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doc: Add description for parameters in TransformInput (#3817)
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src/sagemaker/inputs.py

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@@ -162,9 +162,68 @@ class CreateModelInput(object):
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@attr.s
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class TransformInput(object):
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"""Create a class containing all the parameters.
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"""Creates a class containing parameters for configuring input data for a batch tramsform job.
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It can be used when calling ``sagemaker.transformer.Transformer.transform()``
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Args:
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data (str): The S3 location of the input data that the model can consume.
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data_type (str): The data type for a batch transform job.
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(default: ``'S3Prefix'``)
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content_type (str): The multi-purpose internet email extension (MIME) type of the data.
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(default: None)
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compression_type (str): If your transform data is compressed, specify the compression type.
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Valid values: ``'Gzip'``, ``None``
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(default: None)
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split_type (str): The method to use to split the transform job's data files into smaller
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batches.
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Valid values: ``'Line'``, ``RecordIO``, ``'TFRecord'``, None
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(default: None)
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input_filter (str): A JSONPath expression for selecting a portion of the input data to pass
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to the algorithm. For example, you can use this parameter to exclude fields, such as an
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ID column, from the input. If you want SageMaker to pass the entire input dataset to the
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algorithm, accept the default value ``$``. For more information on batch transform data
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processing, input, join, and output, see
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`Associate Prediction Results with Input Records
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<https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html?>`_
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in the *Amazon SageMaker developer guide*.
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Example value: ``$``. For more information about valid values for this parameter, see
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`JSONPath Operators
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<https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators>`_
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in the *Amazon SageMaker developer guide*.
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(default: ``$``)
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output_filter (str): A JSONPath expression for selecting a portion of the joined dataset to
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save in the output file for a batch transform job. If you want SageMaker to store the
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entire input dataset in the output file, leave the default value, $. If you specify
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indexes that aren't within the dimension size of the joined dataset, you get an error.
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Example value: ``$``. For more information about valid values for this parameter, see
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`JSONPath Operators
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<https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators>`_
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in the *Amazon SageMaker developer guide*.
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(default: ``$``)
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join_source (str): Specifies the source of the data to join with the transformed data.
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The default value is ``None``, which specifies not to join the input with the
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transformed data. If you want the batch transform job to join the original input data
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with the transformed data, set to ``Input``.
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Valid values: ``None``, ``Input``
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(default: None)
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model_client_config (dict): Configures the timeout and maximum number of retries for
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processing a transform job invocation.
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* ``'InvocationsTimeoutInSeconds'`` (int) - The timeout value in seconds for an
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invocation request. The default value is 600.
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* ``'InvocationsMaxRetries'`` (int) - The maximum number of retries when invocation
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requests are failing.
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(default: ``{600,3}``)
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batch_data_capture_config (dict): The dict is an object of `BatchDataCaptureConfig
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<https://sagemaker.readthedocs.io/en/stable/api/utility/inputs.html#sagemaker.inputs.BatchDataCaptureConfig>`_
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and specifies configuration related to batch transform job
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for use with Amazon SageMaker Model Monitoring. For more information,
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see `Capture data from batch transform job
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<https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture-batch.html>`_
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in the *Amazon SageMaker developer guide*.
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(default: None)
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"""
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data: str = attr.ib()

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