represents the JSON dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Json' => 'The JSON dataset used in the monitoring job
', ], ], 'MonitoringMaxRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'MonitoringStoppingCondition$MaxRuntimeInSeconds' => 'The maximum runtime allowed in seconds.
The MaxRuntimeInSeconds
cannot exceed the frequency of the job. For data quality and model explainability, this can be up to 3600 seconds for an hourly schedule. For model bias and model quality hourly schedules, this can be up to 1800 seconds.
The networking configuration for the monitoring job.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$NetworkConfig' => 'Specifies networking configuration for the monitoring job.
', 'CreateModelBiasJobDefinitionRequest$NetworkConfig' => 'Networking options for a model bias job.
', 'CreateModelExplainabilityJobDefinitionRequest$NetworkConfig' => 'Networking options for a model explainability job.
', 'CreateModelQualityJobDefinitionRequest$NetworkConfig' => 'Specifies the network configuration for the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$NetworkConfig' => 'The networking configuration for the data quality monitoring job.
', 'DescribeModelBiasJobDefinitionResponse$NetworkConfig' => 'Networking options for a model bias job.
', 'DescribeModelExplainabilityJobDefinitionResponse$NetworkConfig' => 'Networking options for a model explainability job.
', 'DescribeModelQualityJobDefinitionResponse$NetworkConfig' => 'Networking options for a model quality job.
', ], ], 'MonitoringOutput' => [ 'base' => 'The output object for a monitoring job.
', 'refs' => [ 'MonitoringOutputs$member' => NULL, ], ], 'MonitoringOutputConfig' => [ 'base' => 'The output configuration for monitoring jobs.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityJobOutputConfig' => NULL, 'CreateModelBiasJobDefinitionRequest$ModelBiasJobOutputConfig' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityJobOutputConfig' => NULL, 'CreateModelQualityJobDefinitionRequest$ModelQualityJobOutputConfig' => NULL, 'DescribeDataQualityJobDefinitionResponse$DataQualityJobOutputConfig' => NULL, 'DescribeModelBiasJobDefinitionResponse$ModelBiasJobOutputConfig' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityJobOutputConfig' => NULL, 'DescribeModelQualityJobDefinitionResponse$ModelQualityJobOutputConfig' => NULL, 'MonitoringJobDefinition$MonitoringOutputConfig' => 'The array of outputs from the monitoring job to be uploaded to Amazon S3.
', ], ], 'MonitoringOutputs' => [ 'base' => NULL, 'refs' => [ 'MonitoringOutputConfig$MonitoringOutputs' => 'Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
', ], ], 'MonitoringParquetDatasetFormat' => [ 'base' => 'Represents the Parquet dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Parquet' => 'The Parquet dataset used in the monitoring job
', ], ], 'MonitoringProblemType' => [ 'base' => NULL, 'refs' => [ 'ModelQualityAppSpecification$ProblemType' => 'The machine learning problem type of the model that the monitoring job monitors.
', ], ], 'MonitoringResources' => [ 'base' => 'Identifies the resources to deploy for a monitoring job.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$JobResources' => NULL, 'CreateModelBiasJobDefinitionRequest$JobResources' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$JobResources' => NULL, 'CreateModelQualityJobDefinitionRequest$JobResources' => NULL, 'DescribeDataQualityJobDefinitionResponse$JobResources' => NULL, 'DescribeModelBiasJobDefinitionResponse$JobResources' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$JobResources' => NULL, 'DescribeModelQualityJobDefinitionResponse$JobResources' => NULL, 'MonitoringJobDefinition$MonitoringResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
', ], ], 'MonitoringS3Output' => [ 'base' => 'Information about where and how you want to store the results of a monitoring job.
', 'refs' => [ 'MonitoringOutput$S3Output' => 'The Amazon S3 storage location where the results of a monitoring job are saved.
', ], ], 'MonitoringS3Uri' => [ 'base' => NULL, 'refs' => [ 'MonitoringGroundTruthS3Input$S3Uri' => 'The address of the Amazon S3 location of the ground truth labels.
', 'MonitoringS3Output$S3Uri' => 'A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
', ], ], 'MonitoringSchedule' => [ 'base' => 'A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'refs' => [ 'MonitoringScheduleList$member' => NULL, ], ], 'MonitoringScheduleArn' => [ 'base' => NULL, 'refs' => [ 'CreateMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'DescribeProcessingJobResponse$MonitoringScheduleArn' => 'The ARN of a monitoring schedule for an endpoint associated with this processing job.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of a monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'MonitoringScheduleSummary$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'ProcessingJob$MonitoringScheduleArn' => 'The ARN of a monitoring schedule for an endpoint associated with this processing job.
', 'UpdateMonitoringAlertResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'UpdateMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', ], ], 'MonitoringScheduleConfig' => [ 'base' => 'Configures the monitoring schedule and defines the monitoring job.
', 'refs' => [ 'CreateMonitoringScheduleRequest$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleConfig' => NULL, 'MonitoringSchedule$MonitoringScheduleConfig' => NULL, 'UpdateMonitoringScheduleRequest$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', ], ], 'MonitoringScheduleList' => [ 'base' => NULL, 'refs' => [ 'Endpoint$MonitoringSchedules' => 'A list of monitoring schedules for the endpoint. For information about model monitoring, see Amazon SageMaker Model Monitor.
', ], ], 'MonitoringScheduleName' => [ 'base' => NULL, 'refs' => [ 'CreateMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
', 'DeleteMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule to delete.
', 'DescribeMonitoringScheduleRequest$MonitoringScheduleName' => 'Name of a previously created monitoring schedule.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleName' => 'Name of the monitoring schedule.
', 'ListMonitoringAlertHistoryRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'ListMonitoringAlertsRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'ListMonitoringExecutionsRequest$MonitoringScheduleName' => 'Name of a specific schedule to fetch jobs for.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'MonitoringAlertHistorySummary$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'MonitoringExecutionSummary$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'MonitoringScheduleSummary$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'StartMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the schedule to start.
', 'StopMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the schedule to stop.
', 'UpdateMonitoringAlertRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'UpdateMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
', ], ], 'MonitoringScheduleSortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringSchedulesRequest$SortBy' => 'Whether to sort the results by the Status
, CreationTime
, or ScheduledTime
field. The default is CreationTime
.
Summarizes the monitoring schedule.
', 'refs' => [ 'MonitoringScheduleSummaryList$member' => NULL, ], ], 'MonitoringScheduleSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringSchedulesResponse$MonitoringScheduleSummaries' => 'A JSON array in which each element is a summary for a monitoring schedule.
', ], ], 'MonitoringStatisticsResource' => [ 'base' => 'The statistics resource for a monitoring job.
', 'refs' => [ 'DataQualityBaselineConfig$StatisticsResource' => NULL, 'MonitoringBaselineConfig$StatisticsResource' => 'The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
', ], ], 'MonitoringStoppingCondition' => [ 'base' => 'A time limit for how long the monitoring job is allowed to run before stopping.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelBiasJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelQualityJobDefinitionRequest$StoppingCondition' => NULL, 'DescribeDataQualityJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelBiasJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelQualityJobDefinitionResponse$StoppingCondition' => NULL, 'MonitoringJobDefinition$StoppingCondition' => 'Specifies a time limit for how long the monitoring job is allowed to run.
', ], ], 'MonitoringTimeOffsetString' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$StartTimeOffset' => 'If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'BatchTransformInput$EndTimeOffset' => 'If specified, monitoring jobs subtract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'EndpointInput$StartTimeOffset' => 'If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'EndpointInput$EndTimeOffset' => 'If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', ], ], 'MonitoringType' => [ 'base' => NULL, 'refs' => [ 'DescribeMonitoringScheduleResponse$MonitoringType' => 'The type of the monitoring job that this schedule runs. This is one of the following values.
DATA_QUALITY
- The schedule is for a data quality monitoring job.
MODEL_QUALITY
- The schedule is for a model quality monitoring job.
MODEL_BIAS
- The schedule is for a bias monitoring job.
MODEL_EXPLAINABILITY
- The schedule is for an explainability monitoring job.
A filter that returns only the monitoring job runs of the specified monitoring type.
', 'ListMonitoringSchedulesRequest$MonitoringTypeEquals' => 'A filter that returns only the monitoring schedules for the specified monitoring type.
', 'ModelDashboardMonitoringSchedule$MonitoringType' => 'The monitor type of a model monitor.
', 'MonitoringExecutionSummary$MonitoringType' => 'The type of the monitoring job.
', 'MonitoringSchedule$MonitoringType' => 'The type of the monitoring job definition to schedule.
', 'MonitoringScheduleConfig$MonitoringType' => 'The type of the monitoring job definition to schedule.
', 'MonitoringScheduleSummary$MonitoringType' => 'The type of the monitoring job definition that the schedule is for.
', ], ], 'MountPath' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$MountPath' => 'The path within the image to mount the user\'s EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.
', ], ], 'MultiModelConfig' => [ 'base' => 'Specifies additional configuration for hosting multi-model endpoints.
', 'refs' => [ 'ContainerDefinition$MultiModelConfig' => 'Specifies additional configuration for multi-model endpoints.
', ], ], 'NameContains' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsInput$NameContains' => 'A string in the algorithm name. This filter returns only algorithms whose name contains the specified string.
', 'ListClustersRequest$NameContains' => 'Set the maximum number of instances to print in the list.
', 'ListCompilationJobsRequest$NameContains' => 'A filter that returns the model compilation jobs whose name contains a specified string.
', 'ListDataQualityJobDefinitionsRequest$NameContains' => 'A string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.
', 'ListDeviceFleetsRequest$NameContains' => 'Filter for fleets containing this name in their fleet device name.
', 'ListEdgeDeploymentPlansRequest$NameContains' => 'Selects edge deployment plans with names containing this name.
', 'ListEdgeDeploymentPlansRequest$DeviceFleetNameContains' => 'Selects edge deployment plans with a device fleet name containing this name.
', 'ListEdgePackagingJobsRequest$NameContains' => 'Filter for jobs containing this name in their packaging job name.
', 'ListEdgePackagingJobsRequest$ModelNameContains' => 'Filter for jobs where the model name contains this string.
', 'ListHubContentsRequest$NameContains' => 'Only list hub content if the name contains the specified string.
', 'ListHubsRequest$NameContains' => 'Only list hubs with names that contain the specified string.
', 'ListHyperParameterTuningJobsRequest$NameContains' => 'A string in the tuning job name. This filter returns only tuning jobs whose name contains the specified string.
', 'ListInferenceExperimentsRequest$NameContains' => 'Selects inference experiments whose names contain this name.
', 'ListInferenceRecommendationsJobsRequest$NameContains' => 'A string in the job name. This filter returns only recommendations whose name contains the specified string.
', 'ListLabelingJobsRequest$NameContains' => 'A string in the labeling job name. This filter returns only labeling jobs whose name contains the specified string.
', 'ListModelBiasJobDefinitionsRequest$NameContains' => 'Filter for model bias jobs whose name contains a specified string.
', 'ListModelExplainabilityJobDefinitionsRequest$NameContains' => 'Filter for model explainability jobs whose name contains a specified string.
', 'ListModelPackageGroupsInput$NameContains' => 'A string in the model group name. This filter returns only model groups whose name contains the specified string.
', 'ListModelPackagesInput$NameContains' => 'A string in the model package name. This filter returns only model packages whose name contains the specified string.
', 'ListModelQualityJobDefinitionsRequest$NameContains' => 'A string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.
', 'ListMonitoringSchedulesRequest$NameContains' => 'Filter for monitoring schedules whose name contains a specified string.
', 'ListTrainingJobsRequest$NameContains' => 'A string in the training job name. This filter returns only training jobs whose name contains the specified string.
', 'ListTransformJobsRequest$NameContains' => 'A string in the transform job name. This filter returns only transform jobs whose name contains the specified string.
', ], ], 'NeoVpcConfig' => [ 'base' => 'The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker Compilation Jobs Access to Resources in Your Amazon VPC.
', 'refs' => [ 'CreateCompilationJobRequest$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
', 'DescribeCompilationJobResponse$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
', ], ], 'NeoVpcSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'NeoVpcSecurityGroupIds$member' => NULL, ], ], 'NeoVpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'NeoVpcConfig$SecurityGroupIds' => 'The VPC security group IDs. IDs have the form of sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in the Subnets
field.
The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the model in Amazon S3.
', ], ], 'NestedFilters' => [ 'base' => 'A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
For example, to filter on a training job\'s InputDataConfig
property with a specific channel name and S3Uri
prefix, define the following filters:
\'{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}\',
\'{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}\'
A list of nested filter objects.
', ], ], 'NetworkConfig' => [ 'base' => 'Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
', 'refs' => [ 'CreateProcessingJobRequest$NetworkConfig' => 'Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.
', 'DescribeProcessingJobResponse$NetworkConfig' => 'Networking options for a processing job.
', 'MonitoringJobDefinition$NetworkConfig' => 'Specifies networking options for an monitoring job.
', 'ProcessingJob$NetworkConfig' => NULL, ], ], 'NetworkInterfaceId' => [ 'base' => NULL, 'refs' => [ 'DescribeNotebookInstanceOutput$NetworkInterfaceId' => 'The network interface IDs that SageMaker created at the time of creating the instance.
', ], ], 'NextToken' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceRequest$NextToken' => 'Next token of device description.
', 'DescribeDeviceResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'DescribeEdgeDeploymentPlanRequest$NextToken' => 'If the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.
', 'DescribeEdgeDeploymentPlanResponse$NextToken' => 'Token to use when calling the next set of stages in the edge deployment plan.
', 'DescribeFeatureGroupRequest$NextToken' => 'A token to resume pagination of the list of Features
(FeatureDefinitions
). 2,500 Features
are returned by default.
A token to resume pagination of the list of Features
(FeatureDefinitions
).
If the previous call to ListActions
didn\'t return the full set of actions, the call returns a token for getting the next set of actions.
A token for getting the next set of actions, if there are any.
', 'ListAlgorithmsInput$NextToken' => 'If the response to a previous ListAlgorithms
request was truncated, the response includes a NextToken
. To retrieve the next set of algorithms, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListAliasesRequest$NextToken' => 'If the previous call to ListAliases
didn\'t return the full set of aliases, the call returns a token for retrieving the next set of aliases.
A token for getting the next set of aliases, if more aliases exist.
', 'ListAppImageConfigsRequest$NextToken' => 'If the previous call to ListImages
didn\'t return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.
A token for getting the next set of AppImageConfigs, if there are any.
', 'ListAppsRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListAppsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListArtifactsRequest$NextToken' => 'If the previous call to ListArtifacts
didn\'t return the full set of artifacts, the call returns a token for getting the next set of artifacts.
A token for getting the next set of artifacts, if there are any.
', 'ListAssociationsRequest$NextToken' => 'If the previous call to ListAssociations
didn\'t return the full set of associations, the call returns a token for getting the next set of associations.
A token for getting the next set of associations, if there are any.
', 'ListAutoMLJobsRequest$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListAutoMLJobsResponse$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCandidatesForAutoMLJobRequest$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCandidatesForAutoMLJobResponse$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListClusterNodesRequest$NextToken' => 'If the result of the previous ListClusterNodes
request was truncated, the response includes a NextToken
. To retrieve the next set of cluster nodes, use the token in the next request.
The next token specified for listing instances in a SageMaker HyperPod cluster.
', 'ListClustersRequest$NextToken' => 'Set the next token to retrieve the list of SageMaker HyperPod clusters.
', 'ListClustersResponse$NextToken' => 'If the result of the previous ListClusters
request was truncated, the response includes a NextToken
. To retrieve the next set of clusters, use the token in the next request.
If the result of a ListCodeRepositoriesOutput
request was truncated, the response includes a NextToken
. To get the next set of Git repositories, use the token in the next request.
If the result of a ListCodeRepositoriesOutput
request was truncated, the response includes a NextToken
. To get the next set of Git repositories, use the token in the next request.
If the result of the previous ListCompilationJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of model compilation jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this NextToken
. To retrieve the next set of model compilation jobs, use this token in the next request.
If the previous call to ListContexts
didn\'t return the full set of contexts, the call returns a token for getting the next set of contexts.
A token for getting the next set of contexts, if there are any.
', 'ListDataQualityJobDefinitionsRequest$NextToken' => 'If the result of the previous ListDataQualityJobDefinitions
request was truncated, the response includes a NextToken
. To retrieve the next set of transform jobs, use the token in the next request.>
If the result of the previous ListDataQualityJobDefinitions
request was truncated, the response includes a NextToken
. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.
The response from the last list when returning a list large enough to need tokening.
', 'ListDeviceFleetsResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDevicesRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDevicesResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDomainsRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListDomainsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListEdgeDeploymentPlansRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListEdgeDeploymentPlansResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListEdgePackagingJobsRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListEdgePackagingJobsResponse$NextToken' => 'Token to use when calling the next page of results.
', 'ListExperimentsRequest$NextToken' => 'If the previous call to ListExperiments
didn\'t return the full set of experiments, the call returns a token for getting the next set of experiments.
A token for getting the next set of experiments, if there are any.
', 'ListFeatureGroupsRequest$NextToken' => 'A token to resume pagination of ListFeatureGroups
results.
A token to resume pagination of ListFeatureGroups
results.
A token to resume pagination.
', 'ListFlowDefinitionsResponse$NextToken' => 'A token to resume pagination.
', 'ListHubContentVersionsRequest$NextToken' => 'If the response to a previous ListHubContentVersions
request was truncated, the response includes a NextToken
. To retrieve the next set of hub content versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content versions, use it in the subsequent request.
', 'ListHubContentsRequest$NextToken' => 'If the response to a previous ListHubContents
request was truncated, the response includes a NextToken
. To retrieve the next set of hub content, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content, use it in the subsequent request.
', 'ListHubsRequest$NextToken' => 'If the response to a previous ListHubs
request was truncated, the response includes a NextToken
. To retrieve the next set of hubs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hubs, use it in the subsequent request.
', 'ListHumanTaskUisRequest$NextToken' => 'A token to resume pagination.
', 'ListHumanTaskUisResponse$NextToken' => 'A token to resume pagination.
', 'ListHyperParameterTuningJobsRequest$NextToken' => 'If the result of the previous ListHyperParameterTuningJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of tuning jobs, use the token in the next request.
If the result of this ListHyperParameterTuningJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of tuning jobs, use the token in the next request.
If the previous call to ListImageVersions
didn\'t return the full set of versions, the call returns a token for getting the next set of versions.
A token for getting the next set of versions, if there are any.
', 'ListImagesRequest$NextToken' => 'If the previous call to ListImages
didn\'t return the full set of images, the call returns a token for getting the next set of images.
A token for getting the next set of images, if there are any.
', 'ListInferenceExperimentsRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListInferenceExperimentsResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListInferenceRecommendationsJobStepsRequest$NextToken' => 'A token that you can specify to return more results from the list. Specify this field if you have a token that was returned from a previous request.
', 'ListInferenceRecommendationsJobStepsResponse$NextToken' => 'A token that you can specify in your next request to return more results from the list.
', 'ListInferenceRecommendationsJobsRequest$NextToken' => 'If the response to a previous ListInferenceRecommendationsJobsRequest
request was truncated, the response includes a NextToken
. To retrieve the next set of recommendations, use the token in the next request.
A token for getting the next set of recommendations, if there are any.
', 'ListLabelingJobsForWorkteamRequest$NextToken' => 'If the result of the previous ListLabelingJobsForWorkteam
request was truncated, the response includes a NextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
', 'ListLabelingJobsRequest$NextToken' => 'If the result of the previous ListLabelingJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
', 'ListLineageGroupsRequest$NextToken' => 'If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListLineageGroupsResponse$NextToken' => 'If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListModelBiasJobDefinitionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelBiasJobDefinitionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelCardExportJobsRequest$NextToken' => 'If the response to a previous ListModelCardExportJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of model card export jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card export jobs, use it in the subsequent request.
', 'ListModelCardVersionsRequest$NextToken' => 'If the response to a previous ListModelCardVersions
request was truncated, the response includes a NextToken
. To retrieve the next set of model card versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card versions, use it in the subsequent request.
', 'ListModelCardsRequest$NextToken' => 'If the response to a previous ListModelCards
request was truncated, the response includes a NextToken
. To retrieve the next set of model cards, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model cards, use it in the subsequent request.
', 'ListModelExplainabilityJobDefinitionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelExplainabilityJobDefinitionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelMetadataRequest$NextToken' => 'If the response to a previous ListModelMetadataResponse
request was truncated, the response includes a NextToken. To retrieve the next set of model metadata, use the token in the next request.
A token for getting the next set of recommendations, if there are any.
', 'ListModelPackageGroupsInput$NextToken' => 'If the result of the previous ListModelPackageGroups
request was truncated, the response includes a NextToken
. To retrieve the next set of model groups, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model groups, use it in the subsequent request.
', 'ListModelPackagesInput$NextToken' => 'If the response to a previous ListModelPackages
request was truncated, the response includes a NextToken
. To retrieve the next set of model packages, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model packages, use it in the subsequent request.
', 'ListModelQualityJobDefinitionsRequest$NextToken' => 'If the result of the previous ListModelQualityJobDefinitions
request was truncated, the response includes a NextToken
. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.
', 'ListMonitoringAlertHistoryRequest$NextToken' => 'If the result of the previous ListMonitoringAlertHistory
request was truncated, the response includes a NextToken
. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
', 'ListMonitoringAlertsRequest$NextToken' => 'If the result of the previous ListMonitoringAlerts
request was truncated, the response includes a NextToken
. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
', 'ListMonitoringExecutionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringExecutionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringSchedulesRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringSchedulesResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListNotebookInstanceLifecycleConfigsInput$NextToken' => 'If the result of a ListNotebookInstanceLifecycleConfigs
request was truncated, the response includes a NextToken
. To get the next set of lifecycle configurations, use the token in the next request.
If the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.
', 'ListNotebookInstancesInput$NextToken' => ' If the previous call to the ListNotebookInstances
is truncated, the response includes a NextToken
. You can use this token in your subsequent ListNotebookInstances
request to fetch the next set of notebook instances.
You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.
If the response to the previous ListNotebookInstances
request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps
request was truncated, the response includes a NextToken
. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps
request was truncated, the response includes a NextToken
. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutions
request was truncated, the response includes a NextToken
. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutions
request was truncated, the response includes a NextToken
. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution
request was truncated, the response includes a NextToken
. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution
request was truncated, the response includes a NextToken
. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelines
request was truncated, the response includes a NextToken
. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListPipelines
request was truncated, the response includes a NextToken
. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListProcessingJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of processing jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of processing jobs, use it in the subsequent request.
', 'ListProjectsInput$NextToken' => 'If the result of the previous ListProjects
request was truncated, the response includes a NextToken
. To retrieve the next set of projects, use the token in the next request.
If the result of the previous ListCompilationJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of model compilation jobs, use the token in the next request.
A token to resume pagination of ListResourceCatalogs
results.
A token to resume pagination of ListResourceCatalogs
results.
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListSpacesResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListStageDevicesRequest$NextToken' => 'The response from the last list when returning a list large enough to neeed tokening.
', 'ListStageDevicesResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListStudioLifecycleConfigsRequest$NextToken' => 'If the previous call to ListStudioLifecycleConfigs didn\'t return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.
', 'ListStudioLifecycleConfigsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListSubscribedWorkteamsRequest$NextToken' => 'If the result of the previous ListSubscribedWorkteams
request was truncated, the response includes a NextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
', 'ListTagsInput$NextToken' => ' If the response to the previous ListTags
request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.
If response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$NextToken' => 'If the result of the previous ListTrainingJobsForHyperParameterTuningJob
request was truncated, the response includes a NextToken
. To retrieve the next set of training jobs, use the token in the next request.
If the result of this ListTrainingJobsForHyperParameterTuningJob
request was truncated, the response includes a NextToken
. To retrieve the next set of training jobs, use the token in the next request.
If the result of the previous ListTrainingJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of training jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
', 'ListTransformJobsRequest$NextToken' => 'If the result of the previous ListTransformJobs
request was truncated, the response includes a NextToken
. To retrieve the next set of transform jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.
', 'ListTrialComponentsRequest$NextToken' => 'If the previous call to ListTrialComponents
didn\'t return the full set of components, the call returns a token for getting the next set of components.
A token for getting the next set of components, if there are any.
', 'ListTrialsRequest$NextToken' => 'If the previous call to ListTrials
didn\'t return the full set of trials, the call returns a token for getting the next set of trials.
A token for getting the next set of trials, if there are any.
', 'ListUserProfilesRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListUserProfilesResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListWorkforcesRequest$NextToken' => 'A token to resume pagination.
', 'ListWorkforcesResponse$NextToken' => 'A token to resume pagination.
', 'ListWorkteamsRequest$NextToken' => 'If the result of the previous ListWorkteams
request was truncated, the response includes a NextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
', 'SearchRequest$NextToken' => 'If more than MaxResults
resources match the specified SearchExpression
, the response includes a NextToken
. The NextToken
can be passed to the next SearchRequest
to continue retrieving results.
If the result of the previous Search
request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.
The name of the space that appears in the SageMaker Studio UI.
', 'CustomImageContainerArguments$member' => NULL, 'DescribeSpaceResponse$SpaceDisplayName' => 'The name of the space that appears in the Amazon SageMaker Studio UI.
', 'SpaceDetails$SpaceDisplayName' => 'The name of the space that appears in the Studio UI.
', 'UpdateSpaceRequest$SpaceDisplayName' => 'The name of the space that appears in the Amazon SageMaker Studio UI.
', ], ], 'NotebookInstanceAcceleratorType' => [ 'base' => NULL, 'refs' => [ 'NotebookInstanceAcceleratorTypes$member' => NULL, ], ], 'NotebookInstanceAcceleratorTypes' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$AcceleratorTypes' => 'A list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'DescribeNotebookInstanceOutput$AcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'UpdateNotebookInstanceInput$AcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types to associate with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', ], ], 'NotebookInstanceArn' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceOutput$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', 'DescribeNotebookInstanceOutput$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', 'NotebookInstanceSummary$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', ], ], 'NotebookInstanceLifecycleConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', 'DescribeNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', 'NotebookInstanceLifecycleConfigSummary$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigContent' => [ 'base' => NULL, 'refs' => [ 'NotebookInstanceLifecycleHook$Content' => 'A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigList' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceLifecycleConfigInput$OnCreate' => 'A shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
', 'CreateNotebookInstanceLifecycleConfigInput$OnStart' => 'A shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
', 'DescribeNotebookInstanceLifecycleConfigOutput$OnCreate' => 'The shell script that runs only once, when you create a notebook instance.
', 'DescribeNotebookInstanceLifecycleConfigOutput$OnStart' => 'The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
', 'UpdateNotebookInstanceLifecycleConfigInput$OnCreate' => 'The shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
', 'UpdateNotebookInstanceLifecycleConfigInput$OnStart' => 'The shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
', ], ], 'NotebookInstanceLifecycleConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$LifecycleConfigName' => 'The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'CreateNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'DeleteNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration to delete.
', 'DescribeNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration to describe.
', 'DescribeNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'DescribeNotebookInstanceOutput$NotebookInstanceLifecycleConfigName' => 'Returns the name of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance
', 'ListNotebookInstancesInput$NotebookInstanceLifecycleConfigNameContains' => 'A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.
', 'NotebookInstanceLifecycleConfigSummary$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'NotebookInstanceSummary$NotebookInstanceLifecycleConfigName' => 'The name of a notebook instance lifecycle configuration associated with this notebook instance.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'UpdateNotebookInstanceInput$LifecycleConfigName' => 'The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'UpdateNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigNameContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsInput$NameContains' => 'A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.
', ], ], 'NotebookInstanceLifecycleConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsInput$SortBy' => 'Sorts the list of results. The default is CreationTime
.
The sort order for results.
', ], ], 'NotebookInstanceLifecycleConfigSummary' => [ 'base' => 'Provides a summary of a notebook instance lifecycle configuration.
', 'refs' => [ 'NotebookInstanceLifecycleConfigSummaryList$member' => NULL, ], ], 'NotebookInstanceLifecycleConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsOutput$NotebookInstanceLifecycleConfigs' => 'An array of NotebookInstanceLifecycleConfiguration
objects, each listing a lifecycle configuration.
Contains the notebook instance lifecycle configuration script.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH
environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin
.
View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances
in log stream [notebook-instance-name]/[LifecycleConfigHook]
.
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'refs' => [ 'NotebookInstanceLifecycleConfigList$member' => NULL, ], ], 'NotebookInstanceName' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$NotebookInstanceName' => 'The name of the new notebook instance.
', 'CreatePresignedNotebookInstanceUrlInput$NotebookInstanceName' => 'The name of the notebook instance.
', 'DeleteNotebookInstanceInput$NotebookInstanceName' => 'The name of the SageMaker notebook instance to delete.
', 'DescribeNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance that you want information about.
', 'DescribeNotebookInstanceOutput$NotebookInstanceName' => 'The name of the SageMaker notebook instance.
', 'NotebookInstanceSummary$NotebookInstanceName' => 'The name of the notebook instance that you want a summary for.
', 'StartNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to start.
', 'StopNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to terminate.
', 'UpdateNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to update.
', ], ], 'NotebookInstanceNameContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$NameContains' => 'A string in the notebook instances\' name. This filter returns only notebook instances whose name contains the specified string.
', ], ], 'NotebookInstanceSortKey' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$SortBy' => 'The field to sort results by. The default is Name
.
The sort order for results.
', ], ], 'NotebookInstanceStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeNotebookInstanceOutput$NotebookInstanceStatus' => 'The status of the notebook instance.
', 'ListNotebookInstancesInput$StatusEquals' => 'A filter that returns only notebook instances with the specified status.
', 'NotebookInstanceSummary$NotebookInstanceStatus' => 'The status of the notebook instance.
', ], ], 'NotebookInstanceSummary' => [ 'base' => 'Provides summary information for an SageMaker notebook instance.
', 'refs' => [ 'NotebookInstanceSummaryList$member' => NULL, ], ], 'NotebookInstanceSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesOutput$NotebookInstances' => 'An array of NotebookInstanceSummary
objects, one for each notebook instance.
A JSON object that contains the URL string.
', 'DescribeNotebookInstanceOutput$Url' => 'The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
', 'NotebookInstanceSummary$Url' => 'The URL that you use to connect to the Jupyter notebook running in your notebook instance.
', ], ], 'NotebookInstanceVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
', 'DescribeNotebookInstanceOutput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to the notebook instance.
', 'UpdateNotebookInstanceInput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can\'t determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can\'t decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.
', ], ], 'NotebookOutputOption' => [ 'base' => NULL, 'refs' => [ 'SharingSettings$NotebookOutputOption' => 'Whether to include the notebook cell output when sharing the notebook. The default is Disabled
.
Configures Amazon SNS notifications of available or expiring work items for work teams.
', 'refs' => [ 'CreateWorkteamRequest$NotificationConfiguration' => 'Configures notification of workers regarding available or expiring work items.
', 'UpdateWorkteamRequest$NotificationConfiguration' => 'Configures SNS topic notifications for available or expiring work items
', 'Workteam$NotificationConfiguration' => 'Configures SNS notifications of available or expiring work items for work teams.
', ], ], 'NotificationTopicArn' => [ 'base' => NULL, 'refs' => [ 'NotificationConfiguration$NotificationTopicArn' => 'The ARN for the Amazon SNS topic to which notifications should be published.
', ], ], 'NumberOfAcceleratorDevices' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentComputeResourceRequirements$NumberOfAcceleratorDevicesRequired' => 'The number of accelerators to allocate to run a model that you assign to an inference component. Accelerators include GPUs and Amazon Web Services Inferentia.
', ], ], 'NumberOfCpuCores' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentComputeResourceRequirements$NumberOfCpuCoresRequired' => 'The number of CPU cores to allocate to run a model that you assign to an inference component.
', ], ], 'NumberOfHumanWorkersPerDataObject' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$NumberOfHumanWorkersPerDataObject' => 'The number of human workers that will label an object.
', 'LabelingJobForWorkteamSummary$NumberOfHumanWorkersPerDataObject' => 'The configured number of workers per data object.
', ], ], 'NumberOfSteps' => [ 'base' => NULL, 'refs' => [ 'Stairs$NumberOfSteps' => 'Specifies how many steps to perform during traffic.
', ], ], 'ObjectiveStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$ObjectiveStatus' => 'The objective\'s status.
', 'HyperParameterTrainingJobSummary$ObjectiveStatus' => 'The status of the objective metric for the training job:
Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
Pending: The training job is in progress and evaluation of its final objective metric is pending.
Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
', 'ObjectiveStatusCounters$Pending' => 'The number of training jobs that are in progress and pending evaluation of their final objective metric.
', 'ObjectiveStatusCounters$Failed' => 'The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
', ], ], 'ObjectiveStatusCounters' => [ 'base' => 'Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$ObjectiveStatusCounters' => 'The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
', 'HyperParameterTuningJobSearchEntity$ObjectiveStatusCounters' => NULL, 'HyperParameterTuningJobSummary$ObjectiveStatusCounters' => 'The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
', ], ], 'OfflineStoreConfig' => [ 'base' => 'The configuration of an OfflineStore
.
Provide an OfflineStoreConfig
in a request to CreateFeatureGroup
to create an OfflineStore
.
To encrypt an OfflineStore
using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId
, in S3StorageConfig
.
Use this to configure an OfflineFeatureStore
. This parameter allows you to specify:
The Amazon Simple Storage Service (Amazon S3) location of an OfflineStore
.
A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.
An KMS encryption key to encrypt the Amazon S3 location used for OfflineStore
. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.
Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
To learn more about this parameter, see OfflineStoreConfig.
', 'DescribeFeatureGroupResponse$OfflineStoreConfig' => 'The configuration of the offline store. It includes the following configurations:
Amazon S3 location of the offline store.
Configuration of the Glue data catalog.
Table format of the offline store.
Option to disable the automatic creation of a Glue table for the offline store.
Encryption configuration.
The status of OfflineStore
.
The status of the OfflineStore
. Notifies you if replicating data into the OfflineStore
has failed. Returns either: Active
or Blocked
Notifies you if replicating data into the OfflineStore
has failed. Returns either: Active
or Blocked
.
An OfflineStore
status. Filters by OfflineStore
status.
An OfflineStore
status.
Use this parameter to configure your OIDC Identity Provider (IdP).
', 'refs' => [ 'CreateWorkforceRequest$OidcConfig' => 'Use this parameter to configure a private workforce using your own OIDC Identity Provider.
Do not use CognitoConfig
if you specify values for OidcConfig
.
Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.
', ], ], 'OidcConfigForResponse' => [ 'base' => 'Your OIDC IdP workforce configuration.
', 'refs' => [ 'Workforce$OidcConfig' => 'The configuration of an OIDC Identity Provider (IdP) private workforce.
', ], ], 'OidcEndpoint' => [ 'base' => NULL, 'refs' => [ 'OidcConfig$Issuer' => 'The OIDC IdP issuer used to configure your private workforce.
', 'OidcConfig$AuthorizationEndpoint' => 'The OIDC IdP authorization endpoint used to configure your private workforce.
', 'OidcConfig$TokenEndpoint' => 'The OIDC IdP token endpoint used to configure your private workforce.
', 'OidcConfig$UserInfoEndpoint' => 'The OIDC IdP user information endpoint used to configure your private workforce.
', 'OidcConfig$LogoutEndpoint' => 'The OIDC IdP logout endpoint used to configure your private workforce.
', 'OidcConfig$JwksUri' => 'The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
', 'OidcConfigForResponse$Issuer' => 'The OIDC IdP issuer used to configure your private workforce.
', 'OidcConfigForResponse$AuthorizationEndpoint' => 'The OIDC IdP authorization endpoint used to configure your private workforce.
', 'OidcConfigForResponse$TokenEndpoint' => 'The OIDC IdP token endpoint used to configure your private workforce.
', 'OidcConfigForResponse$UserInfoEndpoint' => 'The OIDC IdP user information endpoint used to configure your private workforce.
', 'OidcConfigForResponse$LogoutEndpoint' => 'The OIDC IdP logout endpoint used to configure your private workforce.
', 'OidcConfigForResponse$JwksUri' => 'The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
', ], ], 'OidcMemberDefinition' => [ 'base' => 'A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups
, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups
, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId
, for at rest data encryption. You can turn OnlineStore
on or off by specifying the EnableOnlineStore
flag at General Assembly.
The default value is False
.
You can turn the OnlineStore
on or off by specifying True
for the EnableOnlineStore
flag in OnlineStoreConfig
.
You can also include an Amazon Web Services KMS key ID (KMSKeyId
) for at-rest encryption of the OnlineStore
.
The default value is False
.
The configuration for the OnlineStore
.
Updates the feature group online store configuration.
', 'refs' => [ 'UpdateFeatureGroupRequest$OnlineStoreConfig' => 'Updates the feature group online store configuration.
', ], ], 'OnlineStoreSecurityConfig' => [ 'base' => 'The security configuration for OnlineStore
.
Use to specify KMS Key ID (KMSKeyId
) for at-rest encryption of your OnlineStore
.
The size of the OnlineStore
in bytes.
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
The value of Name
equals Value
.
The value of Name
doesn\'t equal Value
.
The Name
property exists.
The Name
property does not exist.
The value of Name
is greater than Value
. Not supported for text properties.
The value of Name
is greater than or equal to Value
. Not supported for text properties.
The value of Name
is less than Value
. Not supported for text properties.
The value of Name
is less than or equal to Value
. Not supported for text properties.
The value of Name
is one of the comma delimited strings in Value
. Only supported for text properties.
The value of Name
contains the string Value
. Only supported for text properties.
A SearchExpression
can include the Contains
operator multiple times when the value of Name
is one of the following:
Experiment.DisplayName
Experiment.ExperimentName
Experiment.Tags
Trial.DisplayName
Trial.TrialName
Trial.Tags
TrialComponent.DisplayName
TrialComponent.TrialComponentName
TrialComponent.Tags
TrialComponent.InputArtifacts
TrialComponent.OutputArtifacts
A SearchExpression
can include only one Contains
operator for all other values of Name
. In these cases, if you include multiple Contains
operators in the SearchExpression
, the result is the following error message: "\'CONTAINS\' operator usage limit of 1 exceeded.
"
The maximum value of the metric.
', 'TrialComponentMetricSummary$Min' => 'The minimum value of the metric.
', 'TrialComponentMetricSummary$Last' => 'The most recent value of the metric.
', 'TrialComponentMetricSummary$Avg' => 'The average value of the metric.
', 'TrialComponentMetricSummary$StdDev' => 'The standard deviation of the metric.
', ], ], 'OptionalInteger' => [ 'base' => NULL, 'refs' => [ 'TrialComponentMetricSummary$Count' => 'The number of samples used to generate the metric.
', ], ], 'OptionalVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to the processing instance.
', 'HyperParameterTuningResourceConfig$VolumeSizeInGB' => 'The volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for InstanceConfigs
is also specified.
Some instance types have a fixed total local storage size. If you select one of these instances for training, VolumeSizeInGB
cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.
SageMaker supports only the General Purpose SSD (gp2) storage volume type.
The size, in GB, of the ML storage volume attached to the processing instance.
', ], ], 'OrderKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$SortOrder' => 'The sort order for results. The default is Descending
.
The sort order for results. The default is Descending
.
The sort order for results. The default is Descending
.
The sort order for results. The default is Descending
.
The model output compression type. Select None
to output an uncompressed model, recommended for large model outputs. Defaults to gzip.
Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice
and TargetPlatform
are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice
list, use TargetPlatform
to describe the platform of your edge device and CompilerOptions
if there are specific settings that are required or recommended to use for particular TargetPlatform.
Provides information about the output location for the compiled model and the target device the model runs on.
', 'DescribeCompilationJobResponse$OutputConfig' => 'Information about the output location for the compiled model and the target device that the model runs on.
', ], ], 'OutputDataConfig' => [ 'base' => 'Provides information about how to store model training results (model artifacts).
', 'refs' => [ 'CreateTrainingJobRequest$OutputDataConfig' => 'Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
', 'DescribeTrainingJobResponse$OutputDataConfig' => 'The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
', 'HyperParameterTrainingJobDefinition$OutputDataConfig' => 'Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
', 'TrainingJob$OutputDataConfig' => 'The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
', 'TrainingJobDefinition$OutputDataConfig' => 'the path to the S3 bucket where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
', ], ], 'OutputParameter' => [ 'base' => 'An output parameter of a pipeline step.
', 'refs' => [ 'OutputParameterList$member' => NULL, ], ], 'OutputParameterList' => [ 'base' => NULL, 'refs' => [ 'CallbackStepMetadata$OutputParameters' => 'A list of the output parameters of the callback step.
', 'LambdaStepMetadata$OutputParameters' => 'A list of the output parameters of the Lambda step.
', 'SendPipelineExecutionStepSuccessRequest$OutputParameters' => 'A list of the output parameters of the callback step.
', ], ], 'OwnershipSettings' => [ 'base' => 'The collection of ownership settings for a space.
', 'refs' => [ 'CreateSpaceRequest$OwnershipSettings' => 'A collection of ownership settings.
', 'DescribeSpaceResponse$OwnershipSettings' => 'The collection of ownership settings for a space.
', ], ], 'OwnershipSettingsSummary' => [ 'base' => 'Specifies summary information about the ownership settings.
', 'refs' => [ 'SpaceDetails$OwnershipSettingsSummary' => 'Specifies summary information about the ownership settings.
', ], ], 'PaginationToken' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$NextToken' => 'If the result of the previous ListEndpointConfig
request was truncated, the response includes a NextToken
. To retrieve the next set of endpoint configurations, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent request
', 'ListEndpointsInput$NextToken' => 'If the result of a ListEndpoints
request was truncated, the response includes a NextToken
. To retrieve the next set of endpoints, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
', 'ListInferenceComponentsInput$NextToken' => 'A token that you use to get the next set of results following a truncated response. If the response to the previous request was truncated, that response provides the value for this token.
', 'ListInferenceComponentsOutput$NextToken' => 'The token to use in a subsequent request to get the next set of results following a truncated response.
', 'ListModelsInput$NextToken' => 'If the response to a previous ListModels
request was truncated, the response includes a NextToken
. To retrieve the next set of models, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.
', ], ], 'ParallelismConfiguration' => [ 'base' => 'Configuration that controls the parallelism of the pipeline. By default, the parallelism configuration specified applies to all executions of the pipeline unless overridden.
', 'refs' => [ 'CreatePipelineRequest$ParallelismConfiguration' => 'This is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.
', 'DescribePipelineExecutionResponse$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline.
', 'DescribePipelineResponse$ParallelismConfiguration' => 'Lists the parallelism configuration applied to the pipeline.
', 'Pipeline$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline.
', 'PipelineExecution$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline execution.
', 'RetryPipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline.
', 'StartPipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
', 'UpdatePipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
', 'UpdatePipelineRequest$ParallelismConfiguration' => 'If specified, it applies to all executions of this pipeline by default.
', ], ], 'Parameter' => [ 'base' => 'Assigns a value to a named Pipeline parameter.
', 'refs' => [ 'ParameterList$member' => NULL, ], ], 'ParameterKey' => [ 'base' => NULL, 'refs' => [ 'AutoParameter$Name' => 'The name of the hyperparameter to optimize using Autotune.
', 'CategoricalParameterRange$Name' => 'The name of the categorical hyperparameter to tune.
', 'ContinuousParameterRange$Name' => 'The name of the continuous hyperparameter to tune.
', 'IntegerParameterRange$Name' => 'The name of the hyperparameter to search.
', ], ], 'ParameterList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineParametersForExecutionResponse$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', 'PipelineExecution$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', 'StartPipelineExecutionRequest$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', ], ], 'ParameterName' => [ 'base' => NULL, 'refs' => [ 'HyperParameterSpecification$Name' => 'The name of this hyperparameter. The name must be unique.
', ], ], 'ParameterRange' => [ 'base' => 'Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
', 'refs' => [ 'HyperParameterSpecification$Range' => 'The allowed range for this hyperparameter.
', ], ], 'ParameterRanges' => [ 'base' => 'Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for Array Members
refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can\'t exceed the maximum number specified.
The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
', ], ], 'ParameterType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterSpecification$Type' => 'The type of this hyperparameter. The valid types are Integer
, Continuous
, Categorical
, and FreeText
.
An example value of the hyperparameter to optimize using Autotune.
', 'ContinuousParameterRange$MinValue' => 'The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValue
for tuning.
The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue
value and this value for tuning.
The minimum floating-point value allowed.
', 'ContinuousParameterRangeSpecification$MaxValue' => 'The maximum floating-point value allowed.
', 'IntegerParameterRange$MinValue' => 'The minimum value of the hyperparameter to search.
', 'IntegerParameterRange$MaxValue' => 'The maximum value of the hyperparameter to search.
', 'IntegerParameterRangeSpecification$MinValue' => 'The minimum integer value allowed.
', 'IntegerParameterRangeSpecification$MaxValue' => 'The maximum integer value allowed.
', 'ParameterValues$member' => NULL, ], ], 'ParameterValues' => [ 'base' => NULL, 'refs' => [ 'CategoricalParameterRange$Values' => 'A list of the categories for the hyperparameter.
', 'CategoricalParameterRangeSpecification$Values' => 'The allowed categories for the hyperparameter.
', ], ], 'Parent' => [ 'base' => 'The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.
', 'refs' => [ 'Parents$member' => NULL, ], ], 'ParentHyperParameterTuningJob' => [ 'base' => 'A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
', 'refs' => [ 'ParentHyperParameterTuningJobs$member' => NULL, ], ], 'ParentHyperParameterTuningJobs' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningJobWarmStartConfig$ParentHyperParameterTuningJobs' => 'An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
', ], ], 'Parents' => [ 'base' => NULL, 'refs' => [ 'TrialComponent$Parents' => 'An array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.
', ], ], 'PendingDeploymentSummary' => [ 'base' => 'The summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.
', 'refs' => [ 'DescribeEndpointOutput$PendingDeploymentSummary' => 'Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.
', ], ], 'PendingProductionVariantSummary' => [ 'base' => 'The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the VariantStatus
, weight and capacity for a production variant associated with an endpoint.
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.
', 'PendingDeploymentSummary$ShadowProductionVariants' => 'An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants
for the in-progress deployment.
Percentage of devices in the fleet to deploy to the current stage.
', 'ShadowModelVariantConfig$SamplingPercentage' => 'The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant.
', ], ], 'Phase' => [ 'base' => 'Defines the traffic pattern.
', 'refs' => [ 'Phases$member' => NULL, ], ], 'Phases' => [ 'base' => NULL, 'refs' => [ 'TrafficPattern$Phases' => 'Defines the phases traffic specification.
', ], ], 'Pipeline' => [ 'base' => 'A SageMaker Model Building Pipeline instance.
', 'refs' => [ 'SearchRecord$Pipeline' => NULL, ], ], 'PipelineArn' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the created pipeline.
', 'DeletePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline to delete.
', 'DescribePipelineExecutionResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'DescribePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'Pipeline$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'PipelineExecution$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline that was executed.
', 'PipelineSummary$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'UpdatePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the updated pipeline.
', ], ], 'PipelineDefinition' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineDefinition' => 'The JSON pipeline definition of the pipeline.
', 'DescribePipelineDefinitionForExecutionResponse$PipelineDefinition' => 'The JSON pipeline definition.
', 'DescribePipelineResponse$PipelineDefinition' => 'The JSON pipeline definition.
', 'UpdatePipelineRequest$PipelineDefinition' => 'The JSON pipeline definition.
', ], ], 'PipelineDefinitionS3Location' => [ 'base' => 'The location of the pipeline definition stored in Amazon S3.
', 'refs' => [ 'CreatePipelineRequest$PipelineDefinitionS3Location' => 'The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
', 'UpdatePipelineRequest$PipelineDefinitionS3Location' => 'The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
', ], ], 'PipelineDescription' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineDescription' => 'A description of the pipeline.
', 'DescribePipelineResponse$PipelineDescription' => 'The description of the pipeline.
', 'Pipeline$PipelineDescription' => 'The description of the pipeline.
', 'PipelineSummary$PipelineDescription' => 'The description of the pipeline.
', 'UpdatePipelineRequest$PipelineDescription' => 'The description of the pipeline.
', ], ], 'PipelineExecution' => [ 'base' => 'An execution of a pipeline.
', 'refs' => [ 'SearchRecord$PipelineExecution' => NULL, ], ], 'PipelineExecutionArn' => [ 'base' => NULL, 'refs' => [ 'CacheHitResult$SourcePipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineDefinitionForExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'ListPipelineExecutionStepsRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'ListPipelineParametersForExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'PipelineExecution$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'RetryPipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'RetryPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'SelectiveExecutionConfig$SourcePipelineExecutionArn' => 'The ARN from a reference execution of the current pipeline. Used to copy input collaterals needed for the selected steps to run. The execution status of the pipeline can be either Failed
or Success
.
This field is required if the steps you specify for SelectedSteps
depend on output collaterals from any non-specified pipeline steps. For more information, see Selective Execution for Pipeline Steps.
The ARN from an execution of the current pipeline.
', 'SendPipelineExecutionStepFailureResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'SendPipelineExecutionStepSuccessResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StartPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StopPipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StopPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'UpdatePipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the updated pipeline execution.
', ], ], 'PipelineExecutionDescription' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'PipelineExecution$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'StartPipelineExecutionRequest$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionDescription' => 'The description of the pipeline execution.
', ], ], 'PipelineExecutionFailureReason' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$FailureReason' => 'If the execution failed, a message describing why.
', 'PipelineExecution$FailureReason' => 'If the execution failed, a message describing why.
', ], ], 'PipelineExecutionName' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'PipelineExecution$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'StartPipelineExecutionRequest$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', ], ], 'PipelineExecutionStatus' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionStatus' => 'The status of the pipeline execution.
', 'PipelineExecution$PipelineExecutionStatus' => 'The status of the pipeline status.
', 'PipelineExecutionSummary$PipelineExecutionStatus' => 'The status of the pipeline execution.
', ], ], 'PipelineExecutionStep' => [ 'base' => 'An execution of a step in a pipeline.
', 'refs' => [ 'PipelineExecutionStepList$member' => NULL, ], ], 'PipelineExecutionStepList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineExecutionStepsResponse$PipelineExecutionSteps' => 'A list of PipeLineExecutionStep
objects. Each PipeLineExecutionStep
consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.
Metadata for a step execution.
', 'refs' => [ 'PipelineExecutionStep$Metadata' => 'Metadata to run the pipeline step.
', ], ], 'PipelineExecutionSummary' => [ 'base' => 'A pipeline execution summary.
', 'refs' => [ 'PipelineExecutionSummaryList$member' => NULL, ], ], 'PipelineExecutionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineExecutionsResponse$PipelineExecutionSummaries' => 'Contains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.
', ], ], 'PipelineExperimentConfig' => [ 'base' => 'Specifies the names of the experiment and trial created by a pipeline.
', 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExperimentConfig' => NULL, 'PipelineExecution$PipelineExperimentConfig' => NULL, ], ], 'PipelineName' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineName' => 'The name of the pipeline.
', 'CreatePipelineRequest$PipelineDisplayName' => 'The display name of the pipeline.
', 'DeletePipelineRequest$PipelineName' => 'The name of the pipeline to delete.
', 'DescribePipelineResponse$PipelineName' => 'The name of the pipeline.
', 'DescribePipelineResponse$PipelineDisplayName' => 'The display name of the pipeline.
', 'ListPipelinesRequest$PipelineNamePrefix' => 'The prefix of the pipeline name.
', 'Pipeline$PipelineName' => 'The name of the pipeline.
', 'Pipeline$PipelineDisplayName' => 'The display name of the pipeline.
', 'PipelineSummary$PipelineName' => 'The name of the pipeline.
', 'PipelineSummary$PipelineDisplayName' => 'The display name of the pipeline.
', 'UpdatePipelineRequest$PipelineName' => 'The name of the pipeline to update.
', 'UpdatePipelineRequest$PipelineDisplayName' => 'The display name of the pipeline.
', ], ], 'PipelineNameOrArn' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline to describe.
', 'ListPipelineExecutionsRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline.
', 'StartPipelineExecutionRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline.
', ], ], 'PipelineParameterName' => [ 'base' => NULL, 'refs' => [ 'Parameter$Name' => 'The name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.
', ], ], 'PipelineStatus' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineResponse$PipelineStatus' => 'The status of the pipeline execution.
', 'Pipeline$PipelineStatus' => 'The status of the pipeline.
', ], ], 'PipelineSummary' => [ 'base' => 'A summary of a pipeline.
', 'refs' => [ 'PipelineSummaryList$member' => NULL, ], ], 'PipelineSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListPipelinesResponse$PipelineSummaries' => 'Contains a sorted list of PipelineSummary
objects matching the specified filters. Each PipelineSummary
consists of PipelineArn, PipelineName, ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and RoleArn. This list can be empty.
The platform identifier of the notebook instance runtime environment.
', 'DescribeNotebookInstanceOutput$PlatformIdentifier' => 'The platform identifier of the notebook instance runtime environment.
', ], ], 'PolicyString' => [ 'base' => NULL, 'refs' => [ 'GetModelPackageGroupPolicyOutput$ResourcePolicy' => 'The resource policy for the model group.
', 'PutModelPackageGroupPolicyInput$ResourcePolicy' => 'The resource policy for the model group.
', ], ], 'PredefinedMetricSpecification' => [ 'base' => 'A specification for a predefined metric.
', 'refs' => [ 'MetricSpecification$Predefined' => 'Information about a predefined metric.
', ], ], 'PresignedDomainUrl' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlResponse$AuthorizedUrl' => 'The presigned URL.
', ], ], 'ProbabilityThresholdAttribute' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$ProbabilityThresholdAttribute' => 'The threshold for the class probability to be evaluated as a positive result.
', 'EndpointInput$ProbabilityThresholdAttribute' => 'The threshold for the class probability to be evaluated as a positive result.
', ], ], 'ProblemType' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobRequest$ProblemType' => 'Defines the type of supervised learning problem available for the candidates. For more information, see Amazon SageMaker Autopilot problem types.
', 'DescribeAutoMLJobResponse$ProblemType' => 'Returns the job\'s problem type.
', 'ResolvedAttributes$ProblemType' => 'The problem type.
', 'TabularJobConfig$ProblemType' => 'The type of supervised learning problem available for the model candidates of the AutoML job V2. For more information, see Amazon SageMaker Autopilot problem types.
You must either specify the type of supervised learning problem in ProblemType
and provide the AutoMLJobObjective metric, or none at all.
The type of supervised learning problem available for the model candidates of the AutoML job V2 (Binary Classification, Multiclass Classification, Regression). For more information, see Amazon SageMaker Autopilot problem types.
', ], ], 'ProcessingClusterConfig' => [ 'base' => 'Configuration for the cluster used to run a processing job.
', 'refs' => [ 'ProcessingResources$ClusterConfig' => 'The configuration for the resources in a cluster used to run the processing job.
', ], ], 'ProcessingEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'MonitoringEnvironmentMap$key' => NULL, 'ProcessingEnvironmentMap$key' => NULL, ], ], 'ProcessingEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobRequest$Environment' => 'The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.
', 'DescribeProcessingJobResponse$Environment' => 'The environment variables set in the Docker container.
', 'ProcessingJob$Environment' => 'Sets the environment variables in the Docker container.
', ], ], 'ProcessingEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'MonitoringEnvironmentMap$value' => NULL, 'ProcessingEnvironmentMap$value' => NULL, ], ], 'ProcessingFeatureStoreOutput' => [ 'base' => 'Configuration for processing job outputs in Amazon SageMaker Feature Store.
', 'refs' => [ 'ProcessingOutput$FeatureStoreOutput' => 'Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when AppManaged
is specified.
The inputs for a processing job. The processing input must specify exactly one of either S3Input
or DatasetDefinition
types.
An array of inputs configuring the data to download into the processing container.
', 'DescribeProcessingJobResponse$ProcessingInputs' => 'The inputs for a processing job.
', 'ProcessingJob$ProcessingInputs' => 'List of input configurations for the processing job.
', ], ], 'ProcessingInstanceCount' => [ 'base' => NULL, 'refs' => [ 'MonitoringClusterConfig$InstanceCount' => 'The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
', 'ProcessingClusterConfig$InstanceCount' => 'The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
', ], ], 'ProcessingInstanceType' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$InstanceType' => 'The instance type to deploy a custom rule for debugging a training job.
', 'MonitoringClusterConfig$InstanceType' => 'The ML compute instance type for the processing job.
', 'ProcessingClusterConfig$InstanceType' => 'The ML compute instance type for the processing job.
', 'ProfilerRuleConfiguration$InstanceType' => 'The instance type to deploy a custom rule for profiling a training job.
', ], ], 'ProcessingJob' => [ 'base' => 'An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
', 'refs' => [ 'TrialComponentSourceDetail$ProcessingJob' => 'Information about a processing job that\'s the source of a trial component.
', ], ], 'ProcessingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobResponse$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'DebugRuleEvaluationStatus$RuleEvaluationJobArn' => 'The Amazon Resource Name (ARN) of the rule evaluation job.
', 'DescribeProcessingJobResponse$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'MonitoringExecutionSummary$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the monitoring job.
', 'ProcessingJob$ProcessingJobArn' => 'The ARN of the processing job.
', 'ProcessingJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'ProcessingJobSummary$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job..
', 'ProfilerRuleEvaluationStatus$RuleEvaluationJobArn' => 'The Amazon Resource Name (ARN) of the rule evaluation job.
', ], ], 'ProcessingJobName' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobRequest$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DataQualityBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the data quality monitoring job.
', 'DescribeProcessingJobRequest$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeProcessingJobResponse$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'ModelBiasBaselineConfig$BaseliningJobName' => 'The name of the baseline model bias job.
', 'ModelExplainabilityBaselineConfig$BaseliningJobName' => 'The name of the baseline model explainability job.
', 'ModelQualityBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the monitoring job.
', 'MonitoringBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the monitoring job.
', 'ProcessingJob$ProcessingJobName' => 'The name of the processing job.
', 'ProcessingJobSummary$ProcessingJobName' => 'The name of the processing job.
', 'StopProcessingJobRequest$ProcessingJobName' => 'The name of the processing job to stop.
', ], ], 'ProcessingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeProcessingJobResponse$ProcessingJobStatus' => 'Provides the status of a processing job.
', 'ListProcessingJobsRequest$StatusEquals' => 'A filter that retrieves only processing jobs with a specific status.
', 'ProcessingJob$ProcessingJobStatus' => 'The status of the processing job.
', 'ProcessingJobSummary$ProcessingJobStatus' => 'The status of the processing job.
', ], ], 'ProcessingJobStepMetadata' => [ 'base' => 'Metadata for a processing job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$ProcessingJob' => 'The Amazon Resource Name (ARN) of the processing job that was run by this step execution.
', ], ], 'ProcessingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListProcessingJobsResponse$ProcessingJobSummaries' => 'An array of ProcessingJobSummary
objects, each listing a processing job.
Summary of information about a processing job.
', 'refs' => [ 'ProcessingJobSummaries$member' => NULL, ], ], 'ProcessingLocalPath' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$LocalPath' => 'Path to the filesystem where the batch transform data is available to the container.
', 'DatasetDefinition$LocalPath' => 'The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath
is an absolute path to the input data. This is a required parameter when AppManaged
is False
(default).
Path to the filesystem where the endpoint data is available to the container.
', 'MonitoringS3Output$LocalPath' => 'The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
', 'ProcessingS3Input$LocalPath' => 'The local path in your container where you want Amazon SageMaker to write input data to. LocalPath
is an absolute path to the input data and must begin with /opt/ml/processing/
. LocalPath
is a required parameter when AppManaged
is False
(default).
The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath
is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container\'s entrypoint is invoked.
Specifies the maximum runtime in seconds.
', ], ], 'ProcessingOutput' => [ 'base' => 'Describes the results of a processing job. The processing output must specify exactly one of either S3Output
or FeatureStoreOutput
types.
Configuration for uploading output from the processing container.
', 'refs' => [ 'CreateProcessingJobRequest$ProcessingOutputConfig' => 'Output configuration for the processing job.
', 'DescribeProcessingJobResponse$ProcessingOutputConfig' => 'Output configuration for the processing job.
', 'ProcessingJob$ProcessingOutputConfig' => NULL, ], ], 'ProcessingOutputs' => [ 'base' => NULL, 'refs' => [ 'ProcessingOutputConfig$Outputs' => 'An array of outputs configuring the data to upload from the processing container.
', ], ], 'ProcessingResources' => [ 'base' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'refs' => [ 'CreateProcessingJobRequest$ProcessingResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'DescribeProcessingJobResponse$ProcessingResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'ProcessingJob$ProcessingResources' => NULL, ], ], 'ProcessingS3CompressionType' => [ 'base' => NULL, 'refs' => [ 'ProcessingS3Input$S3CompressionType' => 'Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip
can only be used when Pipe
mode is specified as the S3InputMode
. In Pipe
mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicated
Whether input data distributed in Amazon S3 is fully replicated or sharded by an Amazon S3 key. Defaults to FullyReplicated
Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated
, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
Whether you use an S3Prefix
or a ManifestFile
for the data type. If you choose S3Prefix
, S3Uri
identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile
, S3Uri
identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
Configuration for downloading input data from Amazon S3 into the processing container.
', 'refs' => [ 'ProcessingInput$S3Input' => 'Configuration for downloading input data from Amazon S3 into the processing container.
', ], ], 'ProcessingS3InputMode' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$S3InputMode' => 'Whether the Pipe
or File
is used as the input mode for transferring data for the monitoring job. Pipe
mode is recommended for large datasets. File
mode is useful for small files that fit in memory. Defaults to File
.
Whether the Pipe
or File
is used as the input mode for transferring data for the monitoring job. Pipe
mode is recommended for large datasets. File
mode is useful for small files that fit in memory. Defaults to File
.
Whether to use File
or Pipe
input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe
mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.
Configuration for uploading output data to Amazon S3 from the processing container.
', 'refs' => [ 'ProcessingOutput$S3Output' => 'Configuration for processing job outputs in Amazon S3.
', ], ], 'ProcessingS3UploadMode' => [ 'base' => NULL, 'refs' => [ 'MonitoringS3Output$S3UploadMode' => 'Whether to upload the results of the monitoring job continuously or after the job completes.
', 'ProcessingS3Output$S3UploadMode' => 'Whether to upload the results of the processing job continuously or after the job completes.
', ], ], 'ProcessingStoppingCondition' => [ 'base' => 'Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
', 'refs' => [ 'CreateProcessingJobRequest$StoppingCondition' => 'The time limit for how long the processing job is allowed to run.
', 'DescribeProcessingJobResponse$StoppingCondition' => 'The time limit for how long the processing job is allowed to run.
', 'ProcessingJob$StoppingCondition' => NULL, ], ], 'ProcessingVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'MonitoringClusterConfig$VolumeSizeInGB' => 'The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
', 'ProcessingClusterConfig$VolumeSizeInGB' => 'The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
Certain Nitro-based instances include local storage with a fixed total size, dependent on the instance type. When using these instances for processing, Amazon SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage. You can\'t request a VolumeSizeInGB
greater than the total size of the local instance storage.
For a list of instance types that support local instance storage, including the total size per instance type, see Instance Store Volumes.
Indicates CPU or GPU compatibility.
CPU
: The image version is compatible with CPU.
GPU
: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU
: The image version is compatible with CPU.
GPU
: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU
: The image version is compatible with CPU.
GPU
: The image version is compatible with GPU.
The product identifier of the algorithm.
', 'ModelPackageContainerDefinition$ProductId' => 'The Amazon Web Services Marketplace product ID of the model package.
', ], ], 'ProductListings' => [ 'base' => NULL, 'refs' => [ 'Workteam$ProductListingIds' => 'The Amazon Marketplace identifier for a vendor\'s work team.
', ], ], 'ProductionVariant' => [ 'base' => 'Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
', 'refs' => [ 'ProductionVariantList$member' => NULL, ], ], 'ProductionVariantAcceleratorType' => [ 'base' => NULL, 'refs' => [ 'PendingProductionVariantSummary$AcceleratorType' => 'The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'ProductionVariant$AcceleratorType' => 'The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
', ], ], 'ProductionVariantContainerStartupHealthCheckTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentStartupParameters$ContainerStartupHealthCheckTimeoutInSeconds' => 'The timeout value, in seconds, for your inference container to pass health check by Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
', 'ProductionVariant$ContainerStartupHealthCheckTimeoutInSeconds' => 'The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
', ], ], 'ProductionVariantCoreDumpConfig' => [ 'base' => 'Specifies configuration for a core dump from the model container when the process crashes.
', 'refs' => [ 'ProductionVariant$CoreDumpConfig' => 'Specifies configuration for a core dump from the model container when the process crashes.
', ], ], 'ProductionVariantInstanceType' => [ 'base' => NULL, 'refs' => [ 'EndpointInputConfiguration$InstanceType' => 'The instance types to use for the load test.
', 'EndpointOutputConfiguration$InstanceType' => 'The instance type recommended by Amazon SageMaker Inference Recommender.
', 'PendingProductionVariantSummary$InstanceType' => 'The type of instances associated with the variant.
', 'ProductionVariant$InstanceType' => 'The ML compute instance type.
', 'RealTimeInferenceRecommendation$InstanceType' => 'The recommended instance type for Real-Time Inference.
', 'RealtimeInferenceInstanceTypes$member' => NULL, ], ], 'ProductionVariantList' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigInput$ProductionVariants' => 'An array of ProductionVariant
objects, one for each model that you want to host at this endpoint.
An array of ProductionVariant
objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants
. If you use this field, you can only specify one variant for ProductionVariants
and one variant for ShadowProductionVariants
.
An array of ProductionVariant
objects, one for each model that you want to host at this endpoint.
An array of ProductionVariant
objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants
.
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
', 'refs' => [ 'PendingProductionVariantSummary$ManagedInstanceScaling' => 'Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
', 'ProductionVariant$ManagedInstanceScaling' => 'Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
', 'ProductionVariantSummary$ManagedInstanceScaling' => 'Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
', ], ], 'ProductionVariantModelDataDownloadTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'InferenceComponentStartupParameters$ModelDataDownloadTimeoutInSeconds' => 'The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this inference component.
', 'ProductionVariant$ModelDataDownloadTimeoutInSeconds' => 'The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
', ], ], 'ProductionVariantRoutingConfig' => [ 'base' => 'Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
', 'refs' => [ 'PendingProductionVariantSummary$RoutingConfig' => 'Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
', 'ProductionVariant$RoutingConfig' => 'Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
', 'ProductionVariantSummary$RoutingConfig' => 'Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
', ], ], 'ProductionVariantSSMAccess' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$EnableSSMAccess' => ' You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint
.
Specifies the serverless configuration for an endpoint variant.
', 'refs' => [ 'EndpointInputConfiguration$ServerlessConfig' => NULL, 'EndpointOutputConfiguration$ServerlessConfig' => NULL, 'PendingProductionVariantSummary$CurrentServerlessConfig' => 'The serverless configuration for the endpoint.
', 'PendingProductionVariantSummary$DesiredServerlessConfig' => 'The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.
', 'ProductionVariant$ServerlessConfig' => 'The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
', 'ProductionVariantSummary$CurrentServerlessConfig' => 'The serverless configuration for the endpoint.
', 'ProductionVariantSummary$DesiredServerlessConfig' => 'The serverless configuration requested for the endpoint update.
', ], ], 'ProductionVariantServerlessUpdateConfig' => [ 'base' => 'Specifies the serverless update concurrency configuration for an endpoint variant.
', 'refs' => [ 'DesiredWeightAndCapacity$ServerlessUpdateConfig' => 'Specifies the serverless update concurrency configuration for an endpoint variant.
', ], ], 'ProductionVariantStatus' => [ 'base' => 'Describes the status of the production variant.
', 'refs' => [ 'ProductionVariantStatusList$member' => NULL, ], ], 'ProductionVariantStatusList' => [ 'base' => NULL, 'refs' => [ 'PendingProductionVariantSummary$VariantStatus' => 'The endpoint variant status which describes the current deployment stage status or operational status.
', 'ProductionVariantSummary$VariantStatus' => 'The endpoint variant status which describes the current deployment stage status or operational status.
', ], ], 'ProductionVariantSummary' => [ 'base' => 'Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities
API and the endpoint status is Updating
, you get different desired and current values.
An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
', 'DescribeEndpointOutput$ShadowProductionVariants' => 'An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants
.
A list of the production variants hosted on the endpoint. Each production variant is a model.
', 'Endpoint$ShadowProductionVariants' => 'A list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the production variant.
', ], ], 'ProductionVariantVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
', ], ], 'ProfilerConfig' => [ 'base' => 'Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
', 'refs' => [ 'CreateTrainingJobRequest$ProfilerConfig' => NULL, 'DescribeTrainingJobResponse$ProfilerConfig' => NULL, 'TrainingJob$ProfilerConfig' => NULL, ], ], 'ProfilerConfigForUpdate' => [ 'base' => 'Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and storage paths.
', 'refs' => [ 'UpdateTrainingJobRequest$ProfilerConfig' => 'Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
', ], ], 'ProfilerRuleConfiguration' => [ 'base' => 'Configuration information for profiling rules.
', 'refs' => [ 'ProfilerRuleConfigurations$member' => NULL, ], ], 'ProfilerRuleConfigurations' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', 'DescribeTrainingJobResponse$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', 'UpdateTrainingJobRequest$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', ], ], 'ProfilerRuleEvaluationStatus' => [ 'base' => 'Information about the status of the rule evaluation.
', 'refs' => [ 'ProfilerRuleEvaluationStatuses$member' => NULL, ], ], 'ProfilerRuleEvaluationStatuses' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$ProfilerRuleEvaluationStatuses' => 'Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
', ], ], 'ProfilingIntervalInMilliseconds' => [ 'base' => NULL, 'refs' => [ 'ProfilerConfig$ProfilingIntervalInMilliseconds' => 'A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
', 'ProfilerConfigForUpdate$ProfilingIntervalInMilliseconds' => 'A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
', ], ], 'ProfilingParameters' => [ 'base' => NULL, 'refs' => [ 'ProfilerConfig$ProfilingParameters' => 'Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig
, PythonProfilingConfig
, and DataLoaderProfilingConfig
. The following codes are configuration structures for the ProfilingParameters
parameter. To learn more about how to configure the ProfilingParameters
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig
, PythonProfilingConfig
, and DataLoaderProfilingConfig
. The following codes are configuration structures for the ProfilingParameters
parameter. To learn more about how to configure the ProfilingParameters
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Profiling status of a training job.
', ], ], 'ProgrammingLang' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ProgrammingLang' => 'The supported programming language and its version.
', 'DescribeImageVersionResponse$ProgrammingLang' => 'The supported programming language and its version.
', 'UpdateImageVersionRequest$ProgrammingLang' => 'The supported programming language and its version.
', ], ], 'Project' => [ 'base' => 'The properties of a project as returned by the Search API.
', 'refs' => [ 'SearchRecord$Project' => 'The properties of a project.
', ], ], 'ProjectArn' => [ 'base' => NULL, 'refs' => [ 'CreateProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'DescribeProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'Project$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'ProjectSummary$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'UpdateProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', ], ], 'ProjectEntityName' => [ 'base' => NULL, 'refs' => [ 'CreateProjectInput$ProjectName' => 'The name of the project.
', 'DeleteProjectInput$ProjectName' => 'The name of the project to delete.
', 'DescribeProjectInput$ProjectName' => 'The name of the project to describe.
', 'DescribeProjectOutput$ProjectName' => 'The name of the project.
', 'ListProjectsInput$NameContains' => 'A filter that returns the projects whose name contains a specified string.
', 'Project$ProjectName' => 'The name of the project.
', 'ProjectSummary$ProjectName' => 'The name of the project.
', 'UpdateProjectInput$ProjectName' => 'The name of the project.
', ], ], 'ProjectId' => [ 'base' => NULL, 'refs' => [ 'CreateProjectOutput$ProjectId' => 'The ID of the new project.
', 'DescribeProjectOutput$ProjectId' => 'The ID of the project.
', 'Project$ProjectId' => 'The ID of the project.
', 'ProjectSummary$ProjectId' => 'The ID of the project.
', ], ], 'ProjectSortBy' => [ 'base' => NULL, 'refs' => [ 'ListProjectsInput$SortBy' => 'The field by which to sort results. The default is CreationTime
.
The sort order for results. The default is Ascending
.
The status of the project.
', 'Project$ProjectStatus' => 'The status of the project.
', 'ProjectSummary$ProjectStatus' => 'The status of the project.
', ], ], 'ProjectSummary' => [ 'base' => 'Information about a project.
', 'refs' => [ 'ProjectSummaryList$member' => NULL, ], ], 'ProjectSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListProjectsOutput$ProjectSummaryList' => 'A list of summaries of projects.
', ], ], 'PropertyNameHint' => [ 'base' => NULL, 'refs' => [ 'PropertyNameQuery$PropertyNameHint' => 'Text that begins a property\'s name.
', ], ], 'PropertyNameQuery' => [ 'base' => 'Part of the SuggestionQuery
type. Specifies a hint for retrieving property names that begin with the specified text.
Defines a property name hint. Only property names that begin with the specified hint are included in the response.
', ], ], 'PropertyNameSuggestion' => [ 'base' => 'A property name returned from a GetSearchSuggestions
call that specifies a value in the PropertyNameQuery
field.
A list of property names for a Resource
that match a SuggestionQuery
.
The current status of the product.
AVAILABLE
- Stable state, ready to perform any operation. The most recent operation succeeded and completed.
UNDER_CHANGE
- Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations.
TAINTED
- Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version.
ERROR
- An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack.
PLAN_IN_PROGRESS
- Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
A key value pair used when you provision a project as a service catalog product. For information, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'ProvisioningParameters$member' => NULL, ], ], 'ProvisioningParameterKey' => [ 'base' => NULL, 'refs' => [ 'ProvisioningParameter$Key' => 'The key that identifies a provisioning parameter.
', ], ], 'ProvisioningParameterValue' => [ 'base' => NULL, 'refs' => [ 'ProvisioningParameter$Value' => 'The value of the provisioning parameter.
', ], ], 'ProvisioningParameters' => [ 'base' => NULL, 'refs' => [ 'ServiceCatalogProvisioningDetails$ProvisioningParameters' => 'A list of key value pairs that you specify when you provision a product.
', 'ServiceCatalogProvisioningUpdateDetails$ProvisioningParameters' => 'A list of key value pairs that you specify when you provision a product.
', ], ], 'PublicWorkforceTaskPrice' => [ 'base' => 'Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
0.012
0.024
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
0.840
0.960
1.080
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
2.400
2.280
2.160
2.040
1.920
1.800
1.680
1.560
1.440
1.320
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
The price that you pay for each task performed by an Amazon Mechanical Turk worker.
', ], ], 'PutModelPackageGroupPolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'PutModelPackageGroupPolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'QualityCheckStepMetadata' => [ 'base' => 'Container for the metadata for a Quality check step. For more information, see the topic on QualityCheck step in the Amazon SageMaker Developer Guide.
', 'refs' => [ 'PipelineExecutionStepMetadata$QualityCheck' => 'The configurations and outcomes of the check step execution. This includes:
The type of the check conducted.
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The Boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck
is set the same as CalculatedBaseline
.
A set of filters to narrow the set of lineage entities connected to the StartArn
(s) returned by the QueryLineage
API action.
A set of filtering parameters that allow you to specify which entities should be returned.
Properties - Key-value pairs to match on the lineage entities\' properties.
LineageTypes - A set of lineage entity types to match on. For example: TrialComponent
, Artifact
, or Context
.
CreatedBefore - Filter entities created before this date.
ModifiedBefore - Filter entities modified before this date.
ModifiedAfter - Filter entities modified after this date.
The maximum depth in lineage relationships from the StartArns
that are traversed. Depth is a measure of the number of Associations
from the StartArn
entity to the matched results.
Limits the number of vertices in the results. Use the NextToken
in a response to to retrieve the next page of results.
A list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.
', ], ], 'QueryLineageTypes' => [ 'base' => NULL, 'refs' => [ 'QueryFilters$LineageTypes' => 'Filter the lineage entities connected to the StartArn
(s) by the type of the lineage entity.
Filter the lineage entities connected to the StartArn
(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.
Filter the lineage entities connected to the StartArn
by type. For example: DataSet
, Model
, Endpoint
, or ModelDeployment
.
A collection of settings that apply to an RSessionGateway
app.
A collection of settings that configure the RSessionGateway
app.
Indicates whether the current user has access to the RStudioServerPro
app.
A collection of settings that configure user interaction with the RStudioServerPro
app.
A collection of settings that configure user interaction with the RStudioServerPro
app.
A collection of settings that configure the RStudioServerPro
Domain-level app.
A collection of settings that configure the RStudioServerPro
Domain-level app.
A collection of settings that update the current configuration for the RStudioServerPro
Domain-level app.
A collection of RStudioServerPro
Domain-level app settings to update. A single RStudioServerPro
application is created for a domain.
The level of permissions that the user has within the RStudioServerPro
app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.
A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.
', ], ], 'RealTimeInferenceConfig' => [ 'base' => 'The infrastructure configuration for deploying the model to a real-time inference endpoint.
', 'refs' => [ 'ModelInfrastructureConfig$RealTimeInferenceConfig' => 'The infrastructure configuration for deploying the model to real-time inference.
', ], ], 'RealTimeInferenceRecommendation' => [ 'base' => 'The recommended configuration to use for Real-Time Inference.
', 'refs' => [ 'RealTimeInferenceRecommendations$member' => NULL, ], ], 'RealTimeInferenceRecommendations' => [ 'base' => NULL, 'refs' => [ 'DeploymentRecommendation$RealTimeInferenceRecommendations' => 'A list of RealTimeInferenceRecommendation items.
', ], ], 'RealtimeInferenceInstanceTypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedRealtimeInferenceInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
', 'InferenceSpecification$SupportedRealtimeInferenceInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
This parameter is required for unversioned models, and optional for versioned models.
', ], ], 'RecommendationFailureReason' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInferenceBenchmark$FailureReason' => 'The reason why a benchmark failed.
', ], ], 'RecommendationJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobResponse$JobArn' => 'The Amazon Resource Name (ARN) of the recommendation job.
', 'DescribeInferenceRecommendationsJobResponse$JobArn' => 'The Amazon Resource Name (ARN) of the job.
', 'InferenceRecommendationsJob$JobArn' => 'The Amazon Resource Name (ARN) of the recommendation job.
', ], ], 'RecommendationJobCompilationJobName' => [ 'base' => NULL, 'refs' => [ 'ModelConfiguration$CompilationJobName' => 'The name of the compilation job used to create the recommended model artifacts.
', ], ], 'RecommendationJobCompiledOutputConfig' => [ 'base' => 'Provides information about the output configuration for the compiled model.
', 'refs' => [ 'RecommendationJobOutputConfig$CompiledOutputConfig' => 'Provides information about the output configuration for the compiled model.
', ], ], 'RecommendationJobContainerConfig' => [ 'base' => 'Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig
override the corresponding fields in the model package. Use ContainerConfig
if you want to specify these fields for the recommendation job but don\'t want to edit them in your model package.
Specifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig
override the corresponding fields in the model package.
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.
', ], ], 'RecommendationJobDescription' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobDescription' => 'Description of the recommendation job.
', 'DescribeInferenceRecommendationsJobResponse$JobDescription' => 'The job description that you provided when you initiated the job.
', 'InferenceRecommendationsJob$JobDescription' => 'The job description.
', ], ], 'RecommendationJobFrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$FrameworkVersion' => 'The framework version of the container image.
', ], ], 'RecommendationJobInferenceBenchmark' => [ 'base' => 'The details for a specific benchmark from an Inference Recommender job.
', 'refs' => [ 'InferenceRecommendationsJobStep$InferenceBenchmark' => 'The details for a specific benchmark.
', ], ], 'RecommendationJobInputConfig' => [ 'base' => 'The input configuration of the recommendation job.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$InputConfig' => 'Provides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.
', 'DescribeInferenceRecommendationsJobResponse$InputConfig' => 'Returns information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations you provided when you initiated the job.
', ], ], 'RecommendationJobName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobName' => 'A name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account. The job name is passed down to the resources created by the recommendation job. The names of resources (such as the model, endpoint configuration, endpoint, and compilation) that are prefixed with the job name are truncated at 40 characters.
', 'DescribeInferenceRecommendationsJobRequest$JobName' => 'The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeInferenceRecommendationsJobResponse$JobName' => 'The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'GetScalingConfigurationRecommendationRequest$InferenceRecommendationsJobName' => 'The name of a previously completed Inference Recommender job.
', 'GetScalingConfigurationRecommendationResponse$InferenceRecommendationsJobName' => 'The name of a previously completed Inference Recommender job.
', 'InferenceRecommendationsJob$JobName' => 'The name of the job.
', 'InferenceRecommendationsJobStep$JobName' => 'The name of the Inference Recommender job.
', 'ListInferenceRecommendationsJobStepsRequest$JobName' => 'The name for the Inference Recommender job.
', 'StopInferenceRecommendationsJobRequest$JobName' => 'The name of the job you want to stop.
', ], ], 'RecommendationJobOutputConfig' => [ 'base' => 'Provides information about the output configuration for the compiled model.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$OutputConfig' => 'Provides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.
', ], ], 'RecommendationJobPayloadConfig' => [ 'base' => 'The configuration for the payload for a recommendation job.
', 'refs' => [ 'RecommendationJobContainerConfig$PayloadConfig' => 'Specifies the SamplePayloadUrl
and all other sample payload-related fields.
Specifies the maximum number of jobs that can run in parallel and the maximum number of jobs that can run.
', 'refs' => [ 'RecommendationJobInputConfig$ResourceLimit' => 'Defines the resource limit of the job.
', ], ], 'RecommendationJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$Status' => 'The status of the job.
', 'InferenceRecommendationsJob$Status' => 'The status of the job.
', 'InferenceRecommendationsJobStep$Status' => 'The current status of the benchmark.
', 'ListInferenceRecommendationsJobStepsRequest$Status' => 'A filter to return benchmarks of a specified status. If this field is left empty, then all benchmarks are returned.
', 'ListInferenceRecommendationsJobsRequest$StatusEquals' => 'A filter that retrieves only inference recommendations jobs with a specific status.
', ], ], 'RecommendationJobStoppingConditions' => [ 'base' => 'Specifies conditions for stopping a job. When a job reaches a stopping condition limit, SageMaker ends the job.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$StoppingConditions' => 'A set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.
', 'DescribeInferenceRecommendationsJobResponse$StoppingConditions' => 'The stopping conditions that you provided when you initiated the job.
', ], ], 'RecommendationJobSupportedContentType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobSupportedContentTypes$member' => NULL, ], ], 'RecommendationJobSupportedContentTypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobPayloadConfig$SupportedContentTypes' => 'The supported MIME types for the input data.
', ], ], 'RecommendationJobSupportedEndpointType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedEndpointType' => 'The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
', ], ], 'RecommendationJobSupportedInstanceTypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
', ], ], 'RecommendationJobSupportedResponseMIMEType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobSupportedResponseMIMETypes$member' => NULL, ], ], 'RecommendationJobSupportedResponseMIMETypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', ], ], 'RecommendationJobType' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobType' => 'Defines the type of recommendation job. Specify Default
to initiate an instance recommendation and Advanced
to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT
) job.
The job type that you provided when you initiated the job.
', 'InferenceRecommendationsJob$JobType' => 'The recommendation job type.
', ], ], 'RecommendationJobVpcConfig' => [ 'base' => 'Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
', 'refs' => [ 'RecommendationJobInputConfig$VpcConfig' => 'Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
', ], ], 'RecommendationJobVpcSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobVpcSecurityGroupIds$member' => NULL, ], ], 'RecommendationJobVpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobVpcConfig$SecurityGroupIds' => 'The VPC security group IDs. IDs have the form of sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in the Subnets
field.
The ID of the subnets in the VPC to which you want to connect your model.
', ], ], 'RecommendationMetrics' => [ 'base' => 'The metrics of recommendations.
', 'refs' => [ 'InferenceRecommendation$Metrics' => 'The metrics used to decide what recommendation to make.
', 'RecommendationJobInferenceBenchmark$Metrics' => NULL, ], ], 'RecommendationStatus' => [ 'base' => NULL, 'refs' => [ 'DeploymentRecommendation$RecommendationStatus' => 'Status of the deployment recommendation. The status NOT_APPLICABLE
means that SageMaker is unable to provide a default recommendation for the model using the information provided. If the deployment status is IN_PROGRESS
, retry your API call after a few seconds to get a COMPLETED
deployment recommendation.
The type of the subtask.
BENCHMARK
: Evaluate the performance of your model on different instance types.
A filter to return details about the specified type of subtask.
BENCHMARK
: Evaluate the performance of your model on different instance types.
Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don\'t need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
', ], ], 'RedshiftClusterId' => [ 'base' => 'The Redshift cluster Identifier.
', 'refs' => [ 'RedshiftDatasetDefinition$ClusterId' => NULL, ], ], 'RedshiftDatabase' => [ 'base' => 'The name of the Redshift database used in Redshift query execution.
', 'refs' => [ 'RedshiftDatasetDefinition$Database' => NULL, ], ], 'RedshiftDatasetDefinition' => [ 'base' => 'Configuration for Redshift Dataset Definition input.
', 'refs' => [ 'DatasetDefinition$RedshiftDatasetDefinition' => NULL, ], ], 'RedshiftQueryString' => [ 'base' => 'The SQL query statements to be executed.
', 'refs' => [ 'RedshiftDatasetDefinition$QueryString' => NULL, ], ], 'RedshiftResultCompressionType' => [ 'base' => 'The compression used for Redshift query results.
', 'refs' => [ 'RedshiftDatasetDefinition$OutputCompression' => NULL, ], ], 'RedshiftResultFormat' => [ 'base' => 'The data storage format for Redshift query results.
', 'refs' => [ 'RedshiftDatasetDefinition$OutputFormat' => NULL, ], ], 'RedshiftUserName' => [ 'base' => 'The database user name used in Redshift query execution.
', 'refs' => [ 'RedshiftDatasetDefinition$DbUser' => NULL, ], ], 'RegisterDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'RegisterModelStepMetadata' => [ 'base' => 'Metadata for a register model job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$RegisterModel' => 'The Amazon Resource Name (ARN) of the model package that the model was registered to by this step execution.
', ], ], 'ReleaseNotes' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ReleaseNotes' => 'The maintainer description of the image version.
', 'DescribeImageVersionResponse$ReleaseNotes' => 'The maintainer description of the image version.
', 'UpdateImageVersionRequest$ReleaseNotes' => 'The maintainer description of the image version.
', ], ], 'RemoteDebugConfig' => [ 'base' => 'Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
', 'refs' => [ 'CreateTrainingJobRequest$RemoteDebugConfig' => 'Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
', 'DescribeTrainingJobResponse$RemoteDebugConfig' => 'Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
', ], ], 'RemoteDebugConfigForUpdate' => [ 'base' => 'Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
', 'refs' => [ 'UpdateTrainingJobRequest$RemoteDebugConfig' => 'Configuration for remote debugging while the training job is running. You can update the remote debugging configuration when the SecondaryStatus
of the job is Downloading
or Training
.To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
Contains input values for a task.
', 'refs' => [ 'RenderUiTemplateRequest$Task' => 'A RenderableTask
object containing a representative task to render.
A description of an error that occurred while rendering the template.
', 'refs' => [ 'RenderingErrorList$member' => NULL, ], ], 'RenderingErrorList' => [ 'base' => NULL, 'refs' => [ 'RenderUiTemplateResponse$Errors' => 'A list of one or more RenderingError
objects if any were encountered while rendering the template. If there were no errors, the list is empty.
Set this to one of the following values:
Platform
- The model image is hosted in Amazon ECR.
Vpc
- The model image is hosted in a private Docker registry in your VPC.
Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc
as the value for the RepositoryAccessMode
field of the ImageConfig
object that you passed to a call to CreateModel
and the private Docker registry where the model image is hosted requires authentication.
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc
as the value for the RepositoryAccessMode
field, and the private Docker registry where the model image is hosted requires authentication.
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
', ], ], 'RepositoryUrl' => [ 'base' => NULL, 'refs' => [ 'CodeRepository$RepositoryUrl' => 'The URL of the Git repository.
', ], ], 'ResolvedAttributes' => [ 'base' => 'The resolved attributes.
', 'refs' => [ 'DescribeAutoMLJobResponse$ResolvedAttributes' => 'Contains ProblemType
, AutoMLJobObjective
, and CompletionCriteria
. If you do not provide these values, they are inferred.
The Amazon Resource Name (ARN) of the resource that you want to tag.
', 'DeleteTagsInput$ResourceArn' => 'The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
', 'ListTagsInput$ResourceArn' => 'The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
', ], ], 'ResourceCatalog' => [ 'base' => ' A resource catalog containing all of the resources of a specific resource type within a resource owner account. For an example on sharing the Amazon SageMaker Feature Store DefaultFeatureGroupCatalog
, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.
The Amazon Resource Name (ARN) of the ResourceCatalog
.
A free form description of the ResourceCatalog
.
A list of the requested ResourceCatalog
s.
A string that partially matches one or more ResourceCatalog
s names. Filters ResourceCatalog
by name.
The name of the ResourceCatalog
.
The value on which the resource catalog list is sorted.
', ], ], 'ResourceCatalogSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListResourceCatalogsRequest$SortOrder' => 'The order in which the resource catalogs are listed.
', ], ], 'ResourceConfig' => [ 'base' => 'Describes the resources, including machine learning (ML) compute instances and ML storage volumes, to use for model training.
', 'refs' => [ 'CreateTrainingJobRequest$ResourceConfig' => 'The resources, including the ML compute instances and ML storage volumes, to use for model training.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File
as the TrainingInputMode
in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
', 'HyperParameterTrainingJobDefinition$ResourceConfig' => 'The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File
as the TrainingInputMode
in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig
instead.
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
', 'TrainingJobDefinition$ResourceConfig' => 'The resources, including the ML compute instances and ML storage volumes, to use for model training.
', ], ], 'ResourceConfigForUpdate' => [ 'base' => 'The ResourceConfig
to update KeepAlivePeriodInSeconds
. Other fields in the ResourceConfig
cannot be updated.
The training job ResourceConfig
to update warm pool retention length.
The ID of the Amazon Elastic File System managed by this Domain.
', ], ], 'ResourceInUse' => [ 'base' => 'Resource being accessed is in use.
', 'refs' => [], ], 'ResourceLimitExceeded' => [ 'base' => 'You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
', 'refs' => [], ], 'ResourceLimits' => [ 'base' => 'Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
', 'refs' => [ 'HyperParameterTuningJobConfig$ResourceLimits' => 'The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$ResourceLimits' => 'The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
', ], ], 'ResourceNotFound' => [ 'base' => 'Resource being access is not found.
', 'refs' => [], ], 'ResourcePolicyString' => [ 'base' => NULL, 'refs' => [ 'GetLineageGroupPolicyResponse$ResourcePolicy' => 'The resource policy that gives access to the lineage group in another account.
', ], ], 'ResourcePropertyName' => [ 'base' => NULL, 'refs' => [ 'Filter$Name' => 'A resource property name. For example, TrainingJobName
. For valid property names, see SearchRecord. You must specify a valid property for the resource.
The name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig
.
A suggested property name based on what you entered in the search textbox in the SageMaker console.
', 'SearchRequest$SortBy' => 'The name of the resource property used to sort the SearchResults
. The default is LastModifiedTime
.
The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time.
Multiply ResourceRetainedBillableTimeInSeconds
by the number of instances (InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: ResourceRetainedBillableTimeInSeconds * InstanceCount
.
Specifies the ARN\'s of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
', 'refs' => [ 'AppDetails$ResourceSpec' => NULL, 'CodeEditorAppSettings$DefaultResourceSpec' => NULL, 'CreateAppRequest$ResourceSpec' => 'The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
The value of InstanceType
passed as part of the ResourceSpec
in the CreateApp
call overrides the value passed as part of the ResourceSpec
configured for the user profile or the domain. If InstanceType
is not specified in any of those three ResourceSpec
values for a KernelGateway
app, the CreateApp
call fails with a request validation error.
The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
', 'JupyterLabAppSettings$DefaultResourceSpec' => NULL, 'JupyterServerAppSettings$DefaultResourceSpec' => 'The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns
parameter, then this parameter is also required.
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
', ], ], 'ResourceType' => [ 'base' => NULL, 'refs' => [ 'GetSearchSuggestionsRequest$Resource' => 'The name of the SageMaker resource to search for.
', 'SearchRequest$Resource' => 'The name of the SageMaker resource to search for.
', ], ], 'ResponseMIMEType' => [ 'base' => NULL, 'refs' => [ 'ResponseMIMETypes$member' => NULL, ], ], 'ResponseMIMETypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', 'InferenceSpecification$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', ], ], 'RetentionPolicy' => [ 'base' => 'The retention policy for data stored on an Amazon Elastic File System (EFS) volume.
', 'refs' => [ 'DeleteDomainRequest$RetentionPolicy' => 'The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).
', ], ], 'RetentionType' => [ 'base' => NULL, 'refs' => [ 'RetentionPolicy$HomeEfsFileSystem' => 'The default is Retain
, which specifies to keep the data stored on the EFS volume.
Specify Delete
to delete the data stored on the EFS volume.
The retry strategy to use when a training job fails due to an InternalServerError
. RetryStrategy
is specified as part of the CreateTrainingJob
and CreateHyperParameterTuningJob
requests. You can add the StoppingCondition
parameter to the request to limit the training time for the complete job.
The number of times to retry the job when the job fails due to an InternalServerError
.
The number of times to retry the job when the job fails due to an InternalServerError
.
The number of times to retry the job when the job fails due to an InternalServerError
.
The number of times to retry the job when the job fails due to an InternalServerError
.
The IAM roles that SageMaker uses to run the training jobs.
', 'ClusterInstanceGroupDetails$ExecutionRole' => 'The execution role for the instance group to assume.
', 'ClusterInstanceGroupSpecification$ExecutionRole' => 'Specifies an IAM execution role to be assumed by the instance group.
', 'CreateAutoMLJobRequest$RoleArn' => 'The ARN of the role that is used to access the data.
', 'CreateAutoMLJobV2Request$RoleArn' => 'The ARN of the role that is used to access the data.
', 'CreateCompilationJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
During model compilation, Amazon SageMaker needs your permission to:
Read input data from an S3 bucket
Write model artifacts to an S3 bucket
Write logs to Amazon CloudWatch Logs
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole
permission. For more information, see Amazon SageMaker Roles.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateDeviceFleetRequest$RoleArn' => 'The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
', 'CreateEdgePackagingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.
', 'CreateEndpointConfigInput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform actions on your behalf. For more information, see SageMaker Roles.
To be able to pass this role to Amazon SageMaker, the caller of this action must have the iam:PassRole
permission.
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore
if an OfflineStoreConfig
is provided.
The Amazon Resource Name (ARN) of the role needed to call other services on your behalf. For example, arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298
.
The ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'CreateInferenceExperimentRequest$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'CreateInferenceRecommendationsJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'CreateLabelingJobRequest$RoleArn' => 'The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
', 'CreateModelBiasJobDefinitionRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateModelExplainabilityJobDefinitionRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateModelInput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateNotebookInstanceInput$RoleArn' => 'When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
The Amazon Resource Name (ARN) of the role used by the pipeline to access and create resources.
', 'CreateProcessingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateTrainingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
The ARN of the execution role for the space.
', 'DescribeAutoMLJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeAutoMLJobV2Response$RoleArn' => 'The ARN of the Identity and Access Management role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeCompilationJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to perform the model compilation job.
', 'DescribeDataQualityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeDeviceFleetResponse$RoleArn' => 'The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
', 'DescribeEdgePackagingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
', 'DescribeEndpointConfigOutput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you assigned to the endpoint configuration.
', 'DescribeFeatureGroupResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
', 'DescribeFlowDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) execution role for the flow definition.
', 'DescribeImageResponse$RoleArn' => 'The ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'DescribeInferenceExperimentResponse$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'DescribeInferenceRecommendationsJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role you provided when you initiated the job.
', 'DescribeLabelingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.
', 'DescribeModelBiasJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeModelExplainabilityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeModelOutput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
', 'DescribeModelQualityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeNotebookInstanceOutput$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role associated with the instance.
', 'DescribePipelineResponse$RoleArn' => 'The Amazon Resource Name (ARN) that the pipeline uses to execute.
', 'DescribeProcessingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeTrainingJobResponse$RoleArn' => 'The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
', 'FeatureGroup$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.
', 'HyperParameterTrainingJobDefinition$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
', 'InferenceExperimentSummary$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'InferenceRecommendationsJob$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'Model$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
', 'ModelPackageValidationSpecification$ValidationRole' => 'The IAM roles to be used for the validation of the model package.
', 'ModelRegisterSettings$CrossAccountModelRegisterRoleArn' => 'The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services account in which SageMaker model registry is set up.
', 'MonitoringJobDefinition$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'Pipeline$RoleArn' => 'The Amazon Resource Name (ARN) of the role that created the pipeline.
', 'PipelineSummary$RoleArn' => 'The Amazon Resource Name (ARN) that the pipeline used to execute.
', 'ProcessingJob$RoleArn' => 'The ARN of the role used to create the processing job.
', 'RStudioServerProDomainSettings$DomainExecutionRoleArn' => 'The ARN of the execution role for the RStudioServerPro
Domain-level app.
The execution role for the RStudioServerPro
Domain-level app.
The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
', 'RenderUiTemplateRequest$RoleArn' => 'The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.
', 'TimeSeriesForecastingSettings$AmazonForecastRoleArn' => 'The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default, Canvas uses the execution role specified in the UserProfile
that launches the Canvas application. If an execution role is not specified in the UserProfile
, Canvas uses the execution role specified in the Domain that owns the UserProfile
. To allow time series forecasting, this IAM role should have the AmazonSageMakerCanvasForecastAccess policy attached and forecast.amazonaws.com
added in the trust relationship as a service principal.
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
', 'UpdateDeviceFleetRequest$RoleArn' => 'The Amazon Resource Name (ARN) of the device.
', 'UpdateImageRequest$RoleArn' => 'The new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'UpdateNotebookInstanceInput$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
The Amazon Resource Name (ARN) that the pipeline uses to execute.
', 'UserSettings$ExecutionRole' => 'The execution role for the user.
', ], ], 'RollingUpdatePolicy' => [ 'base' => 'Specifies a rolling deployment strategy for updating a SageMaker endpoint.
', 'refs' => [ 'DeploymentConfig$RollingUpdatePolicy' => 'Specifies a rolling deployment strategy for updating a SageMaker endpoint.
', ], ], 'RootAccess' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$RootAccess' => 'Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled
.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Whether root access is enabled or disabled for users of the notebook instance.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled
.
If you set this to Disabled
, users don\'t have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.
Sets how the endpoint routes incoming traffic:
LEAST_OUTSTANDING_REQUESTS
: The endpoint routes requests to the specific instances that have more capacity to process them.
RANDOM
: The endpoint routes each request to a randomly chosen instance.
The name of the rule configuration. It must be unique relative to other rule configuration names.
', 'DebugRuleEvaluationStatus$RuleConfigurationName' => 'The name of the rule configuration.
', 'ProfilerRuleConfiguration$RuleConfigurationName' => 'The name of the rule configuration. It must be unique relative to other rule configuration names.
', 'ProfilerRuleEvaluationStatus$RuleConfigurationName' => 'The name of the rule configuration.
', ], ], 'RuleEvaluationStatus' => [ 'base' => NULL, 'refs' => [ 'DebugRuleEvaluationStatus$RuleEvaluationStatus' => 'Status of the rule evaluation.
', 'ProfilerRuleEvaluationStatus$RuleEvaluationStatus' => 'Status of the rule evaluation.
', ], ], 'RuleParameters' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$RuleParameters' => 'Runtime configuration for rule container.
', 'ProfilerRuleConfiguration$RuleParameters' => 'Runtime configuration for rule container.
', ], ], 'S3DataDistribution' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$S3DataDistributionType' => 'If you want SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify FullyReplicated
.
If you want SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify ShardedByS3Key
. If there are n ML compute instances launched for a training job, each instance gets approximately 1/n of the number of S3 objects. In this case, model training on each machine uses only the subset of training data.
Don\'t choose more ML compute instances for training than available S3 objects. If you do, some nodes won\'t get any data and you will pay for nodes that aren\'t getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances, you might choose ShardedByS3Key
. If the algorithm requires copying training data to the ML storage volume (when TrainingInputMode
is set to File
), this copies 1/n of the number of objects.
Describes the S3 data source.
Your input bucket must be in the same Amazon Web Services region as your training job.
', 'refs' => [ 'DataSource$S3DataSource' => 'The S3 location of the data source that is associated with a channel.
', ], ], 'S3DataType' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$S3DataType' => 'If you choose S3Prefix
, S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
If you choose ManifestFile
, S3Uri
identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
If you choose AugmentedManifestFile
, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile
can only be used if the Channel\'s input mode is Pipe
.
If you choose S3Prefix
, S3Uri
identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.
If you choose ManifestFile
, S3Uri
identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.
The following values are compatible: ManifestFile
, S3Prefix
The following value is not compatible: AugmentedManifestFile
Specifies the S3 location of ML model data to deploy.
', 'refs' => [ 'ModelDataSource$S3DataSource' => 'Specifies the S3 location of ML model data to deploy.
', ], ], 'S3ModelDataType' => [ 'base' => NULL, 'refs' => [ 'S3ModelDataSource$S3DataType' => 'Specifies the type of ML model data to deploy.
If you choose S3Prefix
, S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix as part of the ML model data to deploy. A valid key name prefix identified by S3Uri
always ends with a forward slash (/).
If you choose S3Object
, S3Uri
identifies an object that is the ML model data to deploy.
Specifies the S3 path of ML model data to deploy.
', ], ], 'S3OutputPath' => [ 'base' => NULL, 'refs' => [ 'HubS3StorageConfig$S3OutputPath' => 'The Amazon S3 bucket prefix for hosting hub content.
', ], ], 'S3StorageConfig' => [ 'base' => 'The Amazon Simple Storage (Amazon S3) location and and security configuration for OfflineStore
.
The Amazon Simple Storage (Amazon S3) location of OfflineStore
.
The uniform resource identifier (URI) used to identify an additional data source used in inference or training.
', 'AthenaDatasetDefinition$OutputS3Uri' => 'The location in Amazon S3 where Athena query results are stored.
', 'AutoMLCandidateGenerationConfig$FeatureSpecificationS3Uri' => 'A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames
(optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }
.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric
, categorical
, text
, and datetime
. In HPO mode, Autopilot can support numeric
, categorical
, text
, datetime
, and sequence
.
If only FeatureDataTypes
is provided, the column keys (col1
, col2
,..) should be a subset of the column names in the input data.
If both FeatureDataTypes
and FeatureAttributeNames
are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames
.
The key name FeatureAttributeNames
is fixed. The values listed in ["col1", "col2", ...]
are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
The Amazon S3 output path. Must be 128 characters or less.
', 'AutoMLS3DataSource$S3Uri' => 'The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.
', 'BatchDataCaptureConfig$DestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'CheckpointConfig$S3Uri' => 'Identifies the S3 path where you want SageMaker to store checkpoints. For example, s3://bucket-name/key-name-prefix
.
An Amazon S3 bucket path where your LifeCycle scripts are stored.
', 'CreateLabelingJobRequest$LabelCategoryConfigS3Uri' => 'The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to "labels"
, you must provide worker instructions in the label category configuration file using the "instructions"
parameter: "instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}
. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .
For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1
, label_2
,...
,label_n
with your label categories.
{
"document-version": "2018-11-28",
"labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]
}
Note the following about the label category configuration file:
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
Each label category must be unique, you cannot specify duplicate label categories.
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName
in the label category configuration. Use this parameter to enter the LabelAttributeName
of the labeling job you want to adjust or verify annotations of.
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.
', 'DataQualityAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'DataQualityAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'DebugHookConfig$S3OutputPath' => 'Path to Amazon S3 storage location for metrics and tensors.
', 'DebugRuleConfiguration$S3OutputPath' => 'Path to Amazon S3 storage location for rules.
', 'DescribeEdgePackagingJobResponse$ModelArtifact' => 'The Amazon Simple Storage (S3) URI where model artifacts ares stored.
', 'DescribeLabelingJobResponse$LabelCategoryConfigS3Uri' => 'The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:
Semantic segmentation labeling jobs using automated labeling: 20 labels
Box bounding labeling jobs (all): 10 labels
The file is a JSON structure in the following format:
{
"document-version": "2018-11-28"
"labels": [
{
"label": "label 1"
},
{
"label": "label 2"
},
...
{
"label": "label n"
}
]
}
The Amazon Simple Storage (S3) bucker URI.
', 'FileSource$S3Uri' => 'The Amazon S3 URI for the file source.
', 'FlowDefinitionOutputConfig$S3OutputPath' => 'The Amazon S3 path where the object containing human output will be made available.
To learn more about the format of Amazon A2I output data, see Amazon A2I Output Data.
', 'InferenceRecommendationsJob$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'InputConfig$S3Uri' => 'The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'LabelingJobOutput$OutputDatasetS3Uri' => 'The Amazon S3 bucket location of the manifest file for labeled data.
', 'LabelingJobOutputConfig$S3OutputPath' => 'The Amazon S3 location to write output data.
', 'LabelingJobS3DataSource$ManifestS3Uri' => 'The Amazon S3 location of the manifest file that describes the input data objects.
The input manifest file referenced in ManifestS3Uri
must contain one of the following keys: source-ref
or source
. The value of the keys are interpreted as follows:
source-ref
: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.
source
: The source of the object is the value. Use this value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.
', 'MetricsSource$S3Uri' => 'The S3 URI for the metrics source.
', 'ModelArtifacts$S3ModelArtifacts' => 'The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz
.
JSON formatted S3 file that defines bias parameters. For more information on this JSON configuration file, see Configure bias parameters.
', 'ModelCardExportArtifacts$S3ExportArtifacts' => 'The Amazon S3 URI of the exported model artifacts.
', 'ModelCardExportOutputConfig$S3OutputPath' => 'The Amazon S3 output path to export your model card PDF.
', 'ModelExplainabilityAppSpecification$ConfigUri' => 'JSON formatted Amazon S3 file that defines explainability parameters. For more information on this JSON configuration file, see Configure model explainability parameters.
', 'ModelQualityAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'ModelQualityAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'MonitoringAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'MonitoringAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'MonitoringConstraintsResource$S3Uri' => 'The Amazon S3 URI for the constraints resource.
', 'MonitoringStatisticsResource$S3Uri' => 'The Amazon S3 URI for the statistics resource.
', 'OutputConfig$S3OutputLocation' => 'Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix
.
Identifies the S3 path where you want SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix
.
The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
', 'ProcessingS3Output$S3Uri' => 'A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
', 'ProfilerConfig$S3OutputPath' => 'Path to Amazon S3 storage location for system and framework metrics.
', 'ProfilerConfigForUpdate$S3OutputPath' => 'Path to Amazon S3 storage location for system and framework metrics.
', 'ProfilerRuleConfiguration$S3OutputPath' => 'Path to Amazon S3 storage location for rules.
', 'RecommendationJobCompiledOutputConfig$S3OutputUri' => 'Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.
', 'RecommendationJobPayloadConfig$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'RedshiftDatasetDefinition$OutputS3Uri' => 'The location in Amazon S3 where the Redshift query results are stored.
', 'S3DataSource$S3Uri' => 'Depending on the value specified for the S3DataType
, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix/
A manifest might look like this: s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of S3Uri
. Note that the prefix must be a valid non-empty S3Uri
that precludes users from specifying a manifest whose individual S3Uri
is sourced from different S3 buckets.
The following code example shows a valid manifest format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
This JSON is equivalent to the following S3Uri
list:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uri
in this manifest is the input data for the channel for this data source. The object that each S3Uri
points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
', 'S3StorageConfig$S3Uri' => 'The S3 URI, or location in Amazon S3, of OfflineStore
.
S3 URIs have a format similar to the following: s3://example-bucket/prefix/
.
The S3 path where offline records are written.
', 'SharingSettings$S3OutputPath' => 'When NotebookOutputOption
is Allowed
, the Amazon S3 bucket used to store the shared notebook snapshots.
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job V2. You can input FeatureAttributeNames
(optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }
.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric
, categorical
, text
, and datetime
. In HPO mode, Autopilot can support numeric
, categorical
, text
, datetime
, and sequence
.
If only FeatureDataTypes
is provided, the column keys (col1
, col2
,..) should be a subset of the column names in the input data.
If both FeatureDataTypes
and FeatureAttributeNames
are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames
.
The key name FeatureAttributeNames
is fixed. The values listed in ["col1", "col2", ...]
are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
Path to Amazon S3 storage location for TensorBoard output.
', 'TimeSeriesForecastingJobConfig$FeatureSpecificationS3Uri' => 'A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig
. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig
. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig
.
You can input FeatureAttributeNames
(optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }
.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
Autopilot supports the following data types: numeric
, categorical
, text
, and datetime
.
These column keys must not include any column set in TimeSeriesConfig
.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example, s3://bucket-name/key-name-prefix
.
For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out
suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at s3://bucket-name/input-name-prefix/dataset01/data.csv
, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out
. Batch transform doesn\'t upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out
file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.
Depending on the value specified for the S3DataType
, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix/
.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
The preceding JSON matches the following S3Uris
:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris
in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris
points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
', 'WorkspaceSettings$S3ArtifactPath' => 'The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users must log out and log back in to apply the new location.
', ], ], 'SageMakerImageVersionAlias' => [ 'base' => NULL, 'refs' => [ 'DeleteImageVersionRequest$Alias' => 'The alias of the image to delete.
', 'DescribeImageVersionRequest$Alias' => 'The alias of the image version.
', 'ListAliasesRequest$Alias' => 'The alias of the image version.
', 'SageMakerImageVersionAliases$member' => NULL, 'UpdateImageVersionRequest$Alias' => 'The alias of the image version.
', ], ], 'SageMakerImageVersionAliases' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$Aliases' => 'A list of aliases created with the image version.
', 'ListAliasesResponse$SageMakerImageVersionAliases' => 'A list of SageMaker image version aliases.
', 'UpdateImageVersionRequest$AliasesToAdd' => 'A list of aliases to add.
', 'UpdateImageVersionRequest$AliasesToDelete' => 'A list of aliases to delete.
', ], ], 'SagemakerServicecatalogStatus' => [ 'base' => NULL, 'refs' => [ 'GetSagemakerServicecatalogPortfolioStatusOutput$Status' => 'Whether Service Catalog is enabled or disabled in SageMaker.
', ], ], 'SampleWeightAttributeName' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$SampleWeightAttributeName' => 'If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
', 'TabularJobConfig$SampleWeightAttributeName' => 'If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
', ], ], 'SamplingPercentage' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$InitialSamplingPercentage' => 'The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints with high traffic.
', 'DataCaptureConfigSummary$CurrentSamplingPercentage' => 'The percentage of requests being captured by your Endpoint.
', ], ], 'ScalingPolicies' => [ 'base' => NULL, 'refs' => [ 'DynamicScalingConfiguration$ScalingPolicies' => 'An object of the scaling policies for each metric.
', ], ], 'ScalingPolicy' => [ 'base' => 'An object containing a recommended scaling policy.
', 'refs' => [ 'ScalingPolicies$member' => NULL, ], ], 'ScalingPolicyMetric' => [ 'base' => 'The metric for a scaling policy.
', 'refs' => [ 'GetScalingConfigurationRecommendationResponse$Metric' => 'An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job.
', ], ], 'ScalingPolicyObjective' => [ 'base' => 'An object where you specify the anticipated traffic pattern for an endpoint.
', 'refs' => [ 'GetScalingConfigurationRecommendationRequest$ScalingPolicyObjective' => 'An object where you specify the anticipated traffic pattern for an endpoint.
', 'GetScalingConfigurationRecommendationResponse$ScalingPolicyObjective' => 'An object representing the anticipated traffic pattern for an endpoint that you specified in the request.
', ], ], 'ScheduleConfig' => [ 'base' => 'Configuration details about the monitoring schedule.
', 'refs' => [ 'MonitoringScheduleConfig$ScheduleConfig' => 'Configures the monitoring schedule.
', ], ], 'ScheduleExpression' => [ 'base' => NULL, 'refs' => [ 'ScheduleConfig$ScheduleExpression' => 'A cron expression that describes details about the monitoring schedule.
The supported cron expressions are:
If you want to set the job to start every hour, use the following:
Hourly: cron(0 * ? * * *)
If you want to start the job daily:
cron(0 [00-23] ? * * *)
If you want to run the job one time, immediately, use the following keyword:
NOW
For example, the following are valid cron expressions:
Daily at noon UTC: cron(0 12 ? * * *)
Daily at midnight UTC: cron(0 0 ? * * *)
To support running every 6, 12 hours, the following are also supported:
cron(0 [00-23]/[01-24] ? * * *)
For example, the following are valid cron expressions:
Every 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)
Every two hours starting at midnight: cron(0 0/2 ? * * *)
Even though the cron expression is set to start at 5PM UTC, note that there could be a delay of 0-20 minutes from the actual requested time to run the execution.
We recommend that if you would like a daily schedule, you do not provide this parameter. Amazon SageMaker will pick a time for running every day.
You can also specify the keyword NOW
to run the monitoring job immediately, one time, without recurring.
The status of an monitoring job.
', 'ListMonitoringSchedulesRequest$StatusEquals' => 'A filter that returns only monitoring schedules modified before a specified time.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleStatus' => 'The status of the monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleStatus' => 'The status of the monitoring schedule. This can be one of the following values.
PENDING
- The schedule is pending being created.
FAILED
- The schedule failed.
SCHEDULED
- The schedule was successfully created.
STOPPED
- The schedule was stopped.
The status of the monitoring schedule.
', ], ], 'SearchExpression' => [ 'base' => 'A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression
can contain up to twenty elements.
A SearchExpression
contains the following components:
A list of Filter
objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter
objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions.
A list of SearchExpression
objects. A search expression object can be nested in a list of search expression objects.
A Boolean operator: And
or Or
.
A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions
, NestedFilters
, and Filters
that can be included in a SearchExpression
object is 50.
A list of search expression objects.
', ], ], 'SearchRecord' => [ 'base' => 'A single resource returned as part of the Search API response.
', 'refs' => [ 'SearchResultsList$member' => NULL, ], ], 'SearchRequest' => [ 'base' => NULL, 'refs' => [], ], 'SearchResponse' => [ 'base' => NULL, 'refs' => [], ], 'SearchResultsList' => [ 'base' => NULL, 'refs' => [ 'SearchResponse$Results' => 'A list of SearchRecord
objects.
How SearchResults
are ordered. Valid values are Ascending
or Descending
. The default is Descending
.
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage
under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting
- Starting the training job.
Downloading
- An optional stage for algorithms that support File
training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training
- Training is in progress.
Interrupted
- The job stopped because the managed spot training instances were interrupted.
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
Completed
- The training job has completed.
Failed
- The training job has failed. The reason for the failure is returned in the FailureReason
field of DescribeTrainingJobResponse
.
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime.
MaxWaitTimeExceeded
- The job stopped because it exceeded the maximum allowed wait time.
Stopped
- The training job has stopped.
Stopping
- Stopping the training job.
Valid values for SecondaryStatus
are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTraining
DownloadingTrainingImage
Contains a secondary status information from a training job.
Status might be one of the following secondary statuses:
Starting
- Starting the training job.
Downloading
- An optional stage for algorithms that support File
training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training
- Training is in progress.
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
Completed
- The training job has completed.
Failed
- The training job has failed. The reason for the failure is returned in the FailureReason
field of DescribeTrainingJobResponse
.
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime.
Stopped
- The training job has stopped.
Stopping
- Stopping the training job.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage
under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting
- Starting the training job.
Downloading
- An optional stage for algorithms that support File
training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training
- Training is in progress.
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
Completed
- The training job has completed.
Failed
- The training job has failed. The reason for the failure is returned in the FailureReason
field of DescribeTrainingJobResponse
.
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime.
Stopped
- The training job has stopped.
Stopping
- Stopping the training job.
Valid values for SecondaryStatus
are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
An array element of SecondaryStatusTransitions
for DescribeTrainingJob. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job\'s secondary status.
A history of all of the secondary statuses that the training job has transitioned through.
', 'TrainingJob$SecondaryStatusTransitions' => 'A history of all of the secondary statuses that the training job has transitioned through.
', ], ], 'SecretArn' => [ 'base' => NULL, 'refs' => [ 'GitConfig$SecretArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT
and must be in the following format:
{"username": UserName, "password": Password}
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT
and must be in the following format:
{"username": UserName, "password": Password}
The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your identity provider, such as the client ID and secret, authorization URL, and token URL.
', ], ], 'SecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'DescribeDomainResponse$SecurityGroupIdForDomainBoundary' => 'The ID of the security group that authorizes traffic between the RSessionGateway
apps and the RStudioServerPro
app.
The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', 'DefaultSpaceSettings$SecurityGroups' => 'The security group IDs for the Amazon Virtual Private Cloud that the space uses for communication.
', 'DescribeNotebookInstanceOutput$SecurityGroups' => 'The IDs of the VPC security groups.
', 'UserSettings$SecurityGroups' => 'The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
Optional when the CreateDomain.AppNetworkAccessType
parameter is set to PublicInternetOnly
.
Required when the CreateDomain.AppNetworkAccessType
parameter is set to VpcOnly
, unless specified as part of the DefaultUserSettings
for the domain.
Amazon SageMaker adds a security group to allow NFS traffic from Amazon SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
', ], ], 'Seed' => [ 'base' => NULL, 'refs' => [ 'ShuffleConfig$Seed' => 'Determines the shuffling order in ShuffleConfig
value.
A step selected to run in selective execution mode.
', 'refs' => [ 'SelectedStepList$member' => NULL, ], ], 'SelectedStepList' => [ 'base' => NULL, 'refs' => [ 'SelectiveExecutionConfig$SelectedSteps' => 'A list of pipeline steps to run. All step(s) in all path(s) between two selected steps should be included.
', ], ], 'SelectiveExecutionConfig' => [ 'base' => 'The selective execution configuration applied to the pipeline run.
', 'refs' => [ 'DescribePipelineExecutionResponse$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', 'PipelineExecution$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', 'StartPipelineExecutionRequest$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', ], ], 'SelectiveExecutionResult' => [ 'base' => 'The ARN from an execution of the current pipeline.
', 'refs' => [ 'PipelineExecutionStep$SelectiveExecutionResult' => 'The ARN from an execution of the current pipeline from which results are reused for this step.
', ], ], 'SendPipelineExecutionStepFailureRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepFailureResponse' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepSuccessRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepSuccessResponse' => [ 'base' => NULL, 'refs' => [], ], 'ServerlessMaxConcurrency' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$MaxConcurrency' => 'The maximum number of concurrent invocations your serverless endpoint can process.
', 'ProductionVariantServerlessUpdateConfig$MaxConcurrency' => 'The updated maximum number of concurrent invocations your serverless endpoint can process.
', ], ], 'ServerlessMemorySizeInMB' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$MemorySizeInMB' => 'The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
', ], ], 'ServerlessProvisionedConcurrency' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$ProvisionedConcurrency' => 'The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency
.
This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
The updated amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency
.
The ID of the provisioned product.
', 'ServiceCatalogProvisioningDetails$ProductId' => 'The ID of the product to provision.
', 'ServiceCatalogProvisioningDetails$ProvisioningArtifactId' => 'The ID of the provisioning artifact.
', 'ServiceCatalogProvisioningDetails$PathId' => 'The path identifier of the product. This value is optional if the product has a default path, and required if the product has more than one path.
', 'ServiceCatalogProvisioningUpdateDetails$ProvisioningArtifactId' => 'The ID of the provisioning artifact.
', ], ], 'ServiceCatalogProvisionedProductDetails' => [ 'base' => 'Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'DescribeProjectOutput$ServiceCatalogProvisionedProductDetails' => 'Information about a provisioned service catalog product.
', 'Project$ServiceCatalogProvisionedProductDetails' => NULL, ], ], 'ServiceCatalogProvisioningDetails' => [ 'base' => 'Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'CreateProjectInput$ServiceCatalogProvisioningDetails' => 'The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don\'t provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
', 'DescribeProjectOutput$ServiceCatalogProvisioningDetails' => 'Information used to provision a service catalog product. For information, see What is Amazon Web Services Service Catalog.
', 'Project$ServiceCatalogProvisioningDetails' => NULL, ], ], 'ServiceCatalogProvisioningUpdateDetails' => [ 'base' => 'Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'UpdateProjectInput$ServiceCatalogProvisioningUpdateDetails' => 'The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don\'t provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
', ], ], 'SessionExpirationDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlRequest$SessionExpirationDurationInSeconds' => 'The session expiration duration in seconds. This value defaults to 43200.
', 'CreatePresignedNotebookInstanceUrlInput$SessionExpirationDurationInSeconds' => 'The duration of the session, in seconds. The default is 12 hours.
', ], ], 'ShadowModeConfig' => [ 'base' => ' The configuration of ShadowMode
inference experiment type, which specifies a production variant to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode
inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode
inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode
inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The name and sampling percentage of a shadow variant.
', 'refs' => [ 'ShadowModelVariantConfigList$member' => NULL, ], ], 'ShadowModelVariantConfigList' => [ 'base' => NULL, 'refs' => [ 'ShadowModeConfig$ShadowModelVariants' => 'List of shadow variant configurations.
', ], ], 'SharingSettings' => [ 'base' => 'Specifies options for sharing Amazon SageMaker Studio notebooks. These settings are specified as part of DefaultUserSettings
when the CreateDomain
API is called, and as part of UserSettings
when the CreateUserProfile
API is called. When SharingSettings
is not specified, notebook sharing isn\'t allowed.
Specifies options for sharing Amazon SageMaker Studio notebooks.
', ], ], 'SharingType' => [ 'base' => NULL, 'refs' => [ 'SpaceSharingSettings$SharingType' => 'Specifies the sharing type of the space.
', 'SpaceSharingSettingsSummary$SharingType' => 'Specifies the sharing type of the space.
', ], ], 'ShuffleConfig' => [ 'base' => 'A configuration for a shuffle option for input data in a channel. If you use S3Prefix
for S3DataType
, the results of the S3 key prefix matches are shuffled. If you use ManifestFile
, the order of the S3 object references in the ManifestFile
is shuffled. If you use AugmentedManifestFile
, the order of the JSON lines in the AugmentedManifestFile
is shuffled. The shuffling order is determined using the Seed
value.
For Pipe input mode, when ShuffleConfig
is specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig
is combined with S3DataDistributionType
of ShardedByS3Key
, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
A configuration for a shuffle option for input data in a channel. If you use S3Prefix
for S3DataType
, this shuffles the results of the S3 key prefix matches. If you use ManifestFile
, the order of the S3 object references in the ManifestFile
is shuffled. If you use AugmentedManifestFile
, the order of the JSON lines in the AugmentedManifestFile
is shuffled. The shuffling order is determined using the Seed
value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType
of ShardedByS3Key
, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
The ARN of the application managed by SageMaker in IAM Identity Center. This value is only returned for domains created after October 1, 2023.
', ], ], 'SingleSignOnUserIdentifier' => [ 'base' => NULL, 'refs' => [ 'CreateUserProfileRequest$SingleSignOnUserIdentifier' => 'A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain\'s AuthMode is IAM Identity Center, this field is required. If the Domain\'s AuthMode is not IAM Identity Center, this field cannot be specified.
', 'DescribeUserProfileResponse$SingleSignOnUserIdentifier' => 'The IAM Identity Center user identifier.
', ], ], 'SkipModelValidation' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$SkipModelValidation' => 'Indicates if you want to skip model validation.
', 'DescribeModelPackageOutput$SkipModelValidation' => 'Indicates if you want to skip model validation.
', 'ModelPackage$SkipModelValidation' => 'Indicates if you want to skip model validation.
', ], ], 'SnsTopicArn' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceNotificationConfig$SuccessTopic' => 'Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
', 'AsyncInferenceNotificationConfig$ErrorTopic' => 'Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
', 'LabelingJobOutputConfig$SnsTopicArn' => 'An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn
if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.
If you provide an SnsTopicArn
in OutputConfig
, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.
To learn more, see Receive Output Data from a Streaming Labeling Job.
', 'LabelingJobSnsDataSource$SnsTopicArn' => 'The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.
', ], ], 'SortActionsBy' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime
.
The property used to sort results. The default value is CreationTime
.
The property used to sort results. The default value is CreationTime
.
The field to sort results by. The default is CreationTime
.
The field to sort results by. The default is CreationTime
.
The field to sort results by. The default is CreationTime
.
The field to sort results by. The default is CreationTime
.
The property used to sort results. The default value is CreationTime
.
The property used to sort results. The default value is CreationTime
.
The column by which to sort the listed inference experiments.
', ], ], 'SortLineageGroupsBy' => [ 'base' => NULL, 'refs' => [ 'ListLineageGroupsRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime
.
The sort order. The default value is Descending
.
The sort order for the results. The default is Ascending
.
The sort order. The default value is Descending
.
The sort order for the results. The default is Ascending.
', 'ListArtifactsRequest$SortOrder' => 'The sort order. The default value is Descending
.
The sort order. The default value is Descending
.
The sort order for results. The default value is Ascending
.
The sort order for results. The default value is Ascending
.
The sort order for results. The default is Ascending
.
The sort order. The default value is Descending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
What direction to sort in.
', 'ListEdgeDeploymentPlansRequest$SortOrder' => 'The direction of the sorting (ascending or descending).
', 'ListEdgePackagingJobsRequest$SortOrder' => 'What direction to sort by.
', 'ListExperimentsRequest$SortOrder' => 'The sort order. The default value is Descending
.
An optional value that specifies whether you want the results sorted in Ascending
or Descending
order.
Sort hub content versions by ascending or descending order.
', 'ListHubContentsRequest$SortOrder' => 'Sort hubs by ascending or descending order.
', 'ListHubsRequest$SortOrder' => 'Sort hubs by ascending or descending order.
', 'ListHumanTaskUisRequest$SortOrder' => 'An optional value that specifies whether you want the results sorted in Ascending
or Descending
order.
The sort order for results. The default is Ascending
.
The direction of sorting (ascending or descending).
', 'ListInferenceRecommendationsJobsRequest$SortOrder' => 'The sort order for the results.
', 'ListLabelingJobsForWorkteamRequest$SortOrder' => 'The sort order for results. The default is Ascending
.
The sort order for results. The default is Ascending
.
The sort order for the results. The default is Ascending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
The sort order for results. The default is Ascending
.
The sort order for the results. The default is Ascending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
The sort order, whether Ascending
or Descending
, of the alert history. The default is Descending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
Whether to sort the results in Ascending
or Descending
order. The default is Descending
.
The field by which to sort results. The default is CreatedTime
.
The sort order for results.
', 'ListPipelinesRequest$SortOrder' => 'The sort order for results.
', 'ListProcessingJobsRequest$SortOrder' => 'The sort order for results. The default is Ascending
.
The sort order for the results. The default is Ascending
.
The sort order. The default value is Descending.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$SortOrder' => 'The sort order for results. The default is Ascending
.
The sort order for results. The default is Ascending
.
The sort order for results. The default is Descending
.
The sort order. The default value is Descending
.
The sort order. The default value is Descending
.
The sort order for the results. The default is Ascending.
', 'ListWorkforcesRequest$SortOrder' => 'Sort workforces in ascending or descending order.
', 'ListWorkteamsRequest$SortOrder' => 'The sort order for results. The default is Ascending
.
The field by which to sort results. The default is CreatedTime
.
The field by which to sort results. The default is CreatedTime
.
The property used to sort results. The default value is CreationTime
.
The property used to sort results. The default value is CreationTime
.
Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
', 'refs' => [ 'SourceAlgorithmList$member' => NULL, ], ], 'SourceAlgorithmList' => [ 'base' => NULL, 'refs' => [ 'SourceAlgorithmSpecification$SourceAlgorithms' => 'A list of the algorithms that were used to create a model package.
', ], ], 'SourceAlgorithmSpecification' => [ 'base' => 'A list of algorithms that were used to create a model package.
', 'refs' => [ 'CreateModelPackageInput$SourceAlgorithmSpecification' => 'Details about the algorithm that was used to create the model package.
', 'DescribeModelPackageOutput$SourceAlgorithmSpecification' => 'Details about the algorithm that was used to create the model package.
', 'ModelPackage$SourceAlgorithmSpecification' => 'A list of algorithms that were used to create a model package.
', ], ], 'SourceIpConfig' => [ 'base' => 'A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to login to their worker portal from an IP address within this range. By default, a workforce isn\'t restricted to specific IP addresses.
', 'refs' => [ 'CreateWorkforceRequest$SourceIpConfig' => NULL, 'UpdateWorkforceRequest$SourceIpConfig' => 'A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce.
Maximum: Ten CIDR values
', 'Workforce$SourceIpConfig' => 'A list of one to ten IP address ranges (CIDRs) to be added to the workforce allow list. By default, a workforce isn\'t restricted to specific IP addresses.
', ], ], 'SourceType' => [ 'base' => NULL, 'refs' => [ 'ExperimentSource$SourceType' => 'The source type.
', 'TrialComponentSource$SourceType' => 'The source job type.
', 'TrialSource$SourceType' => 'The source job type.
', ], ], 'SourceUri' => [ 'base' => NULL, 'refs' => [ 'ActionSource$SourceUri' => 'The URI of the source.
', 'ArtifactSource$SourceUri' => 'The URI of the source.
', 'ContextSource$SourceUri' => 'The URI of the source.
', 'ListActionsRequest$SourceUri' => 'A filter that returns only actions with the specified source URI.
', 'ListArtifactsRequest$SourceUri' => 'A filter that returns only artifacts with the specified source URI.
', 'ListContextsRequest$SourceUri' => 'A filter that returns only contexts with the specified source URI.
', ], ], 'SpaceArn' => [ 'base' => NULL, 'refs' => [ 'CreateSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', 'DescribeSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', 'UpdateSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', ], ], 'SpaceCodeEditorAppSettings' => [ 'base' => 'The application settings for a Code Editor space.
', 'refs' => [ 'SpaceSettings$CodeEditorAppSettings' => 'The Code Editor application settings.
', ], ], 'SpaceDetails' => [ 'base' => 'The space\'s details.
', 'refs' => [ 'SpaceList$member' => NULL, ], ], 'SpaceEbsVolumeSizeInGb' => [ 'base' => NULL, 'refs' => [ 'DefaultEbsStorageSettings$DefaultEbsVolumeSizeInGb' => 'The default size of the EBS storage volume for a private space.
', 'DefaultEbsStorageSettings$MaximumEbsVolumeSizeInGb' => 'The maximum size of the EBS storage volume for a private space.
', 'EbsStorageSettings$EbsVolumeSizeInGb' => 'The size of an EBS storage volume for a private space.
', ], ], 'SpaceJupyterLabAppSettings' => [ 'base' => 'The settings for the JupyterLab application within a space.
', 'refs' => [ 'SpaceSettings$JupyterLabAppSettings' => 'The settings for the JupyterLab application.
', ], ], 'SpaceList' => [ 'base' => NULL, 'refs' => [ 'ListSpacesResponse$Spaces' => 'The list of spaces.
', ], ], 'SpaceName' => [ 'base' => NULL, 'refs' => [ 'AppDetails$SpaceName' => 'The name of the space.
', 'CreateAppRequest$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName
must be set.
The name of the space.
', 'CreateSpaceRequest$SpaceName' => 'The name of the space.
', 'DeleteAppRequest$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName
must be set.
The name of the space.
', 'DescribeAppRequest$SpaceName' => 'The name of the space.
', 'DescribeAppResponse$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName
must be set.
The name of the space.
', 'DescribeSpaceResponse$SpaceName' => 'The name of the space.
', 'ListAppsRequest$SpaceNameEquals' => 'A parameter to search by space name. If UserProfileNameEquals
is set, then this value cannot be set.
A parameter by which to filter the results.
', 'SpaceDetails$SpaceName' => 'The name of the space.
', 'UpdateSpaceRequest$SpaceName' => 'The name of the space.
', ], ], 'SpaceSettings' => [ 'base' => 'A collection of space settings.
', 'refs' => [ 'CreateSpaceRequest$SpaceSettings' => 'A collection of space settings.
', 'DescribeSpaceResponse$SpaceSettings' => 'A collection of space settings.
', 'UpdateSpaceRequest$SpaceSettings' => 'A collection of space settings.
', ], ], 'SpaceSettingsSummary' => [ 'base' => 'Specifies summary information about the space settings.
', 'refs' => [ 'SpaceDetails$SpaceSettingsSummary' => 'Specifies summary information about the space settings.
', ], ], 'SpaceSharingSettings' => [ 'base' => 'A collection of space sharing settings.
', 'refs' => [ 'CreateSpaceRequest$SpaceSharingSettings' => 'A collection of space sharing settings.
', 'DescribeSpaceResponse$SpaceSharingSettings' => 'The collection of space sharing settings for a space.
', ], ], 'SpaceSharingSettingsSummary' => [ 'base' => 'Specifies summary information about the space sharing settings.
', 'refs' => [ 'SpaceDetails$SpaceSharingSettingsSummary' => 'Specifies summary information about the space sharing settings.
', ], ], 'SpaceSortKey' => [ 'base' => NULL, 'refs' => [ 'ListSpacesRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime
.
The status.
', 'SpaceDetails$Status' => 'The status.
', ], ], 'SpaceStorageSettings' => [ 'base' => 'The storage settings for a private space.
', 'refs' => [ 'SpaceSettings$SpaceStorageSettings' => 'The storage settings for a private space.
', 'SpaceSettingsSummary$SpaceStorageSettings' => 'The storage settings for a private space.
', ], ], 'SpawnRate' => [ 'base' => NULL, 'refs' => [ 'Phase$SpawnRate' => 'Specified how many new users to spawn in a minute.
', ], ], 'SplitType' => [ 'base' => NULL, 'refs' => [ 'TransformInput$SplitType' => 'The method to use to split the transform job\'s data files into smaller batches. Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for SplitType
is None
, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter to Line
to split records on a newline character boundary. SplitType
also supports a number of record-oriented binary data formats. Currently, the supported record formats are:
RecordIO
TFRecord
When splitting is enabled, the size of a mini-batch depends on the values of the BatchStrategy
and MaxPayloadInMB
parameters. When the value of BatchStrategy
is MultiRecord
, Amazon SageMaker sends the maximum number of records in each request, up to the MaxPayloadInMB
limit. If the value of BatchStrategy
is SingleRecord
, Amazon SageMaker sends individual records in each request.
Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of BatchStrategy
is set to SingleRecord
. Padding is not removed if the value of BatchStrategy
is set to MultiRecord
.
For more information about RecordIO
, see Create a Dataset Using RecordIO in the MXNet documentation. For more information about TFRecord
, see Consuming TFRecord data in the TensorFlow documentation.
The general status of the current stage.
', ], ], 'Stairs' => [ 'base' => 'Defines the stairs traffic pattern for an Inference Recommender load test. This pattern type consists of multiple steps where the number of users increases at each step.
Specify either the stairs or phases traffic pattern.
', 'refs' => [ 'TrafficPattern$Stairs' => 'Defines the stairs traffic pattern.
', ], ], 'StartEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'StartMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'StartPipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartPipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'Statistic' => [ 'base' => NULL, 'refs' => [ 'CustomizedMetricSpecification$Statistic' => 'The statistic of the customized metric.
', ], ], 'StatusDetails' => [ 'base' => NULL, 'refs' => [ 'DebugRuleEvaluationStatus$StatusDetails' => 'Details from the rule evaluation.
', 'ProfilerRuleEvaluationStatus$StatusDetails' => 'Details from the rule evaluation.
', ], ], 'StatusMessage' => [ 'base' => NULL, 'refs' => [ 'SecondaryStatusTransition$StatusMessage' => 'A detailed description of the progress within a secondary status.
SageMaker provides secondary statuses and status messages that apply to each of them:
Starting the training job.
Launching requested ML instances.
Insufficient capacity error from EC2 while launching instances, retrying!
Launched instance was unhealthy, replacing it!
Preparing the instances for training.
Training image download completed. Training in progress.
Status messages are subject to change. Therefore, we recommend not including them in code that programmatically initiates actions. For examples, don\'t use status messages in if statements.
To have an overview of your training job\'s progress, view TrainingJobStatus
and SecondaryStatus
in DescribeTrainingJob, and StatusMessage
together. For example, at the start of a training job, you might see the following:
TrainingJobStatus
- InProgress
SecondaryStatus
- Training
StatusMessage
- Downloading the training image
The description of the step.
', ], ], 'StepDisplayName' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepDisplayName' => 'The display name of the step.
', ], ], 'StepName' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepName' => 'The name of the step that is executed.
', ], ], 'StepStatus' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepStatus' => 'The status of the step execution.
', ], ], 'StopAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'StopPipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopPipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StoppingCondition' => [ 'base' => 'Specifies a limit to how long a model training job or model compilation job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training or compilation job. Use this API to cap model training costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel
.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
', 'CreateTrainingJobRequest$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
', 'DescribeTrainingJobResponse$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
', 'TrainingJob$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.
', ], ], 'StorageType' => [ 'base' => NULL, 'refs' => [ 'OnlineStoreConfig$StorageType' => 'Option for different tiers of low latency storage for real-time data retrieval.
Standard
: A managed low latency data store for feature groups.
InMemory
: A managed data store for feature groups that supports very low latency retrieval.
if the overall status is Failed
, the reason for the failure.
The attributes of the input data that are the input features.
', 'BatchTransformInput$InferenceAttribute' => 'The attribute of the input data that represents the ground truth label.
', 'BatchTransformInput$ProbabilityAttribute' => 'In a classification problem, the attribute that represents the class probability.
', 'ClusterInstanceStatusDetails$Message' => 'The message from an instance in a SageMaker HyperPod cluster.
', 'ClusterNodeDetails$InstanceId' => 'The ID of the instance.
', 'ClusterNodeSummary$InstanceId' => 'The ID of the instance.
', 'CreateModelPackageInput$Domain' => 'The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
', 'CreateModelPackageInput$Task' => 'The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION"
| "OBJECT_DETECTION"
| "TEXT_GENERATION"
|"IMAGE_SEGMENTATION"
| "FILL_MASK"
| "CLASSIFICATION"
| "REGRESSION"
| "OTHER"
.
Specify "OTHER" if none of the tasks listed fit your use case.
', 'CustomizedMetricSpecification$MetricName' => 'The name of the customized metric.
', 'CustomizedMetricSpecification$Namespace' => 'The namespace of the customized metric.
', 'DescribeClusterResponse$FailureMessage' => 'The failure message of the SageMaker HyperPod cluster.
', 'DescribeEdgePackagingJobResponse$EdgePackagingJobStatusMessage' => 'Returns a message describing the job status and error messages.
', 'DescribeEdgePackagingJobResponse$ModelSignature' => 'The signature document of files in the model artifact.
', 'DescribeModelPackageOutput$Domain' => 'The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.
', 'DescribeModelPackageOutput$Task' => 'The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.
', 'DescribeModelPackageOutput$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).
', 'DeviceDeploymentSummary$DeviceDeploymentStatusMessage' => 'The detailed error message for the deployoment status result.
', 'EdgeDeploymentStatus$EdgeDeploymentStatusMessage' => 'A detailed message about deployment status in current stage.
', 'EdgeOutputConfig$PresetDeploymentConfig' => 'The configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are:
ComponentName
(optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job.
ComponentDescription
(optional) - Description of the component.
ComponentVersion
(optional) - The version of the component.
Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the semantic version specification.
PlatformOS
(optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.
PlatformArchitecture
(optional) - The processor architecture for the platform.
Supported architectures Windows include: Windows32_x86, Windows64_x64.
Supported architectures for Linux include: Linux x86_64, Linux ARMV8.
Returns a message describing the status of the deployed resource.
', 'EndpointInput$FeaturesAttribute' => 'The attributes of the input data that are the input features.
', 'EndpointInput$InferenceAttribute' => 'The attribute of the input data that represents the ground truth label.
', 'EndpointInput$ProbabilityAttribute' => 'In a classification problem, the attribute that represents the class probability.
', 'EndpointOutputConfiguration$EndpointName' => 'The name of the endpoint made during a recommendation job.
', 'EndpointOutputConfiguration$VariantName' => 'The name of the production variant (deployed model) made during a recommendation job.
', 'EnvironmentParameter$Key' => 'The environment key suggested by the Amazon SageMaker Inference Recommender.
', 'EnvironmentParameter$ValueType' => 'The value type suggested by the Amazon SageMaker Inference Recommender.
', 'EnvironmentParameter$Value' => 'The value suggested by the Amazon SageMaker Inference Recommender.
', 'GetScalingConfigurationRecommendationRequest$RecommendationId' => 'The recommendation ID of a previously completed inference recommendation. This ID should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName
field.
Specify either this field or the EndpointName
field.
The recommendation ID of a previously completed inference recommendation.
', 'IamIdentity$Arn' => 'The Amazon Resource Name (ARN) of the IAM identity.
', 'IamIdentity$PrincipalId' => 'The ID of the principal that assumes the IAM identity.
', 'IamIdentity$SourceIdentity' => 'The person or application which assumes the IAM identity.
', 'InferenceRecommendation$RecommendationId' => 'The recommendation ID which uniquely identifies each recommendation.
', 'ListProcessingJobsRequest$NameContains' => 'A string in the processing job name. This filter returns only processing jobs whose name contains the specified string.
', 'ModelCard$ModelId' => 'The unique name (ID) of the model.
', 'ModelCard$RiskRating' => 'The risk rating of the model. Different organizations might have different criteria for model card risk ratings. For more information, see Risk ratings.
', 'ModelCard$ModelPackageGroupName' => 'The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry.
', 'ModelDashboardModelCard$ModelId' => 'For models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.
', 'ModelDashboardModelCard$RiskRating' => 'A model card\'s risk rating. Can be low, medium, or high.
', 'ModelMetadataSummary$Domain' => 'The machine learning domain of the model.
', 'ModelMetadataSummary$Framework' => 'The machine learning framework of the model.
', 'ModelMetadataSummary$Task' => 'The machine learning task of the model.
', 'ModelMetadataSummary$Model' => 'The name of the model.
', 'ModelMetadataSummary$FrameworkVersion' => 'The framework version of the model.
', 'ModelPackage$Domain' => 'The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
', 'ModelPackage$Task' => 'The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
', 'ModelPackage$SamplePayloadUrl' => 'The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'ModelPackageContainerDefinition$Framework' => 'The machine learning framework of the model package container image.
', 'ModelPackageContainerDefinition$NearestModelName' => 'The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata
.
if the overall status is Failed
, the reason for the failure.
The metric type. You can only apply SageMaker metric types to SageMaker endpoints.
', 'ProcessingInput$InputName' => 'The name for the processing job input.
', 'ProcessingOutput$OutputName' => 'The name for the processing job output.
', 'ProductListings$member' => NULL, 'RStudioServerProDomainSettings$RStudioConnectUrl' => 'A URL pointing to an RStudio Connect server.
', 'RStudioServerProDomainSettings$RStudioPackageManagerUrl' => 'A URL pointing to an RStudio Package Manager server.
', 'RStudioServerProDomainSettingsForUpdate$RStudioConnectUrl' => 'A URL pointing to an RStudio Connect server.
', 'RStudioServerProDomainSettingsForUpdate$RStudioPackageManagerUrl' => 'A URL pointing to an RStudio Package Manager server.
', 'RealTimeInferenceRecommendation$RecommendationId' => 'The recommendation ID which uniquely identifies each recommendation.
', 'RecommendationJobContainerConfig$Domain' => 'The machine learning domain of the model and its components.
Valid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING
The machine learning task that the model accomplishes.
Valid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION | REGRESSION | OTHER
The machine learning framework of the container image.
Valid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN
The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
Valid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn | densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet
A Liquid template that renders the HTML for the worker UI.
', 'RenderingError$Code' => 'A unique identifier for a specific class of errors.
', 'RenderingError$Message' => 'A human-readable message describing the error.
', 'ScheduleConfig$DataAnalysisStartTime' => 'Sets the start time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression
parameter. Specify this offset in ISO 8601 duration format. For example, if you want to monitor the five hours of data in your dataset that precede the start of each monitoring job, you would specify: "-PT5H"
.
The start time that you specify must not precede the end time that you specify by more than 24 hours. You specify the end time with the DataAnalysisEndTime
parameter.
If you set ScheduleExpression
to NOW
, this parameter is required.
Sets the end time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression
parameter. Specify this offset in ISO 8601 duration format. For example, if you want to end the window one hour before the start of each monitoring job, you would specify: "-PT1H"
.
The end time that you specify must not follow the start time that you specify by more than 24 hours. You specify the start time with the DataAnalysisStartTime
parameter.
If you set ScheduleExpression
to NOW
, this parameter is required.
The name of the vendor in the Amazon Marketplace.
', 'SubscribedWorkteam$ListingId' => 'Marketplace product listing ID.
', 'UserContext$UserProfileArn' => 'The Amazon Resource Name (ARN) of the user\'s profile.
', 'UserContext$UserProfileName' => 'The name of the user\'s profile.
', 'UserContext$DomainId' => 'The domain associated with the user.
', 'Workforce$SubDomain' => 'The subdomain for your OIDC Identity Provider.
', 'Workteam$SubDomain' => 'The URI of the labeling job\'s user interface. Workers open this URI to start labeling your data objects.
', ], ], 'String1024' => [ 'base' => NULL, 'refs' => [ 'ClarifyCheckStepMetadata$BaselineUsedForDriftCheckConstraints' => 'The Amazon S3 URI of baseline constraints file to be used for the drift check.
', 'ClarifyCheckStepMetadata$CalculatedBaselineConstraints' => 'The Amazon S3 URI of the newly calculated baseline constraints file.
', 'ClarifyCheckStepMetadata$ViolationReport' => 'The Amazon S3 URI of the violation report if violations are detected.
', 'CreateDomainResponse$Url' => 'The URL to the created domain.
', 'DescribeDomainResponse$Url' => 'The domain\'s URL.
', 'DescribeSpaceResponse$Url' => 'Returns the URL of the space. If the space is created with Amazon Web Services IAM Identity Center (Successor to Amazon Web Services Single Sign-On) authentication, users can navigate to the URL after appending the respective redirect parameter for the application type to be federated through Amazon Web Services IAM Identity Center.
The following application types are supported:
Studio Classic: &redirect=JupyterServer
JupyterLab: &redirect=JupyterLab
Code Editor, based on Code-OSS, Visual Studio Code - Open Source: &redirect=CodeEditor
The domain\'s URL.
', 'EMRStepMetadata$LogFilePath' => 'The path to the log file where the cluster step\'s failure root cause is recorded.
', 'OutputParameter$Value' => 'The value of the output parameter.
', 'Parameter$Value' => 'The literal value for the parameter.
', 'QualityCheckStepMetadata$BaselineUsedForDriftCheckStatistics' => 'The Amazon S3 URI of the baseline statistics file used for the drift check.
', 'QualityCheckStepMetadata$BaselineUsedForDriftCheckConstraints' => 'The Amazon S3 URI of the baseline constraints file used for the drift check.
', 'QualityCheckStepMetadata$CalculatedBaselineStatistics' => 'The Amazon S3 URI of the newly calculated baseline statistics file.
', 'QualityCheckStepMetadata$CalculatedBaselineConstraints' => 'The Amazon S3 URI of the newly calculated baseline constraints file.
', 'QualityCheckStepMetadata$ViolationReport' => 'The Amazon S3 URI of violation report if violations are detected.
', ], ], 'String128' => [ 'base' => NULL, 'refs' => [ 'CategoricalParameterRangeValues$member' => NULL, ], ], 'String200' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$Description' => 'A description of the work team.
', 'SubscribedWorkteam$MarketplaceTitle' => 'The title of the service provided by the vendor in the Amazon Marketplace.
', 'SubscribedWorkteam$MarketplaceDescription' => 'The description of the vendor from the Amazon Marketplace.
', 'UpdateWorkteamRequest$Description' => 'An updated description for the work team.
', 'Workteam$Description' => 'A description of the work team.
', ], ], 'String256' => [ 'base' => NULL, 'refs' => [ 'ActionSource$SourceType' => 'The type of the source.
', 'ActionSource$SourceId' => 'The ID of the source.
', 'ArtifactSourceType$Value' => 'The ID.
', 'ArtifactSummary$ArtifactType' => 'The type of the artifact.
', 'AssociationSummary$SourceType' => 'The source type.
', 'AssociationSummary$DestinationType' => 'The destination type.
', 'CallbackStepMetadata$SqsQueueUrl' => 'The URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the callback step.
', 'ClarifyCheckStepMetadata$CheckType' => 'The type of the Clarify Check step
', 'ClarifyCheckStepMetadata$ModelPackageGroupName' => 'The model package group name.
', 'ClarifyCheckStepMetadata$CheckJobArn' => 'The Amazon Resource Name (ARN) of the check processing job that was run by this step\'s execution.
', 'ContextSource$SourceType' => 'The type of the source.
', 'ContextSource$SourceId' => 'The ID of the source.
', 'ContextSummary$ContextType' => 'The type of the context.
', 'CreateActionRequest$ActionType' => 'The action type.
', 'CreateArtifactRequest$ArtifactType' => 'The artifact type.
', 'CreateContextRequest$ContextType' => 'The context type.
', 'CreateUserProfileRequest$SingleSignOnUserValue' => 'The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain\'s AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain\'s AuthMode is not IAM Identity Center, this field cannot be specified.
', 'CustomImageContainerEnvironmentVariables$value' => NULL, 'DescribeActionResponse$ActionType' => 'The type of the action.
', 'DescribeArtifactResponse$ArtifactType' => 'The type of the artifact.
', 'DescribeContextResponse$ContextType' => 'The type of the context.
', 'DescribeDomainResponse$SingleSignOnManagedApplicationInstanceId' => 'The IAM Identity Center managed application instance ID.
', 'DescribeUserProfileResponse$SingleSignOnUserValue' => 'The IAM Identity Center user value.
', 'EMRStepMetadata$ClusterId' => 'The identifier of the EMR cluster.
', 'EMRStepMetadata$StepId' => 'The identifier of the EMR cluster step.
', 'EMRStepMetadata$StepName' => 'The name of the EMR cluster step.
', 'LambdaStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution.
', 'ListActionsRequest$ActionType' => 'A filter that returns only actions of the specified type.
', 'ListArtifactsRequest$ArtifactType' => 'A filter that returns only artifacts of the specified type.
', 'ListAssociationsRequest$SourceType' => 'A filter that returns only associations with the specified source type.
', 'ListAssociationsRequest$DestinationType' => 'A filter that returns only associations with the specified destination type.
', 'ListContextsRequest$ContextType' => 'A filter that returns only contexts of the specified type.
', 'ListTrialComponentsRequest$SourceArn' => 'A filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify SourceArn
, you can\'t filter by ExperimentName
or TrialName
.
The value to filter the model metadata.
', 'ModelStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the created model.
', 'OutputParameter$Name' => 'The name of the output parameter.
', 'QualityCheckStepMetadata$CheckType' => 'The type of the Quality check step.
', 'QualityCheckStepMetadata$ModelPackageGroupName' => 'The model package group name.
', 'QualityCheckStepMetadata$CheckJobArn' => 'The Amazon Resource Name (ARN) of the Quality check processing job that was run by this step execution.
', 'QueryProperties$key' => NULL, 'QueryProperties$value' => NULL, 'RegisterModelStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the model package.
', 'SelectedStep$StepName' => 'The name of the pipeline step.
', 'SendPipelineExecutionStepFailureRequest$FailureReason' => 'A message describing why the step failed.
', ], ], 'String3072' => [ 'base' => NULL, 'refs' => [ 'FailStepMetadata$ErrorMessage' => 'A message that you define and then is processed and rendered by the Fail step when the error occurs.
', 'PipelineExecutionSummary$PipelineExecutionFailureReason' => 'A message generated by SageMaker Pipelines describing why the pipeline execution failed.
', ], ], 'String40' => [ 'base' => NULL, 'refs' => [ 'QueryTypes$member' => NULL, 'Vertex$Type' => 'The type of the lineage entity resource. For example: DataSet
, Model
, Endpoint
, etc...
The type of the action.
', 'CategoricalParameter$Name' => 'The Name of the environment variable.
', 'ModelLatencyThreshold$Percentile' => 'The model latency percentile threshold. Acceptable values are P95
and P99
. For custom load tests, specify the value as P95
.
Limits the number of vertices in the request. Use the NextToken
in a response to to retrieve the next page of results.
Limits the number of vertices in the response. Use the NextToken
in a response to to retrieve the next page of results.
The string value of a categorical hyperparameter. If you specify a value for this parameter, you can\'t specify the NumberValue
parameter.
The App type that the Lifecycle Configuration is attached to.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigAppType' => 'The App type that the Lifecycle Configuration is attached to.
', 'ListStudioLifecycleConfigsRequest$AppTypeEquals' => 'A parameter to search for the App Type to which the Lifecycle Configuration is attached.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigAppType' => 'The App type to which the Lifecycle Configuration is attached.
', ], ], 'StudioLifecycleConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigResponse$StudioLifecycleConfigArn' => 'The ARN of your created Lifecycle Configuration.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigArn' => 'The ARN of the Lifecycle Configuration to describe.
', 'LifecycleConfigArns$member' => NULL, 'ResourceSpec$LifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the Lifecycle Configuration.
', ], ], 'StudioLifecycleConfigContent' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigRequest$StudioLifecycleConfigContent' => 'The content of your Amazon SageMaker Studio Lifecycle Configuration script. This content must be base64 encoded.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigContent' => 'The content of your Amazon SageMaker Studio Lifecycle Configuration script.
', ], ], 'StudioLifecycleConfigDetails' => [ 'base' => 'Details of the Amazon SageMaker Studio Lifecycle Configuration.
', 'refs' => [ 'StudioLifecycleConfigsList$member' => NULL, ], ], 'StudioLifecycleConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration to create.
', 'DeleteStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration to delete.
', 'DescribeStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration to describe.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration that is described.
', 'ListStudioLifecycleConfigsRequest$NameContains' => 'A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigName' => 'The name of the Amazon SageMaker Studio Lifecycle Configuration.
', ], ], 'StudioLifecycleConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListStudioLifecycleConfigsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime.
', ], ], 'StudioLifecycleConfigsList' => [ 'base' => NULL, 'refs' => [ 'ListStudioLifecycleConfigsResponse$StudioLifecycleConfigs' => 'A list of Lifecycle Configurations and their properties.
', ], ], 'StudioWebPortal' => [ 'base' => NULL, 'refs' => [ 'UserSettings$StudioWebPortal' => 'Whether the user can access Studio. If this value is set to DISABLED
, the user cannot access Studio, even if that is the default experience for the domain.
The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
', 'DescribeNotebookInstanceOutput$SubnetId' => 'The ID of the VPC subnet.
', 'Subnets$member' => NULL, ], ], 'Subnets' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$SubnetIds' => 'The VPC subnets that the domain uses for communication.
', 'DescribeDomainResponse$SubnetIds' => 'The VPC subnets that the domain uses for communication.
', 'UpdateDomainRequest$SubnetIds' => 'The VPC subnets that Studio uses for communication.
If removing subnets, ensure there are no apps in the InService
, Pending
, or Deleting
state.
The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.
', ], ], 'SubscribedWorkteam' => [ 'base' => 'Describes a work team of a vendor that does the a labelling job.
', 'refs' => [ 'DescribeSubscribedWorkteamResponse$SubscribedWorkteam' => 'A Workteam
instance that contains information about the work team.
An array of Workteam
objects, each describing a work team.
Returns true
if the work team was successfully deleted; otherwise, returns false
.
Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
', 'refs' => [ 'GetSearchSuggestionsRequest$SuggestionQuery' => 'Limits the property names that are included in the response.
', ], ], 'TableFormat' => [ 'base' => NULL, 'refs' => [ 'OfflineStoreConfig$TableFormat' => 'Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
', ], ], 'TableName' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$TableName' => 'The name of the Glue table.
', ], ], 'TabularJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the tabular problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TabularJobConfig' => 'Settings used to configure an AutoML job V2 for the tabular problem type (regression, classification).
', ], ], 'TabularResolvedAttributes' => [ 'base' => 'The resolved attributes specific to the tabular problem type.
', 'refs' => [ 'AutoMLProblemTypeResolvedAttributes$TabularResolvedAttributes' => 'The resolved attributes for the tabular problem type.
', ], ], 'Tag' => [ 'base' => 'A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
', 'refs' => [ 'TagList$member' => NULL, ], ], 'TagKey' => [ 'base' => NULL, 'refs' => [ 'Tag$Key' => 'The tag key. Tag keys must be unique per resource.
', 'TagKeyList$member' => NULL, ], ], 'TagKeyList' => [ 'base' => NULL, 'refs' => [ 'DeleteTagsInput$TagKeys' => 'An array or one or more tag keys to delete.
', ], ], 'TagList' => [ 'base' => NULL, 'refs' => [ 'AddTagsInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'AddTagsOutput$Tags' => 'A list of tags associated with the SageMaker resource.
', 'CreateActionRequest$Tags' => 'A list of tags to apply to the action.
', 'CreateAlgorithmInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateAppImageConfigRequest$Tags' => 'A list of tags to apply to the AppImageConfig.
', 'CreateAppRequest$Tags' => 'Each tag consists of a key and an optional value. Tag keys must be unique per resource.
', 'CreateArtifactRequest$Tags' => 'A list of tags to apply to the artifact.
', 'CreateAutoMLJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
', 'CreateAutoMLJobV2Request$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
', 'CreateClusterRequest$Tags' => 'Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can add tags to your cluster in the same way you add them in other Amazon Web Services services that support tagging. To learn more about tagging Amazon Web Services resources in general, see Tagging Amazon Web Services Resources User Guide.
', 'CreateCodeRepositoryInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateCompilationJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateContextRequest$Tags' => 'A list of tags to apply to the context.
', 'CreateDataQualityJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateDeviceFleetRequest$Tags' => 'Creates tags for the specified fleet.
', 'CreateDomainRequest$Tags' => 'Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search
API.
Tags that you specify for the Domain are also added to all Apps that the Domain launches.
', 'CreateEdgeDeploymentPlanRequest$Tags' => 'List of tags with which to tag the edge deployment plan.
', 'CreateEdgePackagingJobRequest$Tags' => 'Creates tags for the packaging job.
', 'CreateEndpointConfigInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateEndpointInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateExperimentRequest$Tags' => 'A list of tags to associate with the experiment. You can use Search API to search on the tags.
', 'CreateFeatureGroupRequest$Tags' => 'Tags used to identify Features
in each FeatureGroup
.
An array of key-value pairs that contain metadata to help you categorize and organize a flow definition. Each tag consists of a key and a value, both of which you define.
', 'CreateHubRequest$Tags' => 'Any tags to associate with the hub.
', 'CreateHumanTaskUiRequest$Tags' => 'An array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define.
', 'CreateHyperParameterTuningJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
', 'CreateImageRequest$Tags' => 'A list of tags to apply to the image.
', 'CreateInferenceComponentInput$Tags' => 'A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference.
', 'CreateInferenceExperimentRequest$Tags' => 'Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
', 'CreateInferenceRecommendationsJobRequest$Tags' => 'The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.
', 'CreateLabelingJobRequest$Tags' => 'An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelBiasJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelCardRequest$Tags' => 'Key-value pairs used to manage metadata for model cards.
', 'CreateModelExplainabilityJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateModelPackageGroupInput$Tags' => 'A list of key value pairs associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'CreateModelPackageInput$Tags' => 'A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply ModelPackageGroupName
, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply a tag
argument.
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateMonitoringScheduleRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateNotebookInstanceInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreatePipelineRequest$Tags' => 'A list of tags to apply to the created pipeline.
', 'CreateProcessingJobRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateProjectInput$Tags' => 'An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'CreateSpaceRequest$Tags' => 'Tags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search
API.
Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
', 'CreateTrainingJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateTransformJobRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateTrialComponentRequest$Tags' => 'A list of tags to associate with the component. You can use Search API to search on the tags.
', 'CreateTrialRequest$Tags' => 'A list of tags to associate with the trial. You can use Search API to search on the tags.
', 'CreateUserProfileRequest$Tags' => 'Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.
', 'CreateWorkforceRequest$Tags' => 'An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.
', 'CreateWorkteamRequest$Tags' => 'An array of key-value pairs.
For more information, see Resource Tag and Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'DescribeLabelingJobResponse$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'Endpoint$Tags' => 'A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'Experiment$Tags' => 'The list of tags that are associated with the experiment. You can use Search API to search on the tags.
', 'FeatureGroup$Tags' => 'Tags used to define a FeatureGroup
.
The tags associated with a hyperparameter tuning job. For more information see Tagging Amazon Web Services resources.
', 'ImportHubContentRequest$Tags' => 'Any tags associated with the hub content.
', 'ListTagsOutput$Tags' => 'An array of Tag
objects, each with a tag key and a value.
A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'ModelCard$Tags' => 'Key-value pairs used to manage metadata for the model card.
', 'ModelDashboardModelCard$Tags' => 'The tags associated with a model card.
', 'ModelPackage$Tags' => 'A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'ModelPackageGroup$Tags' => 'A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'MonitoringSchedule$Tags' => 'A list of the tags associated with the monitoring schedlue. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'Pipeline$Tags' => 'A list of tags that apply to the pipeline.
', 'ProcessingJob$Tags' => 'An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'Project$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'RegisterDevicesRequest$Tags' => 'The tags associated with devices.
', 'TrainingJob$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'TransformJob$Tags' => 'A list of tags associated with the transform job.
', 'Trial$Tags' => 'The list of tags that are associated with the trial. You can use Search API to search on the tags.
', 'TrialComponent$Tags' => 'The list of tags that are associated with the component. You can use Search API to search on the tags.
', 'UpdateProjectInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see Amazon Web Services Service Catalog Tag Update Constraints.
', ], ], 'TagValue' => [ 'base' => NULL, 'refs' => [ 'Tag$Value' => 'The tag value.
', ], ], 'TargetAttributeName' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$TargetAttributeName' => 'The name of the target variable in supervised learning, usually represented by \'y\'.
', 'TabularJobConfig$TargetAttributeName' => 'The name of the target variable in supervised learning, usually represented by \'y\'.
', 'TimeSeriesConfig$TargetAttributeName' => 'The name of the column representing the target variable that you want to predict for each item in your dataset. The data type of the target variable must be numerical.
', ], ], 'TargetDevice' => [ 'base' => NULL, 'refs' => [ 'CompilationJobSummary$CompilationTargetDevice' => 'The type of device that the model will run on after the compilation job has completed.
', 'OutputConfig$TargetDevice' => 'Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform
.
Currently ml_trn1
is available only in US East (N. Virginia) Region, and ml_inf2
is available only in US East (Ohio) Region.
The name of the column used to provide the class labels. It should not be same as the content column.
', ], ], 'TargetObjectiveMetricValue' => [ 'base' => NULL, 'refs' => [ 'TuningJobCompletionCriteria$TargetObjectiveMetricValue' => 'The value of the objective metric.
', ], ], 'TargetPlatform' => [ 'base' => 'Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice
.
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice
.
The following examples show how to configure the TargetPlatform
and CompilerOptions
JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"},
"CompilerOptions": {\'mattr\': [\'+neon\']}
Jetson TX2
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"},
"CompilerOptions": {\'gpu-code\': \'sm_62\', \'trt-ver\': \'6.0.1\', \'cuda-ver\': \'10.0\'}
EC2 m5.2xlarge instance OS
"TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"},
"CompilerOptions": {\'mcpu\': \'skylake-avx512\'}
RK3399
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}
ARMv7 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},
"CompilerOptions": {\'ANDROID_PLATFORM\': 25, \'mattr\': [\'+neon\']}
ARMv8 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"},
"CompilerOptions": {\'ANDROID_PLATFORM\': 29}
The type of accelerator that the model will run on after the compilation job has completed.
', 'TargetPlatform$Accelerator' => 'Specifies a target platform accelerator (optional).
NVIDIA
: Nvidia graphics processing unit. It also requires gpu-code
, trt-ver
, cuda-ver
compiler options
MALI
: ARM Mali graphics processor
INTEL_GRAPHICS
: Integrated Intel graphics
The type of architecture that the model will run on after the compilation job has completed.
', 'TargetPlatform$Arch' => 'Specifies a target platform architecture.
X86_64
: 64-bit version of the x86 instruction set.
X86
: 32-bit version of the x86 instruction set.
ARM64
: ARMv8 64-bit CPU.
ARM_EABIHF
: ARMv7 32-bit, Hard Float.
ARM_EABI
: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.
The type of OS that the model will run on after the compilation job has completed.
', 'TargetPlatform$Os' => 'Specifies a target platform OS.
LINUX
: Linux-based operating systems.
ANDROID
: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM
compiler option. For example, "CompilerOptions": {\'ANDROID_PLATFORM\': 28}
A target tracking scaling policy. Includes support for predefined or customized metrics.
When using the PutScalingPolicy API, this parameter is required when you are creating a policy with the policy type TargetTrackingScaling
.
A target tracking scaling policy. Includes support for predefined or customized metrics.
', ], ], 'TaskAvailabilityLifetimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$TaskAvailabilityLifetimeInSeconds' => 'The length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.
If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).
If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
The variant\'s capacity.
', 'PendingProductionVariantSummary$CurrentInstanceCount' => 'The number of instances associated with the variant.
', 'PendingProductionVariantSummary$DesiredInstanceCount' => 'The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
', 'ProductionVariantSummary$CurrentInstanceCount' => 'The number of instances associated with the variant.
', 'ProductionVariantSummary$DesiredInstanceCount' => 'The number of instances requested in the UpdateEndpointWeightsAndCapacities
request.
The number of instances of the type specified by InstanceType
.
A description of the task for your human workers.
', ], ], 'TaskInput' => [ 'base' => NULL, 'refs' => [ 'RenderableTask$Input' => 'A JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable task.input
. For example, if you define a variable task.input.text
in your template, you can supply the variable in the JSON object as "text": "sample text"
.
Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.
', ], ], 'TaskTimeLimitInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$TaskTimeLimitInSeconds' => 'The amount of time that a worker has to complete a task.
If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).
If you create a labeling job using a built-in task type the maximum for this parameter depends on the task type you use:
For image and text labeling jobs, the maximum is 8 hours (28,800 seconds).
For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
A title for the task for your human workers.
', ], ], 'TemplateContent' => [ 'base' => NULL, 'refs' => [ 'UiTemplate$Content' => 'The content of the Liquid template for the worker user interface.
', ], ], 'TemplateContentSha256' => [ 'base' => NULL, 'refs' => [ 'UiTemplateInfo$ContentSha256' => 'The SHA-256 digest of the contents of the template.
', ], ], 'TemplateUrl' => [ 'base' => NULL, 'refs' => [ 'UiTemplateInfo$Url' => 'The URL for the user interface template.
', ], ], 'TensorBoardAppSettings' => [ 'base' => 'The TensorBoard app settings.
', 'refs' => [ 'UserSettings$TensorBoardAppSettings' => 'The TensorBoard app settings.
', ], ], 'TensorBoardOutputConfig' => [ 'base' => 'Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.
', 'refs' => [ 'CreateTrainingJobRequest$TensorBoardOutputConfig' => NULL, 'DescribeTrainingJobResponse$TensorBoardOutputConfig' => NULL, 'TrainingJob$TensorBoardOutputConfig' => NULL, ], ], 'TenthFractionsOfACent' => [ 'base' => NULL, 'refs' => [ 'USD$TenthFractionsOfACent' => 'Fractions of a cent, in tenths.
', ], ], 'TerminationWaitInSeconds' => [ 'base' => NULL, 'refs' => [ 'BlueGreenUpdatePolicy$TerminationWaitInSeconds' => 'Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0.
', ], ], 'TextClassificationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the text classification problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TextClassificationJobConfig' => 'Settings used to configure an AutoML job V2 for the text classification problem type.
', ], ], 'TextGenerationHyperParameterKey' => [ 'base' => NULL, 'refs' => [ 'TextGenerationHyperParameters$key' => NULL, ], ], 'TextGenerationHyperParameterValue' => [ 'base' => NULL, 'refs' => [ 'TextGenerationHyperParameters$value' => NULL, ], ], 'TextGenerationHyperParameters' => [ 'base' => NULL, 'refs' => [ 'TextGenerationJobConfig$TextGenerationHyperParameters' => 'The hyperparameters used to configure and optimize the learning process of the base model. You can set any combination of the following hyperparameters for all base models. For more information on each supported hyperparameter, see Optimize the learning process of your text generation models with hyperparameters.
"epochCount"
: The number of times the model goes through the entire training dataset. Its value should be a string containing an integer value within the range of "1" to "10".
"batchSize"
: The number of data samples used in each iteration of training. Its value should be a string containing an integer value within the range of "1" to "64".
"learningRate"
: The step size at which a model\'s parameters are updated during training. Its value should be a string containing a floating-point value within the range of "0" to "1".
"learningRateWarmupSteps"
: The number of training steps during which the learning rate gradually increases before reaching its target or maximum value. Its value should be a string containing an integer value within the range of "0" to "250".
Here is an example where all four hyperparameters are configured.
{ "epochCount":"5", "learningRate":"0.5", "batchSize": "32", "learningRateWarmupSteps": "10" }
The collection of settings used by an AutoML job V2 for the text generation problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
Settings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning) problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
The resolved attributes specific to the text generation problem type.
', 'refs' => [ 'AutoMLProblemTypeResolvedAttributes$TextGenerationResolvedAttributes' => 'The resolved attributes for the text generation problem type.
', ], ], 'ThingName' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$IotThingName' => 'The Amazon Web Services Internet of Things (IoT) object thing name associated with the device.
', 'Device$IotThingName' => 'Amazon Web Services Internet of Things (IoT) object name.
', 'DeviceSummary$IotThingName' => 'The Amazon Web Services Internet of Things (IoT) object thing name associated with the device..
', ], ], 'ThroughputConfig' => [ 'base' => 'Used to set feature group throughput configuration. There are two modes: ON_DEMAND
and PROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use the Standard
tier online store.
Active throughput configuration of the feature group. There are two modes: ON_DEMAND
and PROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use the Standard
tier online store.
The new throughput configuration for the feature group. You can switch between on-demand and provisioned modes or update the read / write capacity of provisioned feature groups. You can switch a feature group to on-demand only once in a 24 hour period.
', 'refs' => [ 'UpdateFeatureGroupRequest$ThroughputConfig' => NULL, ], ], 'ThroughputMode' => [ 'base' => NULL, 'refs' => [ 'ThroughputConfig$ThroughputMode' => 'The mode used for your feature group throughput: ON_DEMAND
or PROVISIONED
.
The mode used for your feature group throughput: ON_DEMAND
or PROVISIONED
.
Target throughput mode of the feature group. Throughput update is an asynchronous operation, and the outcome should be monitored by polling LastUpdateStatus
field in DescribeFeatureGroup
response. You cannot update a feature group\'s throughput while another update is in progress.
The collection of components that defines the time-series.
', 'refs' => [ 'TimeSeriesForecastingJobConfig$TimeSeriesConfig' => 'The collection of components that defines the time-series.
', ], ], 'TimeSeriesForecastingJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TimeSeriesForecastingJobConfig' => 'Settings used to configure an AutoML job V2 for the time-series forecasting problem type.
', ], ], 'TimeSeriesForecastingSettings' => [ 'base' => 'Time series forecast settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$TimeSeriesForecastingSettings' => 'Time series forecast settings for the SageMaker Canvas application.
', ], ], 'TimeSeriesTransformations' => [ 'base' => 'Transformations allowed on the dataset. Supported transformations are Filling
and Aggregation
. Filling
specifies how to add values to missing values in the dataset. Aggregation
defines how to aggregate data that does not align with forecast frequency.
The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
', ], ], 'Timestamp' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$CreationTime' => 'When the action was created.
', 'ActionSummary$LastModifiedTime' => 'When the action was last modified.
', 'AppImageConfigDetails$CreationTime' => 'When the AppImageConfig was created.
', 'AppImageConfigDetails$LastModifiedTime' => 'When the AppImageConfig was last modified.
', 'ArtifactSummary$CreationTime' => 'When the artifact was created.
', 'ArtifactSummary$LastModifiedTime' => 'When the artifact was last modified.
', 'AssociationSummary$CreationTime' => 'When the association was created.
', 'AutoMLCandidate$CreationTime' => 'The creation time.
', 'AutoMLCandidate$EndTime' => 'The end time.
', 'AutoMLCandidate$LastModifiedTime' => 'The last modified time.
', 'AutoMLJobSummary$CreationTime' => 'When the AutoML job was created.
', 'AutoMLJobSummary$EndTime' => 'The end time of an AutoML job.
', 'AutoMLJobSummary$LastModifiedTime' => 'When the AutoML job was last modified.
', 'ClusterNodeDetails$LaunchTime' => 'The time when the instance is launched.
', 'ClusterNodeSummary$LaunchTime' => 'The time when the instance is launched.
', 'ClusterSummary$CreationTime' => 'The time when the SageMaker HyperPod cluster is created.
', 'CompilationJobSummary$CompilationStartTime' => 'The time when the model compilation job started.
', 'CompilationJobSummary$CompilationEndTime' => 'The time when the model compilation job completed.
', 'ContextSummary$CreationTime' => 'When the context was created.
', 'ContextSummary$LastModifiedTime' => 'When the context was last modified.
', 'CreateTrialComponentRequest$StartTime' => 'When the component started.
', 'CreateTrialComponentRequest$EndTime' => 'When the component ended.
', 'DebugRuleEvaluationStatus$LastModifiedTime' => 'Timestamp when the rule evaluation status was last modified.
', 'DeployedImage$ResolutionTime' => 'The date and time when the image path for the model resolved to the ResolvedImage
When the action was created.
', 'DescribeActionResponse$LastModifiedTime' => 'When the action was last modified.
', 'DescribeAppImageConfigResponse$CreationTime' => 'When the AppImageConfig was created.
', 'DescribeAppImageConfigResponse$LastModifiedTime' => 'When the AppImageConfig was last modified.
', 'DescribeAppResponse$LastHealthCheckTimestamp' => 'The timestamp of the last health check.
', 'DescribeAppResponse$LastUserActivityTimestamp' => 'The timestamp of the last user\'s activity. LastUserActivityTimestamp
is also updated when SageMaker performs health checks without user activity. As a result, this value is set to the same value as LastHealthCheckTimestamp
.
The creation time.
', 'DescribeArtifactResponse$CreationTime' => 'When the artifact was created.
', 'DescribeArtifactResponse$LastModifiedTime' => 'When the artifact was last modified.
', 'DescribeAutoMLJobResponse$CreationTime' => 'Returns the creation time of the AutoML job.
', 'DescribeAutoMLJobResponse$EndTime' => 'Returns the end time of the AutoML job.
', 'DescribeAutoMLJobResponse$LastModifiedTime' => 'Returns the job\'s last modified time.
', 'DescribeAutoMLJobV2Response$CreationTime' => 'Returns the creation time of the AutoML job V2.
', 'DescribeAutoMLJobV2Response$EndTime' => 'Returns the end time of the AutoML job V2.
', 'DescribeAutoMLJobV2Response$LastModifiedTime' => 'Returns the job\'s last modified time.
', 'DescribeClusterResponse$CreationTime' => 'The time when the SageMaker Cluster is created.
', 'DescribeCompilationJobResponse$CompilationStartTime' => 'The time when the model compilation job started the CompilationJob
instances.
You are billed for the time between this timestamp and the timestamp in the CompilationEndTime
field. In Amazon CloudWatch Logs, the start time might be later than this time. That\'s because it takes time to download the compilation job, which depends on the size of the compilation job container.
The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job\'s model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker detected that the job failed.
', 'DescribeContextResponse$CreationTime' => 'When the context was created.
', 'DescribeContextResponse$LastModifiedTime' => 'When the context was last modified.
', 'DescribeDataQualityJobDefinitionResponse$CreationTime' => 'The time that the data quality monitoring job definition was created.
', 'DescribeDeviceFleetResponse$CreationTime' => 'Timestamp of when the device fleet was created.
', 'DescribeDeviceFleetResponse$LastModifiedTime' => 'Timestamp of when the device fleet was last updated.
', 'DescribeDeviceResponse$RegistrationTime' => 'The timestamp of the last registration or de-reregistration.
', 'DescribeDeviceResponse$LatestHeartbeat' => 'The last heartbeat received from the device.
', 'DescribeEdgeDeploymentPlanResponse$CreationTime' => 'The time when the edge deployment plan was created.
', 'DescribeEdgeDeploymentPlanResponse$LastModifiedTime' => 'The time when the edge deployment plan was last updated.
', 'DescribeEdgePackagingJobResponse$CreationTime' => 'The timestamp of when the packaging job was created.
', 'DescribeEdgePackagingJobResponse$LastModifiedTime' => 'The timestamp of when the job was last updated.
', 'DescribeEndpointConfigOutput$CreationTime' => 'A timestamp that shows when the endpoint configuration was created.
', 'DescribeEndpointOutput$CreationTime' => 'A timestamp that shows when the endpoint was created.
', 'DescribeEndpointOutput$LastModifiedTime' => 'A timestamp that shows when the endpoint was last modified.
', 'DescribeExperimentResponse$CreationTime' => 'When the experiment was created.
', 'DescribeExperimentResponse$LastModifiedTime' => 'When the experiment was last modified.
', 'DescribeFlowDefinitionResponse$CreationTime' => 'The timestamp when the flow definition was created.
', 'DescribeHubContentResponse$CreationTime' => 'The date and time that hub content was created.
', 'DescribeHubResponse$CreationTime' => 'The date and time that the hub was created.
', 'DescribeHubResponse$LastModifiedTime' => 'The date and time that the hub was last modified.
', 'DescribeHumanTaskUiResponse$CreationTime' => 'The timestamp when the human task user interface was created.
', 'DescribeHyperParameterTuningJobResponse$CreationTime' => 'The date and time that the tuning job started.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningEndTime' => 'The date and time that the tuning job ended.
', 'DescribeHyperParameterTuningJobResponse$LastModifiedTime' => 'The date and time that the status of the tuning job was modified.
', 'DescribeImageResponse$CreationTime' => 'When the image was created.
', 'DescribeImageResponse$LastModifiedTime' => 'When the image was last modified.
', 'DescribeImageVersionResponse$CreationTime' => 'When the version was created.
', 'DescribeImageVersionResponse$LastModifiedTime' => 'When the version was last modified.
', 'DescribeInferenceComponentOutput$CreationTime' => 'The time when the inference component was created.
', 'DescribeInferenceComponentOutput$LastModifiedTime' => 'The time when the inference component was last updated.
', 'DescribeInferenceExperimentResponse$CreationTime' => 'The timestamp at which you created the inference experiment.
', 'DescribeInferenceExperimentResponse$CompletionTime' => 'The timestamp at which the inference experiment was completed.
', 'DescribeInferenceExperimentResponse$LastModifiedTime' => 'The timestamp at which you last modified the inference experiment.
', 'DescribeInferenceRecommendationsJobResponse$CompletionTime' => 'A timestamp that shows when the job completed.
', 'DescribeLabelingJobResponse$CreationTime' => 'The date and time that the labeling job was created.
', 'DescribeLabelingJobResponse$LastModifiedTime' => 'The date and time that the labeling job was last updated.
', 'DescribeLineageGroupResponse$CreationTime' => 'The creation time of lineage group.
', 'DescribeLineageGroupResponse$LastModifiedTime' => 'The last modified time of the lineage group.
', 'DescribeModelBiasJobDefinitionResponse$CreationTime' => 'The time at which the model bias job was created.
', 'DescribeModelCardExportJobResponse$CreatedAt' => 'The date and time that the model export job was created.
', 'DescribeModelCardExportJobResponse$LastModifiedAt' => 'The date and time that the model export job was last modified.
', 'DescribeModelCardResponse$CreationTime' => 'The date and time the model card was created.
', 'DescribeModelCardResponse$LastModifiedTime' => 'The date and time the model card was last modified.
', 'DescribeModelExplainabilityJobDefinitionResponse$CreationTime' => 'The time at which the model explainability job was created.
', 'DescribeModelOutput$CreationTime' => 'A timestamp that shows when the model was created.
', 'DescribeModelPackageOutput$LastModifiedTime' => 'The last time that the model package was modified.
', 'DescribeModelQualityJobDefinitionResponse$CreationTime' => 'The time at which the model quality job was created.
', 'DescribeMonitoringScheduleResponse$CreationTime' => 'The time at which the monitoring job was created.
', 'DescribeMonitoringScheduleResponse$LastModifiedTime' => 'The time at which the monitoring job was last modified.
', 'DescribePipelineDefinitionForExecutionResponse$CreationTime' => 'The time when the pipeline was created.
', 'DescribePipelineExecutionResponse$CreationTime' => 'The time when the pipeline execution was created.
', 'DescribePipelineExecutionResponse$LastModifiedTime' => 'The time when the pipeline execution was modified last.
', 'DescribePipelineResponse$CreationTime' => 'The time when the pipeline was created.
', 'DescribePipelineResponse$LastModifiedTime' => 'The time when the pipeline was last modified.
', 'DescribePipelineResponse$LastRunTime' => 'The time when the pipeline was last run.
', 'DescribeProcessingJobResponse$ProcessingEndTime' => 'The time at which the processing job completed.
', 'DescribeProcessingJobResponse$ProcessingStartTime' => 'The time at which the processing job started.
', 'DescribeProcessingJobResponse$LastModifiedTime' => 'The time at which the processing job was last modified.
', 'DescribeProcessingJobResponse$CreationTime' => 'The time at which the processing job was created.
', 'DescribeProjectOutput$CreationTime' => 'The time when the project was created.
', 'DescribeProjectOutput$LastModifiedTime' => 'The timestamp when project was last modified.
', 'DescribeStudioLifecycleConfigResponse$CreationTime' => 'The creation time of the Amazon SageMaker Studio Lifecycle Configuration.
', 'DescribeStudioLifecycleConfigResponse$LastModifiedTime' => 'This value is equivalent to CreationTime because Amazon SageMaker Studio Lifecycle Configurations are immutable.
', 'DescribeTrainingJobResponse$CreationTime' => 'A timestamp that indicates when the training job was created.
', 'DescribeTrainingJobResponse$TrainingStartTime' => 'Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime
. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last modified.
', 'DescribeTransformJobResponse$CreationTime' => 'A timestamp that shows when the transform Job was created.
', 'DescribeTransformJobResponse$TransformStartTime' => 'Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime
.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime
.
When the component started.
', 'DescribeTrialComponentResponse$EndTime' => 'When the component ended.
', 'DescribeTrialComponentResponse$CreationTime' => 'When the component was created.
', 'DescribeTrialComponentResponse$LastModifiedTime' => 'When the component was last modified.
', 'DescribeTrialResponse$CreationTime' => 'When the trial was created.
', 'DescribeTrialResponse$LastModifiedTime' => 'When the trial was last modified.
', 'DeviceDeploymentSummary$DeploymentStartTime' => 'The time when the deployment on the device started.
', 'DeviceFleetSummary$CreationTime' => 'Timestamp of when the device fleet was created.
', 'DeviceFleetSummary$LastModifiedTime' => 'Timestamp of when the device fleet was last updated.
', 'DeviceSummary$RegistrationTime' => 'The timestamp of the last registration or de-reregistration.
', 'DeviceSummary$LatestHeartbeat' => 'The last heartbeat received from the device.
', 'EdgeDeploymentPlanSummary$CreationTime' => 'The time when the edge deployment plan was created.
', 'EdgeDeploymentPlanSummary$LastModifiedTime' => 'The time when the edge deployment plan was last updated.
', 'EdgeDeploymentStatus$EdgeDeploymentStageStartTime' => 'The time when the deployment API started.
', 'EdgeModel$LatestSampleTime' => 'The timestamp of the last data sample taken.
', 'EdgeModel$LatestInference' => 'The timestamp of the last inference that was made.
', 'EdgePackagingJobSummary$CreationTime' => 'The timestamp of when the job was created.
', 'EdgePackagingJobSummary$LastModifiedTime' => 'The timestamp of when the edge packaging job was last updated.
', 'Endpoint$CreationTime' => 'The time that the endpoint was created.
', 'Endpoint$LastModifiedTime' => 'The last time the endpoint was modified.
', 'EndpointConfigSummary$CreationTime' => 'A timestamp that shows when the endpoint configuration was created.
', 'EndpointSummary$CreationTime' => 'A timestamp that shows when the endpoint was created.
', 'EndpointSummary$LastModifiedTime' => 'A timestamp that shows when the endpoint was last modified.
', 'Experiment$CreationTime' => 'When the experiment was created.
', 'Experiment$LastModifiedTime' => 'When the experiment was last modified.
', 'ExperimentSummary$CreationTime' => 'When the experiment was created.
', 'ExperimentSummary$LastModifiedTime' => 'When the experiment was last modified.
', 'FeatureGroupSummary$CreationTime' => 'A timestamp indicating the time of creation time of the FeatureGroup
.
The timestamp when SageMaker created the flow definition.
', 'GetDeviceFleetReportResponse$ReportGenerated' => 'Timestamp of when the report was generated.
', 'HubContentInfo$CreationTime' => 'The date and time that the hub content was created.
', 'HubInfo$CreationTime' => 'The date and time that the hub was created.
', 'HubInfo$LastModifiedTime' => 'The date and time that the hub was last modified.
', 'HumanTaskUiSummary$CreationTime' => 'A timestamp when SageMaker created the human task user interface.
', 'HyperParameterTrainingJobSummary$CreationTime' => 'The date and time that the training job was created.
', 'HyperParameterTrainingJobSummary$TrainingStartTime' => 'The date and time that the training job started.
', 'HyperParameterTrainingJobSummary$TrainingEndTime' => 'Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
The time in timestamp format that AMT detected model convergence, as defined by a lack of significant improvement over time based on criteria developed over a wide range of diverse benchmarking tests.
', 'HyperParameterTuningJobSearchEntity$CreationTime' => 'The time that a hyperparameter tuning job was created.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningEndTime' => 'The time that a hyperparameter tuning job ended.
', 'HyperParameterTuningJobSearchEntity$LastModifiedTime' => 'The time that a hyperparameter tuning job was last modified.
', 'HyperParameterTuningJobSummary$CreationTime' => 'The date and time that the tuning job was created.
', 'HyperParameterTuningJobSummary$HyperParameterTuningEndTime' => 'The date and time that the tuning job ended.
', 'HyperParameterTuningJobSummary$LastModifiedTime' => 'The date and time that the tuning job was modified.
', 'Image$CreationTime' => 'When the image was created.
', 'Image$LastModifiedTime' => 'When the image was last modified.
', 'ImageVersion$CreationTime' => 'When the version was created.
', 'ImageVersion$LastModifiedTime' => 'When the version was last modified.
', 'InferenceComponentSummary$CreationTime' => 'The time when the inference component was created.
', 'InferenceComponentSummary$LastModifiedTime' => 'The time when the inference component was last updated.
', 'InferenceExperimentSchedule$StartTime' => 'The timestamp at which the inference experiment started or will start.
', 'InferenceExperimentSchedule$EndTime' => 'The timestamp at which the inference experiment ended or will end.
', 'InferenceExperimentSummary$CreationTime' => 'The timestamp at which the inference experiment was created.
', 'InferenceExperimentSummary$CompletionTime' => 'The timestamp at which the inference experiment was completed.
', 'InferenceExperimentSummary$LastModifiedTime' => 'The timestamp when you last modified the inference experiment.
', 'InferenceRecommendationsJob$CompletionTime' => 'A timestamp that shows when the job completed.
', 'LabelingJobForWorkteamSummary$CreationTime' => 'The date and time that the labeling job was created.
', 'LabelingJobSummary$CreationTime' => 'The date and time that the job was created (timestamp).
', 'LabelingJobSummary$LastModifiedTime' => 'The date and time that the job was last modified (timestamp).
', 'LineageGroupSummary$CreationTime' => 'The creation time of the lineage group summary.
', 'LineageGroupSummary$LastModifiedTime' => 'The last modified time of the lineage group summary.
', 'ListActionsRequest$CreatedAfter' => 'A filter that returns only actions created on or after the specified time.
', 'ListActionsRequest$CreatedBefore' => 'A filter that returns only actions created on or before the specified time.
', 'ListAppImageConfigsRequest$CreationTimeBefore' => 'A filter that returns only AppImageConfigs created on or before the specified time.
', 'ListAppImageConfigsRequest$CreationTimeAfter' => 'A filter that returns only AppImageConfigs created on or after the specified time.
', 'ListAppImageConfigsRequest$ModifiedTimeBefore' => 'A filter that returns only AppImageConfigs modified on or before the specified time.
', 'ListAppImageConfigsRequest$ModifiedTimeAfter' => 'A filter that returns only AppImageConfigs modified on or after the specified time.
', 'ListArtifactsRequest$CreatedAfter' => 'A filter that returns only artifacts created on or after the specified time.
', 'ListArtifactsRequest$CreatedBefore' => 'A filter that returns only artifacts created on or before the specified time.
', 'ListAssociationsRequest$CreatedAfter' => 'A filter that returns only associations created on or after the specified time.
', 'ListAssociationsRequest$CreatedBefore' => 'A filter that returns only associations created on or before the specified time.
', 'ListAutoMLJobsRequest$CreationTimeAfter' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$CreationTimeBefore' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$LastModifiedTimeAfter' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$LastModifiedTimeBefore' => 'Request a list of jobs, using a filter for time.
', 'ListClusterNodesRequest$CreationTimeAfter' => 'A filter that returns nodes in a SageMaker HyperPod cluster created after the specified time. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
YYYY-MM-DDThh:mm:ss.sssTZD
(UTC), for example, 2014-10-01T20:30:00.000Z
YYYY-MM-DDThh:mm:ss.sssTZD
(with offset), for example, 2014-10-01T12:30:00.000-08:00
YYYY-MM-DD
, for example, 2014-10-01
Unix time in seconds, for example, 1412195400
. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
', 'ListClusterNodesRequest$CreationTimeBefore' => 'A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for CreationTimeAfter
. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
Set a start time for the time range during which you want to list SageMaker HyperPod clusters. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
YYYY-MM-DDThh:mm:ss.sssTZD
(UTC), for example, 2014-10-01T20:30:00.000Z
YYYY-MM-DDThh:mm:ss.sssTZD
(with offset), for example, 2014-10-01T12:30:00.000-08:00
YYYY-MM-DD
, for example, 2014-10-01
Unix time in seconds, for example, 1412195400
. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
', 'ListClustersRequest$CreationTimeBefore' => 'Set an end time for the time range during which you want to list SageMaker HyperPod clusters. A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for CreationTimeAfter
. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
A filter that returns only Git repositories that were last modified after the specified time.
', 'ListCodeRepositoriesInput$LastModifiedTimeBefore' => 'A filter that returns only Git repositories that were last modified before the specified time.
', 'ListContextsRequest$CreatedAfter' => 'A filter that returns only contexts created on or after the specified time.
', 'ListContextsRequest$CreatedBefore' => 'A filter that returns only contexts created on or before the specified time.
', 'ListDataQualityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only data quality monitoring job definitions created before the specified time.
', 'ListDataQualityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only data quality monitoring job definitions created after the specified time.
', 'ListDeviceFleetsRequest$CreationTimeAfter' => 'Filter fleets where packaging job was created after specified time.
', 'ListDeviceFleetsRequest$CreationTimeBefore' => 'Filter fleets where the edge packaging job was created before specified time.
', 'ListDeviceFleetsRequest$LastModifiedTimeAfter' => 'Select fleets where the job was updated after X
', 'ListDeviceFleetsRequest$LastModifiedTimeBefore' => 'Select fleets where the job was updated before X
', 'ListDevicesRequest$LatestHeartbeatAfter' => 'Select fleets where the job was updated after X
', 'ListEdgeDeploymentPlansRequest$CreationTimeAfter' => 'Selects edge deployment plans created after this time.
', 'ListEdgeDeploymentPlansRequest$CreationTimeBefore' => 'Selects edge deployment plans created before this time.
', 'ListEdgeDeploymentPlansRequest$LastModifiedTimeAfter' => 'Selects edge deployment plans that were last updated after this time.
', 'ListEdgeDeploymentPlansRequest$LastModifiedTimeBefore' => 'Selects edge deployment plans that were last updated before this time.
', 'ListEdgePackagingJobsRequest$CreationTimeAfter' => 'Select jobs where the job was created after specified time.
', 'ListEdgePackagingJobsRequest$CreationTimeBefore' => 'Select jobs where the job was created before specified time.
', 'ListEdgePackagingJobsRequest$LastModifiedTimeAfter' => 'Select jobs where the job was updated after specified time.
', 'ListEdgePackagingJobsRequest$LastModifiedTimeBefore' => 'Select jobs where the job was updated before specified time.
', 'ListEndpointConfigsInput$CreationTimeBefore' => 'A filter that returns only endpoint configurations created before the specified time (timestamp).
', 'ListEndpointConfigsInput$CreationTimeAfter' => 'A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).
', 'ListEndpointsInput$CreationTimeBefore' => 'A filter that returns only endpoints that were created before the specified time (timestamp).
', 'ListEndpointsInput$CreationTimeAfter' => 'A filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).
', 'ListEndpointsInput$LastModifiedTimeBefore' => 'A filter that returns only endpoints that were modified before the specified timestamp.
', 'ListEndpointsInput$LastModifiedTimeAfter' => 'A filter that returns only endpoints that were modified after the specified timestamp.
', 'ListExperimentsRequest$CreatedAfter' => 'A filter that returns only experiments created after the specified time.
', 'ListExperimentsRequest$CreatedBefore' => 'A filter that returns only experiments created before the specified time.
', 'ListFlowDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only flow definitions with a creation time greater than or equal to the specified timestamp.
', 'ListFlowDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only flow definitions that were created before the specified timestamp.
', 'ListHubContentVersionsRequest$CreationTimeBefore' => 'Only list hub content versions that were created before the time specified.
', 'ListHubContentVersionsRequest$CreationTimeAfter' => 'Only list hub content versions that were created after the time specified.
', 'ListHubContentsRequest$CreationTimeBefore' => 'Only list hub content that was created before the time specified.
', 'ListHubContentsRequest$CreationTimeAfter' => 'Only list hub content that was created after the time specified.
', 'ListHubsRequest$CreationTimeBefore' => 'Only list hubs that were created before the time specified.
', 'ListHubsRequest$CreationTimeAfter' => 'Only list hubs that were created after the time specified.
', 'ListHubsRequest$LastModifiedTimeBefore' => 'Only list hubs that were last modified before the time specified.
', 'ListHubsRequest$LastModifiedTimeAfter' => 'Only list hubs that were last modified after the time specified.
', 'ListHumanTaskUisRequest$CreationTimeAfter' => 'A filter that returns only human task user interfaces with a creation time greater than or equal to the specified timestamp.
', 'ListHumanTaskUisRequest$CreationTimeBefore' => 'A filter that returns only human task user interfaces that were created before the specified timestamp.
', 'ListHyperParameterTuningJobsRequest$CreationTimeAfter' => 'A filter that returns only tuning jobs that were created after the specified time.
', 'ListHyperParameterTuningJobsRequest$CreationTimeBefore' => 'A filter that returns only tuning jobs that were created before the specified time.
', 'ListHyperParameterTuningJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only tuning jobs that were modified after the specified time.
', 'ListHyperParameterTuningJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only tuning jobs that were modified before the specified time.
', 'ListImageVersionsRequest$CreationTimeAfter' => 'A filter that returns only versions created on or after the specified time.
', 'ListImageVersionsRequest$CreationTimeBefore' => 'A filter that returns only versions created on or before the specified time.
', 'ListImageVersionsRequest$LastModifiedTimeAfter' => 'A filter that returns only versions modified on or after the specified time.
', 'ListImageVersionsRequest$LastModifiedTimeBefore' => 'A filter that returns only versions modified on or before the specified time.
', 'ListImagesRequest$CreationTimeAfter' => 'A filter that returns only images created on or after the specified time.
', 'ListImagesRequest$CreationTimeBefore' => 'A filter that returns only images created on or before the specified time.
', 'ListImagesRequest$LastModifiedTimeAfter' => 'A filter that returns only images modified on or after the specified time.
', 'ListImagesRequest$LastModifiedTimeBefore' => 'A filter that returns only images modified on or before the specified time.
', 'ListInferenceComponentsInput$CreationTimeBefore' => 'Filters the results to only those inference components that were created before the specified time.
', 'ListInferenceComponentsInput$CreationTimeAfter' => 'Filters the results to only those inference components that were created after the specified time.
', 'ListInferenceComponentsInput$LastModifiedTimeBefore' => 'Filters the results to only those inference components that were updated before the specified time.
', 'ListInferenceComponentsInput$LastModifiedTimeAfter' => 'Filters the results to only those inference components that were updated after the specified time.
', 'ListInferenceExperimentsRequest$CreationTimeAfter' => 'Selects inference experiments which were created after this timestamp.
', 'ListInferenceExperimentsRequest$CreationTimeBefore' => 'Selects inference experiments which were created before this timestamp.
', 'ListInferenceExperimentsRequest$LastModifiedTimeAfter' => 'Selects inference experiments which were last modified after this timestamp.
', 'ListInferenceExperimentsRequest$LastModifiedTimeBefore' => 'Selects inference experiments which were last modified before this timestamp.
', 'ListLabelingJobsForWorkteamRequest$CreationTimeAfter' => 'A filter that returns only labeling jobs created after the specified time (timestamp).
', 'ListLabelingJobsForWorkteamRequest$CreationTimeBefore' => 'A filter that returns only labeling jobs created before the specified time (timestamp).
', 'ListLabelingJobsRequest$CreationTimeAfter' => 'A filter that returns only labeling jobs created after the specified time (timestamp).
', 'ListLabelingJobsRequest$CreationTimeBefore' => 'A filter that returns only labeling jobs created before the specified time (timestamp).
', 'ListLabelingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only labeling jobs modified after the specified time (timestamp).
', 'ListLabelingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only labeling jobs modified before the specified time (timestamp).
', 'ListLineageGroupsRequest$CreatedAfter' => 'A timestamp to filter against lineage groups created after a certain point in time.
', 'ListLineageGroupsRequest$CreatedBefore' => 'A timestamp to filter against lineage groups created before a certain point in time.
', 'ListModelBiasJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model bias jobs created before a specified time.
', 'ListModelBiasJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model bias jobs created after a specified time.
', 'ListModelCardExportJobsRequest$CreationTimeAfter' => 'Only list model card export jobs that were created after the time specified.
', 'ListModelCardExportJobsRequest$CreationTimeBefore' => 'Only list model card export jobs that were created before the time specified.
', 'ListModelCardVersionsRequest$CreationTimeAfter' => 'Only list model card versions that were created after the time specified.
', 'ListModelCardVersionsRequest$CreationTimeBefore' => 'Only list model card versions that were created before the time specified.
', 'ListModelCardsRequest$CreationTimeAfter' => 'Only list model cards that were created after the time specified.
', 'ListModelCardsRequest$CreationTimeBefore' => 'Only list model cards that were created before the time specified.
', 'ListModelExplainabilityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model explainability jobs created before a specified time.
', 'ListModelExplainabilityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model explainability jobs created after a specified time.
', 'ListModelQualityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model quality monitoring job definitions created before the specified time.
', 'ListModelQualityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model quality monitoring job definitions created after the specified time.
', 'ListModelsInput$CreationTimeBefore' => 'A filter that returns only models created before the specified time (timestamp).
', 'ListModelsInput$CreationTimeAfter' => 'A filter that returns only models with a creation time greater than or equal to the specified time (timestamp).
', 'ListMonitoringAlertHistoryRequest$CreationTimeBefore' => 'A filter that returns only alerts created on or before the specified time.
', 'ListMonitoringAlertHistoryRequest$CreationTimeAfter' => 'A filter that returns only alerts created on or after the specified time.
', 'ListMonitoringExecutionsRequest$ScheduledTimeBefore' => 'Filter for jobs scheduled before a specified time.
', 'ListMonitoringExecutionsRequest$ScheduledTimeAfter' => 'Filter for jobs scheduled after a specified time.
', 'ListMonitoringExecutionsRequest$CreationTimeBefore' => 'A filter that returns only jobs created before a specified time.
', 'ListMonitoringExecutionsRequest$CreationTimeAfter' => 'A filter that returns only jobs created after a specified time.
', 'ListMonitoringExecutionsRequest$LastModifiedTimeBefore' => 'A filter that returns only jobs modified after a specified time.
', 'ListMonitoringExecutionsRequest$LastModifiedTimeAfter' => 'A filter that returns only jobs modified before a specified time.
', 'ListMonitoringSchedulesRequest$CreationTimeBefore' => 'A filter that returns only monitoring schedules created before a specified time.
', 'ListMonitoringSchedulesRequest$CreationTimeAfter' => 'A filter that returns only monitoring schedules created after a specified time.
', 'ListMonitoringSchedulesRequest$LastModifiedTimeBefore' => 'A filter that returns only monitoring schedules modified before a specified time.
', 'ListMonitoringSchedulesRequest$LastModifiedTimeAfter' => 'A filter that returns only monitoring schedules modified after a specified time.
', 'ListPipelineExecutionsRequest$CreatedAfter' => 'A filter that returns the pipeline executions that were created after a specified time.
', 'ListPipelineExecutionsRequest$CreatedBefore' => 'A filter that returns the pipeline executions that were created before a specified time.
', 'ListPipelinesRequest$CreatedAfter' => 'A filter that returns the pipelines that were created after a specified time.
', 'ListPipelinesRequest$CreatedBefore' => 'A filter that returns the pipelines that were created before a specified time.
', 'ListProcessingJobsRequest$CreationTimeAfter' => 'A filter that returns only processing jobs created after the specified time.
', 'ListProcessingJobsRequest$CreationTimeBefore' => 'A filter that returns only processing jobs created after the specified time.
', 'ListProcessingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only processing jobs modified after the specified time.
', 'ListProcessingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only processing jobs modified before the specified time.
', 'ListProjectsInput$CreationTimeAfter' => 'A filter that returns the projects that were created after a specified time.
', 'ListProjectsInput$CreationTimeBefore' => 'A filter that returns the projects that were created before a specified time.
', 'ListResourceCatalogsRequest$CreationTimeAfter' => ' Use this parameter to search for ResourceCatalog
s created after a specific date and time.
Use this parameter to search for ResourceCatalog
s created before a specific date and time.
A filter that returns only Lifecycle Configurations created on or before the specified time.
', 'ListStudioLifecycleConfigsRequest$CreationTimeAfter' => 'A filter that returns only Lifecycle Configurations created on or after the specified time.
', 'ListStudioLifecycleConfigsRequest$ModifiedTimeBefore' => 'A filter that returns only Lifecycle Configurations modified before the specified time.
', 'ListStudioLifecycleConfigsRequest$ModifiedTimeAfter' => 'A filter that returns only Lifecycle Configurations modified after the specified time.
', 'ListTrainingJobsRequest$CreationTimeAfter' => 'A filter that returns only training jobs created after the specified time (timestamp).
', 'ListTrainingJobsRequest$CreationTimeBefore' => 'A filter that returns only training jobs created before the specified time (timestamp).
', 'ListTrainingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only training jobs modified after the specified time (timestamp).
', 'ListTrainingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only training jobs modified before the specified time (timestamp).
', 'ListTransformJobsRequest$CreationTimeAfter' => 'A filter that returns only transform jobs created after the specified time.
', 'ListTransformJobsRequest$CreationTimeBefore' => 'A filter that returns only transform jobs created before the specified time.
', 'ListTransformJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only transform jobs modified after the specified time.
', 'ListTransformJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only transform jobs modified before the specified time.
', 'ListTrialComponentsRequest$CreatedAfter' => 'A filter that returns only components created after the specified time.
', 'ListTrialComponentsRequest$CreatedBefore' => 'A filter that returns only components created before the specified time.
', 'ListTrialsRequest$CreatedAfter' => 'A filter that returns only trials created after the specified time.
', 'ListTrialsRequest$CreatedBefore' => 'A filter that returns only trials created before the specified time.
', 'MetricData$Timestamp' => 'The date and time that the algorithm emitted the metric.
', 'Model$CreationTime' => 'A timestamp that indicates when the model was created.
', 'ModelCard$CreationTime' => 'The date and time that the model card was created.
', 'ModelCard$LastModifiedTime' => 'The date and time that the model card was last modified.
', 'ModelCardExportJobSummary$CreatedAt' => 'The date and time that the model card export job was created.
', 'ModelCardExportJobSummary$LastModifiedAt' => 'The date and time that the model card export job was last modified..
', 'ModelCardSummary$CreationTime' => 'The date and time that the model card was created.
', 'ModelCardSummary$LastModifiedTime' => 'The date and time that the model card was last modified.
', 'ModelCardVersionSummary$CreationTime' => 'The date and time that the model card version was created.
', 'ModelCardVersionSummary$LastModifiedTime' => 'The time date and time that the model card version was last modified.
', 'ModelDashboardEndpoint$CreationTime' => 'A timestamp that indicates when the endpoint was created.
', 'ModelDashboardEndpoint$LastModifiedTime' => 'The last time the endpoint was modified.
', 'ModelDashboardModelCard$CreationTime' => 'A timestamp that indicates when the model card was created.
', 'ModelDashboardModelCard$LastModifiedTime' => 'A timestamp that indicates when the model card was last updated.
', 'ModelDashboardMonitoringSchedule$CreationTime' => 'A timestamp that indicates when the monitoring schedule was created.
', 'ModelDashboardMonitoringSchedule$LastModifiedTime' => 'A timestamp that indicates when the monitoring schedule was last updated.
', 'ModelPackage$LastModifiedTime' => 'The last time the model package was modified.
', 'ModelSummary$CreationTime' => 'A timestamp that indicates when the model was created.
', 'MonitoringAlertHistorySummary$CreationTime' => 'A timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert
to OK
, or from OK
to InAlert
.
A timestamp that indicates when a monitor alert was created.
', 'MonitoringAlertSummary$LastModifiedTime' => 'A timestamp that indicates when a monitor alert was last updated.
', 'MonitoringExecutionSummary$ScheduledTime' => 'The time the monitoring job was scheduled.
', 'MonitoringExecutionSummary$CreationTime' => 'The time at which the monitoring job was created.
', 'MonitoringExecutionSummary$LastModifiedTime' => 'A timestamp that indicates the last time the monitoring job was modified.
', 'MonitoringJobDefinitionSummary$CreationTime' => 'The time that the monitoring job was created.
', 'MonitoringSchedule$CreationTime' => 'The time that the monitoring schedule was created.
', 'MonitoringSchedule$LastModifiedTime' => 'The last time the monitoring schedule was changed.
', 'MonitoringScheduleSummary$CreationTime' => 'The creation time of the monitoring schedule.
', 'MonitoringScheduleSummary$LastModifiedTime' => 'The last time the monitoring schedule was modified.
', 'PendingDeploymentSummary$StartTime' => 'The start time of the deployment.
', 'Pipeline$CreationTime' => 'The creation time of the pipeline.
', 'Pipeline$LastModifiedTime' => 'The time that the pipeline was last modified.
', 'Pipeline$LastRunTime' => 'The time when the pipeline was last run.
', 'PipelineExecution$CreationTime' => 'The creation time of the pipeline execution.
', 'PipelineExecution$LastModifiedTime' => 'The time that the pipeline execution was last modified.
', 'PipelineExecutionStep$StartTime' => 'The time that the step started executing.
', 'PipelineExecutionStep$EndTime' => 'The time that the step stopped executing.
', 'PipelineExecutionSummary$StartTime' => 'The start time of the pipeline execution.
', 'PipelineSummary$CreationTime' => 'The creation time of the pipeline.
', 'PipelineSummary$LastModifiedTime' => 'The time that the pipeline was last modified.
', 'PipelineSummary$LastExecutionTime' => 'The last time that a pipeline execution began.
', 'ProcessingJob$ProcessingEndTime' => 'The time that the processing job ended.
', 'ProcessingJob$ProcessingStartTime' => 'The time that the processing job started.
', 'ProcessingJob$LastModifiedTime' => 'The time the processing job was last modified.
', 'ProcessingJob$CreationTime' => 'The time the processing job was created.
', 'ProcessingJobSummary$CreationTime' => 'The time at which the processing job was created.
', 'ProcessingJobSummary$ProcessingEndTime' => 'The time at which the processing job completed.
', 'ProcessingJobSummary$LastModifiedTime' => 'A timestamp that indicates the last time the processing job was modified.
', 'ProductionVariantStatus$StartTime' => 'The start time of the current status change.
', 'ProfilerRuleEvaluationStatus$LastModifiedTime' => 'Timestamp when the rule evaluation status was last modified.
', 'Project$CreationTime' => 'A timestamp specifying when the project was created.
', 'Project$LastModifiedTime' => 'A timestamp container for when the project was last modified.
', 'ProjectSummary$CreationTime' => 'The time that the project was created.
', 'QueryFilters$CreatedBefore' => 'Filter the lineage entities connected to the StartArn
(s) by created date.
Filter the lineage entities connected to the StartArn
(s) after the create date.
Filter the lineage entities connected to the StartArn
(s) before the last modified date.
Filter the lineage entities connected to the StartArn
(s) after the last modified date.
The time the ResourceCatalog
was created.
A timestamp that shows when the training job transitioned to the current secondary status state.
', 'SecondaryStatusTransition$EndTime' => 'A timestamp that shows when the training job transitioned out of this secondary status state into another secondary status state or when the training job has ended.
', 'StudioLifecycleConfigDetails$CreationTime' => 'The creation time of the Amazon SageMaker Studio Lifecycle Configuration.
', 'StudioLifecycleConfigDetails$LastModifiedTime' => 'This value is equivalent to CreationTime because Amazon SageMaker Studio Lifecycle Configurations are immutable.
', 'TrainingJob$CreationTime' => 'A timestamp that indicates when the training job was created.
', 'TrainingJob$TrainingStartTime' => 'Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime
. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last modified.
', 'TrainingJobSummary$CreationTime' => 'A timestamp that shows when the training job was created.
', 'TrainingJobSummary$TrainingEndTime' => 'A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses (Completed
, Failed
, or Stopped
).
Timestamp when the training job was last modified.
', 'TransformJob$CreationTime' => 'A timestamp that shows when the transform Job was created.
', 'TransformJob$TransformStartTime' => 'Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime
.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime
.
A timestamp that shows when the transform Job was created.
', 'TransformJobSummary$TransformEndTime' => 'Indicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.
', 'TransformJobSummary$LastModifiedTime' => 'Indicates when the transform job was last modified.
', 'Trial$CreationTime' => 'When the trial was created.
', 'Trial$LastModifiedTime' => 'Who last modified the trial.
', 'TrialComponent$StartTime' => 'When the component started.
', 'TrialComponent$EndTime' => 'When the component ended.
', 'TrialComponent$CreationTime' => 'When the component was created.
', 'TrialComponent$LastModifiedTime' => 'When the component was last modified.
', 'TrialComponentMetricSummary$TimeStamp' => 'When the metric was last updated.
', 'TrialComponentSimpleSummary$CreationTime' => 'When the component was created.
', 'TrialComponentSummary$StartTime' => 'When the component started.
', 'TrialComponentSummary$EndTime' => 'When the component ended.
', 'TrialComponentSummary$CreationTime' => 'When the component was created.
', 'TrialComponentSummary$LastModifiedTime' => 'When the component was last modified.
', 'TrialSummary$CreationTime' => 'When the trial was created.
', 'TrialSummary$LastModifiedTime' => 'When the trial was last modified.
', 'UpdateTrialComponentRequest$StartTime' => 'When the component started.
', 'UpdateTrialComponentRequest$EndTime' => 'When the component ended.
', 'Workforce$LastUpdatedDate' => 'The most recent date that UpdateWorkforce was used to successfully add one or more IP address ranges (CIDRs) to a private workforce\'s allow list.
', 'Workforce$CreateDate' => 'The date that the workforce is created.
', 'Workteam$CreateDate' => 'The date and time that the work team was created (timestamp).
', 'Workteam$LastUpdatedDate' => 'The date and time that the work team was last updated (timestamp).
', ], ], 'TimestampAttributeName' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$TimestampAttributeName' => 'The name of the column indicating a point in time at which the target value of a given item is recorded.
', ], ], 'TrafficDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'Phase$DurationInSeconds' => 'Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600. This value should not exceed JobDurationInSeconds
.
Defines how long each traffic step should be.
', ], ], 'TrafficPattern' => [ 'base' => 'Defines the traffic pattern of the load test.
', 'refs' => [ 'RecommendationJobInputConfig$TrafficPattern' => 'Specifies the traffic pattern of the job.
', ], ], 'TrafficRoutingConfig' => [ 'base' => 'Defines the traffic routing strategy during an endpoint deployment to shift traffic from the old fleet to the new fleet.
', 'refs' => [ 'BlueGreenUpdatePolicy$TrafficRoutingConfiguration' => 'Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment.
', ], ], 'TrafficRoutingConfigType' => [ 'base' => NULL, 'refs' => [ 'TrafficRoutingConfig$Type' => 'Traffic routing strategy type.
ALL_AT_ONCE
: Endpoint traffic shifts to the new fleet in a single step.
CANARY
: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic.
LINEAR
: Endpoint traffic shifts to the new fleet in n steps of a configurable size.
Defines the traffic patterns. Choose either PHASES
or STAIRS
.
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
', ], ], 'TrainingContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$ContainerEntrypoint' => 'The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information.
', ], ], 'TrainingContainerEntrypointString' => [ 'base' => NULL, 'refs' => [ 'TrainingContainerEntrypoint$member' => NULL, ], ], 'TrainingEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'TrainingEnvironmentMap$key' => NULL, ], ], 'TrainingEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$Environment' => 'The environment variables to set in the Docker container.
', 'DescribeTrainingJobResponse$Environment' => 'The environment variables to set in the Docker container.
', 'TrainingJob$Environment' => 'The environment variables to set in the Docker container.
', ], ], 'TrainingEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'TrainingEnvironmentMap$value' => NULL, ], ], 'TrainingImageConfig' => [ 'base' => 'The configuration to use an image from a private Docker registry for a training job.
', 'refs' => [ 'AlgorithmSpecification$TrainingImageConfig' => 'The configuration to use an image from a private Docker registry for a training job.
', ], ], 'TrainingInputMode' => [ 'base' => 'The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports Pipe
mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
File mode
If an algorithm supports File
mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won\'t be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports FastFile
mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.
FastFile
mode works best when the data is read sequentially. Augmented manifest files aren\'t supported. The startup time is lower when there are fewer files in the S3 bucket provided.
(Optional) The input mode to use for the data channel in a training job. If you don\'t set a value for InputMode
, SageMaker uses the value set for TrainingInputMode
. Use this parameter to override the TrainingInputMode
setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job\'s general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File
input mode. To stream data directly from Amazon S3 to the container, choose Pipe
input mode.
To use a model for incremental training, choose File
input model.
The number of instances of the type specified by InstanceType
. Choose an instance count larger than 1 for distributed training algorithms. See Step 2: Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
The number of compute instances of type InstanceType
to use. For distributed training, select a value greater than 1.
Specifies the number of instances of the instance group.
', 'ResourceConfig$InstanceCount' => 'The number of ML compute instances to use. For distributed training, provide a value greater than 1.
', ], ], 'TrainingInstanceType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningInstanceConfig$InstanceType' => 'The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type descriptions.
', 'HyperParameterTuningResourceConfig$InstanceType' => 'The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.
', 'InstanceGroup$InstanceType' => 'Specifies the instance type of the instance group.
', 'ResourceConfig$InstanceType' => 'The ML compute instance type.
SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting December 9th, 2022.
Amazon EC2 P4de instances (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, which accelerate the speed of training ML models that need to be trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker supports ML training jobs on P4de instances (ml.p4de.24xlarge
) to reduce model training time. The ml.p4de.24xlarge
instances are available in the following Amazon Web Services Regions.
US East (N. Virginia) (us-east-1)
US West (Oregon) (us-west-2)
To request quota limit increase and start using P4de instances, contact the SageMaker Training service team through your account team.
A list of the instance types that this algorithm can use for training.
', ], ], 'TrainingJob' => [ 'base' => 'Contains information about a training job.
', 'refs' => [ 'SearchRecord$TrainingJob' => 'The properties of a training job.
', 'TrialComponentSourceDetail$TrainingJob' => 'Information about a training job that\'s the source of a trial component.
', ], ], 'TrainingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'DescribeProcessingJobResponse$TrainingJobArn' => 'The ARN of a training job associated with this processing job.
', 'DescribeTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'HyperParameterTrainingJobSummary$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'ProcessingJob$TrainingJobArn' => 'The ARN of the training job associated with this processing job.
', 'TrainingJob$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'TrainingJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the training job that was run by this step execution.
', 'TrainingJobSummary$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'UpdateTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', ], ], 'TrainingJobDefinition' => [ 'base' => 'Defines the input needed to run a training job using the algorithm.
', 'refs' => [ 'AlgorithmValidationProfile$TrainingJobDefinition' => 'The TrainingJobDefinition
object that describes the training job that SageMaker runs to validate your algorithm.
Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband
strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType
must be OFF
to use Hyperband
. This parameter can take on one of the following values (the default value is OFF
):
Training jobs launched by the hyperparameter tuning job do not use early stopping.
SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.
The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
', 'DescribeTrainingJobRequest$TrainingJobName' => 'The name of the training job.
', 'DescribeTrainingJobResponse$TrainingJobName' => 'Name of the model training job.
', 'HyperParameterTrainingJobSummary$TrainingJobName' => 'The name of the training job.
', 'StopTrainingJobRequest$TrainingJobName' => 'The name of the training job to stop.
', 'TrainingJob$TrainingJobName' => 'The name of the training job.
', 'TrainingJobSummary$TrainingJobName' => 'The name of the training job that you want a summary for.
', 'UpdateTrainingJobRequest$TrainingJobName' => 'The name of a training job to update the Debugger profiling configuration.
', 'WarmPoolStatus$ReusedByJob' => 'The name of the matching training job that reused the warm pool.
', ], ], 'TrainingJobSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsForHyperParameterTuningJobRequest$SortBy' => 'The field to sort results by. The default is Name
.
If the value of this field is FinalObjectiveMetricValue
, any training jobs that did not return an objective metric are not listed.
The status of the training job.
SageMaker provides the following training job statuses:
InProgress
- The training is in progress.
Completed
- The training job has completed.
Failed
- The training job has failed. To see the reason for the failure, see the FailureReason
field in the response to a DescribeTrainingJobResponse
call.
Stopping
- The training job is stopping.
Stopped
- The training job has stopped.
For more detailed information, see SecondaryStatus
.
The status of the training job.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$StatusEquals' => 'A filter that returns only training jobs with the specified status.
', 'ListTrainingJobsRequest$StatusEquals' => 'A filter that retrieves only training jobs with a specific status.
', 'TrainingJob$TrainingJobStatus' => 'The status of the training job.
Training job statuses are:
InProgress
- The training is in progress.
Completed
- The training job has completed.
Failed
- The training job has failed. To see the reason for the failure, see the FailureReason
field in the response to a DescribeTrainingJobResponse
call.
Stopping
- The training job is stopping.
Stopped
- The training job has stopped.
For more detailed information, see SecondaryStatus
.
The status of the training job.
', ], ], 'TrainingJobStatusCounter' => [ 'base' => NULL, 'refs' => [ 'TrainingJobStatusCounters$Completed' => 'The number of completed training jobs launched by the hyperparameter tuning job.
', 'TrainingJobStatusCounters$InProgress' => 'The number of in-progress training jobs launched by a hyperparameter tuning job.
', 'TrainingJobStatusCounters$RetryableError' => 'The number of training jobs that failed, but can be retried. A failed training job can be retried only if it failed because an internal service error occurred.
', 'TrainingJobStatusCounters$NonRetryableError' => 'The number of training jobs that failed and can\'t be retried. A failed training job can\'t be retried if it failed because a client error occurred.
', 'TrainingJobStatusCounters$Stopped' => 'The number of training jobs launched by a hyperparameter tuning job that were manually stopped.
', ], ], 'TrainingJobStatusCounters' => [ 'base' => 'The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$TrainingJobStatusCounters' => 'The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.
', 'HyperParameterTuningJobSearchEntity$TrainingJobStatusCounters' => NULL, 'HyperParameterTuningJobSummary$TrainingJobStatusCounters' => 'The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
', ], ], 'TrainingJobStepMetadata' => [ 'base' => 'Metadata for a training job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TrainingJob' => 'The Amazon Resource Name (ARN) of the training job that was run by this step execution.
', ], ], 'TrainingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsResponse$TrainingJobSummaries' => 'An array of TrainingJobSummary
objects, each listing a training job.
Provides summary information about a training job.
', 'refs' => [ 'TrainingJobSummaries$member' => NULL, ], ], 'TrainingRepositoryAccessMode' => [ 'base' => NULL, 'refs' => [ 'TrainingImageConfig$TrainingRepositoryAccessMode' => 'The method that your training job will use to gain access to the images in your private Docker registry. For access to an image in a private Docker registry, set to Vpc
.
An object containing authentication information for a private Docker registry.
', 'refs' => [ 'TrainingImageConfig$TrainingRepositoryAuthConfig' => 'An object containing authentication information for a private Docker registry containing your training images.
', ], ], 'TrainingRepositoryCredentialsProviderArn' => [ 'base' => NULL, 'refs' => [ 'TrainingRepositoryAuthConfig$TrainingRepositoryCredentialsProviderArn' => 'The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access credentials to your private Docker registry.
', ], ], 'TrainingSpecification' => [ 'base' => 'Defines how the algorithm is used for a training job.
', 'refs' => [ 'CreateAlgorithmInput$TrainingSpecification' => 'Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support train
, validation
, and test
channels.
Details about training jobs run by this algorithm.
', ], ], 'TrainingTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$TrainingTimeInSeconds' => 'The training time in seconds.
', 'TrainingJob$TrainingTimeInSeconds' => 'The training time in seconds.
', ], ], 'TransformDataSource' => [ 'base' => 'Describes the location of the channel data.
', 'refs' => [ 'TransformInput$DataSource' => 'Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
', ], ], 'TransformEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'TransformEnvironmentMap$key' => NULL, ], ], 'TransformEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'DescribeTransformJobResponse$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'TransformJob$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'TransformJobDefinition$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', ], ], 'TransformEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'TransformEnvironmentMap$value' => NULL, ], ], 'TransformInput' => [ 'base' => 'Describes the input source of a transform job and the way the transform job consumes it.
', 'refs' => [ 'CreateTransformJobRequest$TransformInput' => 'Describes the input source and the way the transform job consumes it.
', 'DescribeTransformJobResponse$TransformInput' => 'Describes the dataset to be transformed and the Amazon S3 location where it is stored.
', 'TransformJob$TransformInput' => NULL, 'TransformJobDefinition$TransformInput' => 'A description of the input source and the way the transform job consumes it.
', ], ], 'TransformInstanceCount' => [ 'base' => NULL, 'refs' => [ 'TransformResources$InstanceCount' => 'The number of ML compute instances to use in the transform job. The default value is 1
, and the maximum is 100
. For distributed transform jobs, specify a value greater than 1
.
The ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or ml.m5.large
instance types.
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
', 'InferenceSpecification$SupportedTransformInstanceTypes' => 'A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
This parameter is required for unversioned models, and optional for versioned models.
', ], ], 'TransformJob' => [ 'base' => 'A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
', 'refs' => [ 'ModelDashboardModel$LastBatchTransformJob' => NULL, 'TrialComponentSourceDetail$TransformJob' => 'Information about a transform job that\'s the source of a trial component.
', ], ], 'TransformJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobResponse$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'DescribeTransformJobResponse$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'TransformJob$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'TransformJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
', 'TransformJobSummary$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', ], ], 'TransformJobDefinition' => [ 'base' => 'Defines the input needed to run a transform job using the inference specification specified in the algorithm.
', 'refs' => [ 'AlgorithmValidationProfile$TransformJobDefinition' => 'The TransformJobDefinition
object that describes the transform job that SageMaker runs to validate your algorithm.
The TransformJobDefinition
object that describes the transform job used for the validation of the model package.
The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
', 'DescribeTransformJobRequest$TransformJobName' => 'The name of the transform job that you want to view details of.
', 'DescribeTransformJobResponse$TransformJobName' => 'The name of the transform job.
', 'StopTransformJobRequest$TransformJobName' => 'The name of the batch transform job to stop.
', 'TransformJob$TransformJobName' => 'The name of the transform job.
', 'TransformJobSummary$TransformJobName' => 'The name of the transform job.
', ], ], 'TransformJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeTransformJobResponse$TransformJobStatus' => 'The status of the transform job. If the transform job failed, the reason is returned in the FailureReason
field.
A filter that retrieves only transform jobs with a specific status.
', 'TransformJob$TransformJobStatus' => 'The status of the transform job.
Transform job statuses are:
InProgress
- The job is in progress.
Completed
- The job has completed.
Failed
- The transform job has failed. To see the reason for the failure, see the FailureReason
field in the response to a DescribeTransformJob
call.
Stopping
- The transform job is stopping.
Stopped
- The transform job has stopped.
The status of the transform job.
', ], ], 'TransformJobStepMetadata' => [ 'base' => 'Metadata for a transform job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TransformJob' => 'The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
', ], ], 'TransformJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTransformJobsResponse$TransformJobSummaries' => 'An array of TransformJobSummary
objects.
Provides a summary of a transform job. Multiple TransformJobSummary
objects are returned as a list after in response to a ListTransformJobs call.
Describes the results of a transform job.
', 'refs' => [ 'CreateTransformJobRequest$TransformOutput' => 'Describes the results of the transform job.
', 'DescribeTransformJobResponse$TransformOutput' => 'Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
', 'TransformJob$TransformOutput' => NULL, 'TransformJobDefinition$TransformOutput' => 'Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
', ], ], 'TransformResources' => [ 'base' => 'Describes the resources, including ML instance types and ML instance count, to use for transform job.
', 'refs' => [ 'CreateTransformJobRequest$TransformResources' => 'Describes the resources, including ML instance types and ML instance count, to use for the transform job.
', 'DescribeTransformJobResponse$TransformResources' => 'Describes the resources, including ML instance types and ML instance count, to use for the transform job.
', 'TransformJob$TransformResources' => NULL, 'TransformJobDefinition$TransformResources' => 'Identifies the ML compute instances for the transform job.
', ], ], 'TransformS3DataSource' => [ 'base' => 'Describes the S3 data source.
', 'refs' => [ 'TransformDataSource$S3DataSource' => 'The S3 location of the data source that is associated with a channel.
', ], ], 'TransformationAttributeName' => [ 'base' => NULL, 'refs' => [ 'AggregationTransformations$key' => NULL, 'FillingTransformations$key' => NULL, ], ], 'Trial' => [ 'base' => 'The properties of a trial as returned by the Search API.
', 'refs' => [ 'SearchRecord$Trial' => 'The properties of a trial.
', ], ], 'TrialArn' => [ 'base' => NULL, 'refs' => [ 'AssociateTrialComponentResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'CreateTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'DeleteTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial that is being deleted.
', 'DescribeTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'DisassociateTrialComponentResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'Trial$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'TrialSummary$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'UpdateTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', ], ], 'TrialComponent' => [ 'base' => 'The properties of a trial component as returned by the Search API.
', 'refs' => [ 'SearchRecord$TrialComponent' => 'The properties of a trial component.
', ], ], 'TrialComponentArn' => [ 'base' => NULL, 'refs' => [ 'AssociateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'CreateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'DeleteTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the component is being deleted.
', 'DescribeTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'DisassociateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponent$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponentSimpleSummary$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponentSummary$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'UpdateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', ], ], 'TrialComponentArtifact' => [ 'base' => 'Represents an input or output artifact of a trial component. You specify TrialComponentArtifact
as part of the InputArtifacts
and OutputArtifacts
parameters in the CreateTrialComponent request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
', 'refs' => [ 'TrialComponentArtifacts$value' => NULL, ], ], 'TrialComponentArtifactValue' => [ 'base' => NULL, 'refs' => [ 'TrialComponentArtifact$Value' => 'The location of the artifact.
', ], ], 'TrialComponentArtifacts' => [ 'base' => NULL, 'refs' => [ 'CreateTrialComponentRequest$InputArtifacts' => 'The input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.
', 'CreateTrialComponentRequest$OutputArtifacts' => 'The output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.
', 'DescribeTrialComponentResponse$InputArtifacts' => 'The input artifacts of the component.
', 'DescribeTrialComponentResponse$OutputArtifacts' => 'The output artifacts of the component.
', 'TrialComponent$InputArtifacts' => 'The input artifacts of the component.
', 'TrialComponent$OutputArtifacts' => 'The output artifacts of the component.
', 'UpdateTrialComponentRequest$InputArtifacts' => 'Replaces all of the component\'s input artifacts with the specified artifacts or adds new input artifacts. Existing input artifacts are replaced if the trial component is updated with an identical input artifact key.
', 'UpdateTrialComponentRequest$OutputArtifacts' => 'Replaces all of the component\'s output artifacts with the specified artifacts or adds new output artifacts. Existing output artifacts are replaced if the trial component is updated with an identical output artifact key.
', ], ], 'TrialComponentKey128' => [ 'base' => NULL, 'refs' => [ 'TrialComponentArtifacts$key' => NULL, ], ], 'TrialComponentKey256' => [ 'base' => NULL, 'refs' => [ 'ListTrialComponentKey256$member' => NULL, ], ], 'TrialComponentKey320' => [ 'base' => NULL, 'refs' => [ 'TrialComponentParameters$key' => NULL, ], ], 'TrialComponentMetricSummaries' => [ 'base' => NULL, 'refs' => [ 'DescribeTrialComponentResponse$Metrics' => 'The metrics for the component.
', 'TrialComponent$Metrics' => 'The metrics for the component.
', ], ], 'TrialComponentMetricSummary' => [ 'base' => 'A summary of the metrics of a trial component.
', 'refs' => [ 'TrialComponentMetricSummaries$member' => NULL, ], ], 'TrialComponentParameterValue' => [ 'base' => 'The value of a hyperparameter. Only one of NumberValue
or StringValue
can be specified.
This object is specified in the CreateTrialComponent request.
', 'refs' => [ 'TrialComponentParameters$value' => NULL, ], ], 'TrialComponentParameters' => [ 'base' => NULL, 'refs' => [ 'CreateTrialComponentRequest$Parameters' => 'The hyperparameters for the component.
', 'DescribeTrialComponentResponse$Parameters' => 'The hyperparameters of the component.
', 'TrialComponent$Parameters' => 'The hyperparameters of the component.
', 'UpdateTrialComponentRequest$Parameters' => 'Replaces all of the component\'s hyperparameters with the specified hyperparameters or add new hyperparameters. Existing hyperparameters are replaced if the trial component is updated with an identical hyperparameter key.
', ], ], 'TrialComponentPrimaryStatus' => [ 'base' => NULL, 'refs' => [ 'TrialComponentStatus$PrimaryStatus' => 'The status of the trial component.
', ], ], 'TrialComponentSimpleSummaries' => [ 'base' => NULL, 'refs' => [ 'Trial$TrialComponentSummaries' => 'A list of the components associated with the trial. For each component, a summary of the component\'s properties is included.
', ], ], 'TrialComponentSimpleSummary' => [ 'base' => 'A short summary of a trial component.
', 'refs' => [ 'TrialComponentSimpleSummaries$member' => NULL, ], ], 'TrialComponentSource' => [ 'base' => 'The Amazon Resource Name (ARN) and job type of the source of a trial component.
', 'refs' => [ 'DescribeTrialComponentResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the job type.
', 'TrialComponent$Source' => 'The Amazon Resource Name (ARN) and job type of the source of the component.
', 'TrialComponentSimpleSummary$TrialComponentSource' => NULL, 'TrialComponentSources$member' => NULL, 'TrialComponentSummary$TrialComponentSource' => NULL, ], ], 'TrialComponentSourceArn' => [ 'base' => NULL, 'refs' => [ 'TrialComponentMetricSummary$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', 'TrialComponentSource$SourceArn' => 'The source Amazon Resource Name (ARN).
', 'TrialComponentSourceDetail$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'TrialComponentSourceDetail' => [ 'base' => 'Detailed information about the source of a trial component. Either ProcessingJob
or TrainingJob
is returned.
Details of the source of the component.
', ], ], 'TrialComponentSources' => [ 'base' => NULL, 'refs' => [ 'DescribeTrialComponentResponse$Sources' => 'A list of ARNs and, if applicable, job types for multiple sources of an experiment run.
', ], ], 'TrialComponentStatus' => [ 'base' => 'The status of the trial component.
', 'refs' => [ 'CreateTrialComponentRequest$Status' => 'The status of the component. States include:
InProgress
Completed
Failed
The status of the component. States include:
InProgress
Completed
Failed
The status of the component. States include:
InProgress
Completed
Failed
The new status of the component.
', ], ], 'TrialComponentStatusMessage' => [ 'base' => NULL, 'refs' => [ 'TrialComponentStatus$Message' => 'If the component failed, a message describing why.
', ], ], 'TrialComponentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrialComponentsResponse$TrialComponentSummaries' => 'A list of the summaries of your trial components.
', ], ], 'TrialComponentSummary' => [ 'base' => 'A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName
.
The source of the trial.
', 'refs' => [ 'DescribeTrialResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the job type.
', 'Trial$Source' => NULL, 'TrialSummary$TrialSource' => NULL, ], ], 'TrialSourceArn' => [ 'base' => NULL, 'refs' => [ 'TrialSource$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'TrialSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrialsResponse$TrialSummaries' => 'A list of the summaries of your trials.
', ], ], 'TrialSummary' => [ 'base' => 'A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName
.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt
= EventTime
+ TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt
= EventTime
+ TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt
= EventTime
+ TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
TtlDuration
time unit.
TtlDuration
time value.
The job completion criteria.
', 'refs' => [ 'HyperParameterTuningJobConfig$TuningJobCompletionCriteria' => 'The tuning job\'s completion criteria.
', ], ], 'TuningJobStepMetaData' => [ 'base' => 'Metadata for a tuning step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TuningJob' => 'The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
', ], ], 'USD' => [ 'base' => 'Represents an amount of money in United States dollars.
', 'refs' => [ 'PublicWorkforceTaskPrice$AmountInUsd' => 'Defines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.
', ], ], 'UiConfig' => [ 'base' => 'Provided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn
or UiTemplateS3Uri
.
For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn
.
For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri
to specify the location of a worker task template in Amazon S3.
Information about the user interface that workers use to complete the labeling task.
', ], ], 'UiTemplate' => [ 'base' => 'The Liquid template for the worker user interface.
', 'refs' => [ 'CreateHumanTaskUiRequest$UiTemplate' => NULL, 'RenderUiTemplateRequest$UiTemplate' => 'A Template
object containing the worker UI template to render.
Container for user interface template information.
', 'refs' => [ 'DescribeHumanTaskUiResponse$UiTemplate' => NULL, ], ], 'Uid' => [ 'base' => NULL, 'refs' => [ 'CustomPosixUserConfig$Uid' => 'The POSIX user ID.
', ], ], 'UpdateActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateClusterRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateClusterResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointWeightsAndCapacitiesInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointWeightsAndCapacitiesOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceComponentInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceComponentOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceComponentRuntimeConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceComponentRuntimeConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringAlertRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringAlertResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'Url' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$ModelDataUrl' => 'The location of the model artifacts. For more information, see ContainerDefinition.
', 'ClarifyShapBaselineConfig$ShapBaselineUri' => 'The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri
should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in ModelDataUrl
.
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'InferenceComponentContainerSpecificationSummary$ArtifactUrl' => 'The Amazon S3 path where the model artifacts are stored.
', 'ModelPackageContainerDefinition$ModelDataUrl' => 'The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip
compressed tar archive (.tar.gz
suffix).
The model artifacts must be in an S3 bucket that is in the same region as the model package.
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip
compressed tar archive (.tar.gz
suffix).
The model artifacts must be in an S3 bucket that is in the same Amazon Web Services region as the algorithm.
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
', 'refs' => [ 'AssociationSummary$CreatedBy' => NULL, 'DescribeActionResponse$CreatedBy' => NULL, 'DescribeActionResponse$LastModifiedBy' => NULL, 'DescribeArtifactResponse$CreatedBy' => NULL, 'DescribeArtifactResponse$LastModifiedBy' => NULL, 'DescribeContextResponse$CreatedBy' => NULL, 'DescribeContextResponse$LastModifiedBy' => NULL, 'DescribeExperimentResponse$CreatedBy' => 'Who created the experiment.
', 'DescribeExperimentResponse$LastModifiedBy' => 'Who last modified the experiment.
', 'DescribeLineageGroupResponse$CreatedBy' => NULL, 'DescribeLineageGroupResponse$LastModifiedBy' => NULL, 'DescribeModelCardResponse$CreatedBy' => NULL, 'DescribeModelCardResponse$LastModifiedBy' => NULL, 'DescribeModelPackageGroupOutput$CreatedBy' => NULL, 'DescribeModelPackageOutput$CreatedBy' => NULL, 'DescribeModelPackageOutput$LastModifiedBy' => NULL, 'DescribePipelineExecutionResponse$CreatedBy' => NULL, 'DescribePipelineExecutionResponse$LastModifiedBy' => NULL, 'DescribePipelineResponse$CreatedBy' => NULL, 'DescribePipelineResponse$LastModifiedBy' => NULL, 'DescribeProjectOutput$CreatedBy' => NULL, 'DescribeProjectOutput$LastModifiedBy' => NULL, 'DescribeTrialComponentResponse$CreatedBy' => 'Who created the trial component.
', 'DescribeTrialComponentResponse$LastModifiedBy' => 'Who last modified the component.
', 'DescribeTrialResponse$CreatedBy' => 'Who created the trial.
', 'DescribeTrialResponse$LastModifiedBy' => 'Who last modified the trial.
', 'Experiment$CreatedBy' => 'Who created the experiment.
', 'Experiment$LastModifiedBy' => NULL, 'ModelCard$CreatedBy' => NULL, 'ModelCard$LastModifiedBy' => NULL, 'ModelDashboardModelCard$CreatedBy' => NULL, 'ModelDashboardModelCard$LastModifiedBy' => NULL, 'ModelPackage$CreatedBy' => 'Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
', 'ModelPackage$LastModifiedBy' => 'Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
', 'ModelPackageGroup$CreatedBy' => NULL, 'Pipeline$CreatedBy' => NULL, 'Pipeline$LastModifiedBy' => NULL, 'PipelineExecution$CreatedBy' => NULL, 'PipelineExecution$LastModifiedBy' => NULL, 'Project$CreatedBy' => 'Who created the project.
', 'Project$LastModifiedBy' => NULL, 'Trial$CreatedBy' => 'Who created the trial.
', 'Trial$LastModifiedBy' => NULL, 'TrialComponent$CreatedBy' => 'Who created the trial component.
', 'TrialComponent$LastModifiedBy' => NULL, 'TrialComponentSimpleSummary$CreatedBy' => NULL, 'TrialComponentSummary$CreatedBy' => 'Who created the trial component.
', 'TrialComponentSummary$LastModifiedBy' => 'Who last modified the component.
', ], ], 'UserProfileArn' => [ 'base' => NULL, 'refs' => [ 'CreateUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', 'DescribeUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', 'UpdateUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', ], ], 'UserProfileDetails' => [ 'base' => 'The user profile details.
', 'refs' => [ 'UserProfileList$member' => NULL, ], ], 'UserProfileList' => [ 'base' => NULL, 'refs' => [ 'ListUserProfilesResponse$UserProfiles' => 'The list of user profiles.
', ], ], 'UserProfileName' => [ 'base' => NULL, 'refs' => [ 'AppDetails$UserProfileName' => 'The user profile name.
', 'CreateAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName
must be set.
The name of the UserProfile to sign-in as.
', 'CreateUserProfileRequest$UserProfileName' => 'A name for the UserProfile. This value is not case sensitive.
', 'DeleteAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName
must be set.
The user profile name.
', 'DescribeAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName
must be set.
The user profile name.
', 'DescribeUserProfileRequest$UserProfileName' => 'The user profile name. This value is not case sensitive.
', 'DescribeUserProfileResponse$UserProfileName' => 'The user profile name.
', 'ListAppsRequest$UserProfileNameEquals' => 'A parameter to search by user profile name. If SpaceNameEquals
is set, then this value cannot be set.
A parameter by which to filter the results.
', 'OwnershipSettings$OwnerUserProfileName' => 'The user profile who is the owner of the private space.
', 'OwnershipSettingsSummary$OwnerUserProfileName' => 'The user profile who is the owner of the private space.
', 'UpdateUserProfileRequest$UserProfileName' => 'The user profile name.
', 'UserProfileDetails$UserProfileName' => 'The user profile name.
', ], ], 'UserProfileSortKey' => [ 'base' => NULL, 'refs' => [ 'ListUserProfilesRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
', ], ], 'UserProfileStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeUserProfileResponse$Status' => 'The status.
', 'UserProfileDetails$Status' => 'The status.
', ], ], 'UserSettings' => [ 'base' => 'A collection of settings that apply to users in a domain. These settings are specified when the CreateUserProfile
API is called, and as DefaultUserSettings
when the CreateDomain
API is called.
SecurityGroups
is aggregated when specified in both calls. For all other settings in UserSettings
, the values specified in CreateUserProfile
take precedence over those specified in CreateDomain
.
The default settings to use to create a user profile when UserSettings
isn\'t specified in the call to the CreateUserProfile
API.
SecurityGroups
is aggregated when specified in both calls. For all other settings in UserSettings
, the values specified in CreateUserProfile
take precedence over those specified in CreateDomain
.
A collection of settings.
', 'DescribeDomainResponse$DefaultUserSettings' => 'Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.
', 'DescribeUserProfileResponse$UserSettings' => 'A collection of settings.
', 'UpdateDomainRequest$DefaultUserSettings' => 'A collection of settings.
', 'UpdateUserProfileRequest$UserSettings' => 'A collection of settings.
', ], ], 'UsersPerStep' => [ 'base' => NULL, 'refs' => [ 'Stairs$UsersPerStep' => 'Specifies how many new users to spawn in each step.
', ], ], 'UtilizationMetric' => [ 'base' => NULL, 'refs' => [ 'RecommendationMetrics$CpuUtilization' => 'The expected CPU utilization at maximum invocations per minute for the instance.
NaN
indicates that the value is not available.
The expected memory utilization at maximum invocations per minute for the instance.
NaN
indicates that the value is not available.
The percentage of how much utilization you want an instance to use before autoscaling. The default value is 50%.
', 'GetScalingConfigurationRecommendationResponse$TargetCpuUtilizationPerCore' => 'The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the request. The default value is 50%.
', ], ], 'ValidationFraction' => [ 'base' => NULL, 'refs' => [ 'AutoMLDataSplitConfig$ValidationFraction' => 'The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.
', ], ], 'VariantName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceComponentInput$VariantName' => 'The name of an existing production variant where you host the inference component.
', 'DescribeInferenceComponentOutput$VariantName' => 'The name of the production variant that hosts the inference component.
', 'DesiredWeightAndCapacity$VariantName' => 'The name of the variant to update.
', 'InferenceComponentSummary$VariantName' => 'The name of the production variant that hosts the inference component.
', 'ListInferenceComponentsInput$VariantNameEquals' => 'A production variant name to filter the listed inference components. The response includes only those inference components that are hosted at the specified variant.
', 'PendingProductionVariantSummary$VariantName' => 'The name of the variant.
', 'ProductionVariant$VariantName' => 'The name of the production variant.
', 'ProductionVariantSummary$VariantName' => 'The name of the variant.
', ], ], 'VariantProperty' => [ 'base' => 'Specifies a production variant property type for an Endpoint.
If you are updating an endpoint with the RetainAllVariantProperties
option of UpdateEndpointInput set to true
, the VariantProperty
objects listed in the ExcludeRetainedVariantProperties
parameter of UpdateEndpointInput override the existing variant properties of the endpoint.
When you are updating endpoint resources with RetainAllVariantProperties
, whose value is set to true
, ExcludeRetainedVariantProperties
specifies the list of type VariantProperty to override with the values provided by EndpointConfig
. If you don\'t specify a value for ExcludeRetainedVariantProperties
, no variant properties are overridden.
The type of variant property. The supported values are:
DesiredInstanceCount
: Overrides the existing variant instance counts using the InitialInstanceCount
values in the ProductionVariants
of CreateEndpointConfig.
DesiredWeight
: Overrides the existing variant weights using the InitialVariantWeight
values in the ProductionVariants
of CreateEndpointConfig.
DataCaptureConfig
: (Not currently supported.)
The endpoint variant status which describes the current deployment stage status or operational status.
Creating
: Creating inference resources for the production variant.
Deleting
: Terminating inference resources for the production variant.
Updating
: Updating capacity for the production variant.
ActivatingTraffic
: Turning on traffic for the production variant.
Baking
: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
A message that describes the status of the production variant.
', ], ], 'VariantWeight' => [ 'base' => NULL, 'refs' => [ 'DesiredWeightAndCapacity$DesiredWeight' => 'The variant\'s weight.
', 'PendingProductionVariantSummary$CurrentWeight' => 'The weight associated with the variant.
', 'PendingProductionVariantSummary$DesiredWeight' => 'The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
', 'ProductionVariant$InitialVariantWeight' => 'Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight
to the sum of all VariantWeight
values across all ProductionVariants. If unspecified, it defaults to 1.0.
The weight associated with the variant.
', 'ProductionVariantSummary$DesiredWeight' => 'The requested weight, as specified in the UpdateEndpointWeightsAndCapacities
request.
Configuration for your vector collection type.
', 'refs' => [ 'CollectionConfig$VectorConfig' => 'Configuration for your vector collection type.
Dimension
: The number of elements in your vector.
The stability of the image version, specified by the maintainer.
NOT_PROVIDED
: The maintainers did not provide a status for image version stability.
STABLE
: The image version is stable.
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The stability of the image version specified by the maintainer.
NOT_PROVIDED
: The maintainers did not provide a status for image version stability.
STABLE
: The image version is stable.
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The availability of the image version specified by the maintainer.
NOT_PROVIDED
: The maintainers did not provide a status for image version stability.
STABLE
: The image version is stable.
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Version Id of the pipeline definition file. If not specified, Amazon SageMaker will retrieve the latest version.
', ], ], 'VersionedArnOrName' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to use to create the model.
', 'DeleteModelPackageInput$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to delete.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'DescribeModelPackageInput$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to describe.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', ], ], 'Vertex' => [ 'base' => 'A lineage entity connected to the starting entity(ies).
', 'refs' => [ 'Vertices$member' => NULL, ], ], 'Vertices' => [ 'base' => NULL, 'refs' => [ 'QueryLineageResponse$Vertices' => 'A list of vertices connected to the start entity(ies) in the lineage graph.
', ], ], 'VisibilityConditions' => [ 'base' => 'The list of key-value pairs that you specify for your resources.
', 'refs' => [ 'VisibilityConditionsList$member' => NULL, ], ], 'VisibilityConditionsKey' => [ 'base' => NULL, 'refs' => [ 'VisibilityConditions$Key' => 'The key for that specifies the tag that you\'re using to filter the search results. The key must start with Tags.
.
Limits the results of your search request to the resources that you can access.
', ], ], 'VisibilityConditionsValue' => [ 'base' => NULL, 'refs' => [ 'VisibilityConditions$Value' => 'The value for the tag that you\'re using to filter the search results.
', ], ], 'VolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningInstanceConfig$VolumeSizeInGB' => 'The volume size in GB of the data to be processed for hyperparameter optimization (optional).
', 'ResourceConfig$VolumeSizeInGB' => 'The size of the ML storage volume that you want to provision.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose File
as the TrainingInputMode
in the algorithm specification.
When using an ML instance with NVMe SSD volumes, SageMaker doesn\'t provision Amazon EBS General Purpose SSD (gp2) storage. Available storage is fixed to the NVMe-type instance\'s storage capacity. SageMaker configures storage paths for training datasets, checkpoints, model artifacts, and outputs to use the entire capacity of the instance storage. For example, ML instance families with the NVMe-type instance storage include ml.p4d
, ml.g4dn
, and ml.g5
.
When using an ML instance with the EBS-only storage option and without instance storage, you must define the size of EBS volume through VolumeSizeInGB
in the ResourceConfig
API. For example, ML instance families that use EBS volumes include ml.c5
and ml.p2
.
To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
To find the default local paths defined by the SageMaker training platform, see Amazon SageMaker Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and Outputs.
', ], ], 'VpcConfig' => [ 'base' => 'Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
', 'refs' => [ 'AutoMLSecurityConfig$VpcConfig' => 'The VPC configuration.
', 'CreateClusterRequest$VpcConfig' => NULL, 'CreateEndpointConfigInput$VpcConfig' => NULL, 'CreateModelInput$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. VpcConfig
is used in hosting services and in batch transform. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.
A VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'DescribeClusterResponse$VpcConfig' => NULL, 'DescribeEndpointConfigOutput$VpcConfig' => NULL, 'DescribeModelOutput$VpcConfig' => 'A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
', 'DescribeTrainingJobResponse$VpcConfig' => 'A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'HyperParameterTrainingJobDefinition$VpcConfig' => 'The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'LabelingJobResourceConfig$VpcConfig' => NULL, 'Model$VpcConfig' => NULL, 'MonitoringNetworkConfig$VpcConfig' => NULL, 'NetworkConfig$VpcConfig' => NULL, 'TrainingJob$VpcConfig' => 'A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', ], ], 'VpcId' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$VpcId' => 'The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
', 'DescribeDomainResponse$VpcId' => 'The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
', ], ], 'VpcOnlyTrustedAccounts' => [ 'base' => NULL, 'refs' => [ 'DockerSettings$VpcOnlyTrustedAccounts' => 'The list of Amazon Web Services accounts that are trusted when the domain is created in VPC-only mode.
', ], ], 'VpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'VpcConfig$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in the Subnets
field.
The length of the baking period, during which SageMaker monitors alarms for each batch on the new fleet.
', 'TrafficRoutingConfig$WaitIntervalInSeconds' => 'The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
', ], ], 'WarmPoolResourceStatus' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsRequest$WarmPoolStatusEquals' => 'A filter that retrieves only training jobs with a specific warm pool status.
', 'WarmPoolStatus$Status' => 'The status of the warm pool.
InUse
: The warm pool is in use for the training job.
Available
: The warm pool is available to reuse for a matching training job.
Reused
: The warm pool moved to a matching training job for reuse.
Terminated
: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds
.
Status and billing information about the warm pool.
', 'refs' => [ 'DescribeTrainingJobResponse$WarmPoolStatus' => 'The status of the warm pool associated with the training job.
', 'TrainingJobSummary$WarmPoolStatus' => 'The status of the warm pool associated with the training job.
', ], ], 'Workforce' => [ 'base' => 'A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'refs' => [ 'DescribeWorkforceResponse$Workforce' => 'A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'UpdateWorkforceResponse$Workforce' => 'A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'Workforces$member' => NULL, ], ], 'WorkforceArn' => [ 'base' => NULL, 'refs' => [ 'CreateWorkforceResponse$WorkforceArn' => 'The Amazon Resource Name (ARN) of the workforce.
', 'Workforce$WorkforceArn' => 'The Amazon Resource Name (ARN) of the private workforce.
', 'Workteam$WorkforceArn' => 'The Amazon Resource Name (ARN) of the workforce.
', ], ], 'WorkforceFailureReason' => [ 'base' => NULL, 'refs' => [ 'Workforce$FailureReason' => 'The reason your workforce failed.
', ], ], 'WorkforceName' => [ 'base' => NULL, 'refs' => [ 'CreateWorkforceRequest$WorkforceName' => 'The name of the private workforce.
', 'CreateWorkteamRequest$WorkforceName' => 'The name of the workforce.
', 'DeleteWorkforceRequest$WorkforceName' => 'The name of the workforce.
', 'DescribeWorkforceRequest$WorkforceName' => 'The name of the private workforce whose access you want to restrict. WorkforceName
is automatically set to default
when a workforce is created and cannot be modified.
A filter you can use to search for workforces using part of the workforce name.
', 'UpdateWorkforceRequest$WorkforceName' => 'The name of the private workforce that you want to update. You can find your workforce name by using the ListWorkforces operation.
', 'Workforce$WorkforceName' => 'The name of the private workforce.
', ], ], 'WorkforceSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'WorkforceSecurityGroupIds$member' => NULL, ], ], 'WorkforceSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', 'WorkforceVpcConfigResponse$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', ], ], 'WorkforceStatus' => [ 'base' => NULL, 'refs' => [ 'Workforce$Status' => 'The status of your workforce.
', ], ], 'WorkforceSubnetId' => [ 'base' => NULL, 'refs' => [ 'WorkforceSubnets$member' => NULL, ], ], 'WorkforceSubnets' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$Subnets' => 'The ID of the subnets in the VPC that you want to connect.
', 'WorkforceVpcConfigResponse$Subnets' => 'The ID of the subnets in the VPC that you want to connect.
', ], ], 'WorkforceVpcConfigRequest' => [ 'base' => 'The VPC object you use to create or update a workforce.
', 'refs' => [ 'CreateWorkforceRequest$WorkforceVpcConfig' => 'Use this parameter to configure a workforce using VPC.
', 'UpdateWorkforceRequest$WorkforceVpcConfig' => 'Use this parameter to update your VPC configuration for a workforce.
', ], ], 'WorkforceVpcConfigResponse' => [ 'base' => 'A VpcConfig object that specifies the VPC that you want your workforce to connect to.
', 'refs' => [ 'Workforce$WorkforceVpcConfig' => 'The configuration of a VPC workforce.
', ], ], 'WorkforceVpcEndpointId' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigResponse$VpcEndpointId' => 'The IDs for the VPC service endpoints of your VPC workforce when it is created and updated.
', ], ], 'WorkforceVpcId' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$VpcId' => 'The ID of the VPC that the workforce uses for communication.
', 'WorkforceVpcConfigResponse$VpcId' => 'The ID of the VPC that the workforce uses for communication.
', ], ], 'Workforces' => [ 'base' => NULL, 'refs' => [ 'ListWorkforcesResponse$Workforces' => 'A list containing information about your workforce.
', ], ], 'WorkspaceSettings' => [ 'base' => 'The workspace settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$WorkspaceSettings' => 'The workspace settings for the SageMaker Canvas application.
', ], ], 'Workteam' => [ 'base' => 'Provides details about a labeling work team.
', 'refs' => [ 'DescribeWorkteamResponse$Workteam' => 'A Workteam
instance that contains information about the work team.
A Workteam
object that describes the updated work team.
The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.
', 'DescribeSubscribedWorkteamRequest$WorkteamArn' => 'The Amazon Resource Name (ARN) of the subscribed work team to describe.
', 'HumanLoopConfig$WorkteamArn' => 'Amazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see Create and Manage Workforces.
', 'HumanTaskConfig$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.
', 'LabelingJobSummary$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team assigned to the job.
', 'ListLabelingJobsForWorkteamRequest$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team for which you want to see labeling jobs for.
', 'SubscribedWorkteam$WorkteamArn' => 'The Amazon Resource Name (ARN) of the vendor that you have subscribed.
', 'Workteam$WorkteamArn' => 'The Amazon Resource Name (ARN) that identifies the work team.
', ], ], 'WorkteamName' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$WorkteamName' => 'The name of the work team. Use this name to identify the work team.
', 'DeleteWorkteamRequest$WorkteamName' => 'The name of the work team to delete.
', 'DescribeWorkteamRequest$WorkteamName' => 'The name of the work team to return a description of.
', 'ListSubscribedWorkteamsRequest$NameContains' => 'A string in the work team name. This filter returns only work teams whose name contains the specified string.
', 'ListWorkteamsRequest$NameContains' => 'A string in the work team\'s name. This filter returns only work teams whose name contains the specified string.
', 'UpdateWorkteamRequest$WorkteamName' => 'The name of the work team to update.
', 'Workteam$WorkteamName' => 'The name of the work team.
', ], ], 'Workteams' => [ 'base' => NULL, 'refs' => [ 'ListWorkteamsResponse$Workteams' => 'An array of Workteam
objects, each describing a work team.