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batch-score-rest.sh
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batch-score-rest.sh
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# <create_variables>
SUBSCRIPTION_ID=$(az account show --query id -o tsv)
RESOURCE_GROUP=$(az group show --query name -o tsv)
WORKSPACE=$(az configure -l --query "[?name=='workspace'].value" -o tsv)
LOCATION=$(az ml workspace show --query location -o tsv)
API_VERSION="2022-05-01"
TOKEN=$(az account get-access-token --query accessToken -o tsv)
#</create_variables>
# <set_endpoint_name>
export ENDPOINT_NAME=endpt-`echo $RANDOM`
# </set_endpoint_name>
echo "Using: SUBSCRIPTION_ID: $SUBSCRIPTION_ID LOCATION: $LOCATION RESOURCE_GROUP: $RESOURCE_GROUP WORKSPACE: $WORKSPACE ENDPOINT_NAME: $ENDPOINT_NAME"
# <define_wait>
wait_for_completion () {
operation_id=$1
access_token=$2
status="unknown"
while [[ $status != "Completed" && $status != "Succeeded" && $status != "Failed" && $status != "Canceled" ]]
do
echo "Getting operation status from: $operation_id"
operation_result=$(curl --location --request GET $operation_id --header "Authorization: Bearer $access_token")
# TODO error handling here
status=$(echo $operation_result | jq -r '.status')
if [[ -z $status || $status == "null" ]]
then
status=$(echo $operation_result | jq -r '.properties.status')
fi
# Fail early if job submission failed and there is nothing to poll on
if [[ -z $status || $status == "null" ]]
then
echo "No status found on operation, setting to failed."
status="Failed"
fi
echo "Current operation status: $status"
sleep 10
done
if [[ $status == "Failed" ]]
then
error=$(echo $operation_result | jq -r '.error')
echo "Error: $error"
fi
}
# </define_wait>
# <get_storage_details>
# Get values for storage account
response=$(curl --location --request GET "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/datastores?api-version=$API_VERSION&isDefault=true" \
--header "Authorization: Bearer $TOKEN")
DATASTORE_PATH=$(echo $response | jq -r '.value[0].id')
BLOB_URI_PROTOCOL=$(echo $response | jq -r '.value[0].properties.protocol')
BLOB_URI_ENDPOINT=$(echo $response | jq -r '.value[0].properties.endpoint')
AZUREML_DEFAULT_DATASTORE=$(echo $response | jq -r '.value[0].name')
AZUREML_DEFAULT_CONTAINER=$(echo $response | jq -r '.value[0].properties.containerName')
AZURE_STORAGE_ACCOUNT=$(echo $response | jq -r '.value[0].properties.accountName')
export AZURE_STORAGE_ACCOUNT $(echo $AZURE_STORAGE_ACCOUNT)
STORAGE_RESPONSE=$(echo az storage account show-connection-string --name $AZURE_STORAGE_ACCOUNT)
AZURE_STORAGE_CONNECTION_STRING=$($STORAGE_RESPONSE | jq -r '.connectionString')
BLOB_URI_ROOT="$BLOB_URI_PROTOCOL://$AZURE_STORAGE_ACCOUNT.blob.$BLOB_URI_ENDPOINT/$AZUREML_DEFAULT_CONTAINER"
# </get_storage_details>
# <upload_code>
az storage blob upload-batch -d $AZUREML_DEFAULT_CONTAINER/score -s endpoints/batch/mnist/code/ --connection-string $AZURE_STORAGE_CONNECTION_STRING
# </upload_code>
# <create_code>
response=$(curl --location --request PUT "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/codes/score-mnist/versions/1?api-version=$API_VERSION" \
--header "Authorization: Bearer $TOKEN" \
--header "Content-Type: application/json" \
--data-raw "{
\"properties\": {
\"description\": \"Score code\",
\"codeUri\": \"$BLOB_URI_ROOT/score\"
}
}")
# </create_code>
# <upload_model>
az storage blob upload-batch -d $AZUREML_DEFAULT_CONTAINER/model -s endpoints/batch/mnist/model --connection-string $AZURE_STORAGE_CONNECTION_STRING
# </upload_model>
# <create_model>
response=$(curl --location --request PUT "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/models/mnist/versions/1?api-version=$API_VERSION" \
--header "Authorization: Bearer $TOKEN" \
--header "Content-Type: application/json" \
--data-raw "{
\"properties\": {
\"modelUri\":\"azureml://subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/workspaces/$WORKSPACE/datastores/$AZUREML_DEFAULT_DATASTORE/paths/model\"
}
}")
# </create_model>
# <read_condafile>
CONDA_FILE=$(cat endpoints/batch/mnist/environment/conda.json | sed 's/"/\\"/g')
# </read_condafile>
# <create_environment>
ENV_VERSION=$RANDOM
response=$(curl --location --request PUT "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/environments/mnist-env/versions/$ENV_VERSION?api-version=$API_VERSION" \
--header "Authorization: Bearer $TOKEN" \
--header "Content-Type: application/json" \
--data-raw "{
\"properties\":{
\"condaFile\": $(echo \"$CONDA_FILE\"),
\"image\": \"mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04:latest\"
}
}")
# </create_environment>
# <create_compute>
response=$(curl --location --request PUT "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/computes/batch-cluster?api-version=$API_VERSION" \
--header "Authorization: Bearer $TOKEN" \
--header "Content-Type: application/json" \
--data-raw "{
\"properties\":{
\"computeType\": \"AmlCompute\",
\"properties\": {
\"osType\": \"Linux\",
\"vmSize\": \"STANDARD_D2_V2\",
\"scaleSettings\": {
\"maxNodeCount\": 5,
\"minNodeCount\": 0
},
\"remoteLoginPortPublicAccess\": \"NotSpecified\"
},
},
\"location\": \"$LOCATION\"
}")
# </create_compute>
#<create_endpoint>
response=$(curl --location --request PUT "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/batchEndpoints/$ENDPOINT_NAME?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN" \
--data-raw "{
\"properties\": {
\"authMode\": \"aadToken\"
},
\"location\": \"$LOCATION\"
}")
#</create_endpoint>
operation_id=$(echo $response | jq -r '.properties.properties.AzureAsyncOperationUri')
wait_for_completion $operation_id $TOKEN
# <create_deployment>
DEPLOYMENT_NAME="nonmlflowedp"
response=$(curl --location --request PUT "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/batchEndpoints/$ENDPOINT_NAME/deployments/$DEPLOYMENT_NAME?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN" \
--data-raw "{
\"location\": \"$LOCATION\",
\"properties\": {
\"model\": {
\"referenceType\": \"Id\",
\"assetId\": \"/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/models/mnist/versions/1\"
},
\"codeConfiguration\": {
\"codeId\": \"/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/codes/score-mnist/versions/1\",
\"scoringScript\": \"digit_identification.py\"
},
\"environmentId\": \"/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/environments/mnist-env/versions/$ENV_VERSION\",
\"compute\": \"/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/computes/batch-cluster\",
\"resources\": {
\"instanceCount\": 1
},
\"maxConcurrencyPerInstance\": \"4\",
\"retrySettings\": {
\"maxRetries\": 3,
\"timeout\": \"PT30S\"
},
\"errorThreshold\": \"10\",
\"loggingLevel\": \"info\",
\"miniBatchSize\": \"5\",
}
}")
#</create_deployment>
operation_id=$(echo $response | jq -r '.properties.properties.AzureAsyncOperationUri')
wait_for_completion $operation_id $TOKEN
#<set_endpoint_defaults>
response=$(curl --location --request PUT "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/batchEndpoints/$ENDPOINT_NAME?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN" \
--data-raw "{
\"properties\": {
\"authMode\": \"aadToken\",
\"defaults\": {
\"deploymentName\": \"$DEPLOYMENT_NAME\"
}
},
\"location\": \"$LOCATION\"
}")
operation_id=$(echo $response | jq -r '.properties.properties.AzureAsyncOperationUri')
wait_for_completion $operation_id $TOKEN
#</set_endpoint_defaults>
# <get_endpoint>
response=$(curl --location --request GET "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/batchEndpoints/$ENDPOINT_NAME?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN")
# <score_endpoint>
SCORING_URI=$(echo $response | jq -r '.properties.scoringUri')
# </get_endpoint>
# <get_access_token>
SCORING_TOKEN=$(az account get-access-token --resource https://ml.azure.com --query accessToken -o tsv)
# </get_access_token>
# <score_endpoint_with_data_in_cloud>
response=$(curl --location --request POST $SCORING_URI \
--header "Authorization: Bearer $SCORING_TOKEN" \
--header "Content-Type: application/json" \
--data-raw "{
\"properties\": {
\"dataset\": {
\"dataInputType\": \"DataUrl\",
\"Path\": \"https://azuremlexampledata.blob.core.windows.net/data/mnist/sample\"
}
}
}")
JOB_ID=$(echo $response | jq -r '.id')
JOB_ID_SUFFIX=$(echo ${JOB_ID##/*/})
# </score_endpoint_with_data_in_cloud>
# <check_job>
wait_for_completion $SCORING_URI/$JOB_ID_SUFFIX $SCORING_TOKEN
# </check_job>
#<create_dataset>
DATASET_NAME="mnist"
DATASET_VERSION=$RANDOM
response=$(curl --location --request PUT "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/datasets/$DATASET_NAME/versions/$DATASET_VERSION?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN" \
--data-raw "{
\"properties\": {
\"paths\": [
{
\"folder\": \"https://azuremlexampledata.blob.core.windows.net/data/mnist/sample\"
}
]
}
}")
#</create_dataset>
# <score_endpoint_with_dataset>
response=$(curl --location --request POST $SCORING_URI \
--header "Authorization: Bearer $SCORING_TOKEN" \
--header "Content-Type: application/json" \
--data-raw "{
\"properties\": {
\"InputData\": {
\"mnistinput\": {
\"JobInputType\": \"UriFolder\",
\"Uri\": \"azureml://locations/$LOCATION/workspaces/$WORKSPACE/data/$DATASET_NAME/versions/labels/latest\"
}
},
\"OutputData\": {
\"customOutput\": {
\"JobOutputType\": \"UriFolder\",
\"Uri\": \"azureml://datastores/workspaceblobstore/paths/batch/$ENDPOINT_NAME/$RANDOM/\"
}
},
}
}")
# </score_endpoint_with_dataset>
JOB_ID=$(echo $response | jq -r '.id')
JOB_ID_SUFFIX=$(echo ${JOB_ID##/*/})
# <check_job>
wait_for_completion $SCORING_URI/$JOB_ID_SUFFIX $SCORING_TOKEN
# </check_job>
# </score_endpoint>
# <delete_endpoint>
curl --location --request DELETE "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/batchEndpoints/$ENDPOINT_NAME?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN" || true
# </delete_endpoint>