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openapi/paths/s3/getUserDatasetFileUploadPresignedPostObj.yaml
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,61 @@ | ||
| post: | ||
| summary: Get User Dataset file - Upload Presigned Post Object | ||
| description: API Endpoint to use S3 Presigned URLs to upload dataset files to S3 given the user ID, the data source, and the file name. | ||
| tags: | ||
| - s3 | ||
| requestBody: | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| required: | ||
| - uid | ||
| - data_source | ||
| - name | ||
| properties: | ||
| uid: | ||
| type: string | ||
| description: The unique user ID | ||
| data_source: | ||
| type: string | ||
| description: "What type of training was the user running (eg: TABULAR, PRETRAINED, OBJECT_DETECTION, IMAGE, etc)" | ||
| name: | ||
| type: string | ||
| description: The dataset file name | ||
| example: | ||
| uid: "1234" | ||
| data_source: "TABULAR" | ||
| file_name: "data.csv" | ||
| required: true | ||
| responses: | ||
| "200": | ||
| description: Presigned URLs fetched successfully | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| properties: | ||
| message: | ||
| type: string | ||
| example: "Presigned URL fetch successful" | ||
| presigned_post_obj: | ||
| type: string | ||
| example: "{'url': 'https://cloudberry-examples.s3.amazonaws.com/', | ||
| 'fields': { | ||
| 'key': 'uploads/image.jpg', | ||
| 'AWSAccessKeyId': 'AKIALGKOKBY37F5FZF4I', | ||
| 'policy': 'eyJleHBpcmF0aW9uIjogIjIwMTgtMDctMTNUMDI6Mzg6MTBaIiwgImNvbmRpdGlvbnMiOiBbWyJjb250ZW50LWxlbmd0aC1yYW5nZSIsIDEsIDEwNDg1NzldLCB7ImJ1Y2tldCI6ICJjbG91ZGJlcnJ5LWV4YW1wbGVzIn0sIHsia2V5IjogInVwbG9hZHMvaW1hZ2UuanBnIn1dfQ==', | ||
| 'signature': 'ZY7Orehfdzg+ToJJXhYuV/XyK5o='}}" | ||
|
|
||
| "400": | ||
| description: Presigned URL fetch didn't go through successfully. This is usually something wrong with your code | ||
| "401": | ||
| description: User is not authenticated | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| properties: | ||
| error: | ||
| type: string | ||
| example: "User is not authenticated" |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,132 @@ | ||
| post: | ||
| summary: Image Run | ||
| description: API Endpoint to train an image model via Pytorch. | ||
| tags: | ||
| - train | ||
| requestBody: | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| required: | ||
| - uid | ||
| - name | ||
| - dataset_data | ||
| - parameters_data | ||
| properties: | ||
| uid: | ||
| type: string | ||
| description: User ID | ||
| name: | ||
| type: string | ||
| description: Name of the trainspace | ||
| dataset_data: | ||
| type: object | ||
| description: DatasetData instance | ||
| example: | ||
| name: "data.csv" | ||
| is_default_dataset: false | ||
| properties: | ||
| name: | ||
| type: string | ||
| description: Name of the dataset file | ||
| is_default_dataset: | ||
| type: boolean | ||
| description: Whether the dataset is a built-in dataset | ||
| parameters_data: | ||
| type: object | ||
| properties: | ||
| problem_type: | ||
| type: string | ||
| description: Classification or Regression problem | ||
| criterion: | ||
| type: string | ||
| description: Loss function | ||
| optimizer_name: | ||
| type: string | ||
| description: What optimizer should the model use during gradient descent | ||
| example: "SGD" | ||
| shuffle: | ||
| type: boolean | ||
| description: Should the data be shuffled around before training? | ||
| epochs: | ||
| type: integer | ||
| description: How many epochs/iterations to run the model | ||
| test_size: | ||
| type: number | ||
| description: What percentage of your dataset should be dedicated for testing the performance of the model | ||
| batch_size: | ||
| type: integer | ||
| description: How big should each "batch" of the dataset be. This is for training in batch during the epoch | ||
| layers: | ||
| type: array | ||
| description: Architecture of Model | ||
| train_transform: | ||
| type: array | ||
| description: The image transformations you want to apply to the training data | ||
| test_transform: | ||
| type: array | ||
| description: The image transformations you want to apply to the testing data | ||
| required: | ||
| - problem_type | ||
| - criterion | ||
| - optimizer_name | ||
| - shuffle | ||
| - epochs | ||
| - test_size | ||
| - batch_size | ||
| - layers | ||
| - train_transform | ||
| - test_transform | ||
| example: | ||
| uid: "1234" | ||
| name: "My trainspace" | ||
| dataset_data: | ||
| name: "data.zip" | ||
| is_default_dataset: false | ||
| parameters_data: | ||
| problem_type: "classification" | ||
| criterion: "CELOSS" | ||
| optimizer_name: "ADAM" | ||
| shuffle: true | ||
| epochs: 10 | ||
| test_size: 0.2 | ||
| batch_size: 20 | ||
| layers: | ||
| [ | ||
| "nn.Conv2d(1, 5, 3, 1, 1)", | ||
| "nn.MaxPool2d(3, 1)", | ||
| "nn.Flatten()", | ||
| "nn.Linear(500, 10)", | ||
| "nn.Sigmoid()", | ||
| ] | ||
| train_transform: | ||
| [ | ||
| "torchvision.transforms.Grayscale()", | ||
| "torchvision.transforms.toTensor()", | ||
| "torchvision.transforms.Resize((32, 32))", | ||
| ] | ||
| required: true | ||
| responses: | ||
| "200": | ||
| description: Image DL model trained successfully. Shows the results page. | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| properties: | ||
| message: | ||
| type: string | ||
| example: "Training successful" | ||
| "400": | ||
| description: Error in training of model. Could come from problems with the user's request or on the server side. | ||
| "401": | ||
| description: User is not authenticated | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| properties: | ||
| error: | ||
| type: string | ||
| example: "User is not authenticated" |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,129 @@ | ||
| post: | ||
| summary: Tabular Run | ||
| description: API Endpoint to train a Deep Learning (DL) Model for tabular datasets. | ||
| tags: | ||
| - train | ||
| requestBody: | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| required: | ||
| - uid | ||
| - name | ||
| - dataset_data | ||
| - parameters_data | ||
| properties: | ||
| uid: | ||
| type: string | ||
| description: User ID | ||
| name: | ||
| type: string | ||
| description: Name of the trainspace | ||
| dataset_data: | ||
| type: object | ||
| description: DatasetData instance | ||
| example: | ||
| name: "data.csv" | ||
| is_default_dataset: false | ||
| properties: | ||
| name: | ||
| type: string | ||
| description: Name of the dataset file | ||
| is_default_dataset: | ||
| type: boolean | ||
| description: Whether the dataset is a built-in dataset | ||
| parameters_data: | ||
| type: object | ||
| properties: | ||
| target_col: | ||
| type: string | ||
| description: Target column to predict/classify | ||
| features: | ||
| type: array | ||
| description: Input columns to the model | ||
| items: | ||
| type: string | ||
| problem_type: | ||
| type: string | ||
| description: Classification or regression problem | ||
| criterion: | ||
| type: string | ||
| description: Loss function to use | ||
| optimizer_name: | ||
| type: string | ||
| description: What optimizer should the model use during gradient descent | ||
| example: "SGD" | ||
| shuffle: | ||
| type: boolean | ||
| description: Should the rows be shuffled or order be maintained? | ||
| epochs: | ||
| type: integer | ||
| description: How many epochs/iterations do we train model for | ||
| test_size: | ||
| type: number | ||
| description: What percentage of your dataset should be dedicated for testing the performance of the model | ||
| batch_size: | ||
| type: integer | ||
| description: How big should each "batch" of the dataset be. This is for training in batch during the epoch | ||
| layers: | ||
| type: array | ||
| description: Architecture of Model | ||
| required: | ||
| - target_col | ||
| - features | ||
| - problem_type | ||
| - criterion | ||
| - optimizer_name | ||
| - shuffle | ||
| - epochs | ||
| - test_size | ||
| - batch_size | ||
| - layers | ||
| example: | ||
| uid: "1234" | ||
| name: "My trainspace" | ||
| dataset_data: | ||
| name: "data.csv" | ||
| is_default_dataset: false | ||
| parameters_data: | ||
| target_col: "target" | ||
| features: ["col1", "col2", "col3"] | ||
| problem_type: "classification" | ||
| criterion: "CELOSS" | ||
| optimizer_name: "SGD" | ||
| shuffle: true | ||
| epochs: 10 | ||
| test_size: 0.2 | ||
| batch_size: 20 | ||
| layers: | ||
| [ | ||
| "nn.Linear(10, 3)", | ||
| "nn.ReLU()", | ||
| "nn.Linear(3, 10)", | ||
| "nn.Softmax(-1)", | ||
| ] | ||
| required: true | ||
| responses: | ||
| "200": | ||
| description: Training successful. Shows the results page. | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| properties: | ||
| message: | ||
| type: string | ||
| example: "Training successful" | ||
| "400": | ||
| description: Error in training of model. Could come from problems with the user's request or on the server side. | ||
| "401": | ||
| description: User is not authenticated | ||
| content: | ||
| application/json: | ||
| schema: | ||
| type: object | ||
| properties: | ||
| error: | ||
| type: string | ||
| example: "User is not authenticated" |
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