TransformInput ¶

class TransformInput(TypedDict, closed=True):
    data_source: NotRequired[
        "capo_sagemaker.types.transform_data_source.TransformDataSource"
    ]
    """<p>Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.</p>"""
    content_type: NotRequired["capo_sagemaker.types.content_type.ContentType"]
    """<p>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.</p>"""
    compression_type: NotRequired[
        "capo_sagemaker.types.compression_type.CompressionType"
    ]
    """<p>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 <code>None</code>.</p>"""
    split_type: NotRequired["capo_sagemaker.types.split_type.SplitType"]
    """<p>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 <code>SplitType</code> is <code>None</code>, 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 <code>Line</code> to split records on a newline character boundary. <code>SplitType</code> also supports a number of record-oriented binary data formats. Currently, the supported record formats are:</p> <ul> <li> <p>RecordIO</p> </li> <li> <p>TFRecord</p> </li> </ul> <p>When splitting is enabled, the size of a mini-batch depends on the values of the <code>BatchStrategy</code> and <code>MaxPayloadInMB</code> parameters. When the value of <code>BatchStrategy</code> is <code>MultiRecord</code>, Amazon SageMaker sends the maximum number of records in each request, up to the <code>MaxPayloadInMB</code> limit. If the value of <code>BatchStrategy</code> is <code>SingleRecord</code>, Amazon SageMaker sends individual records in each request.</p> <note> <p>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 <code>BatchStrategy</code> is set to <code>SingleRecord</code>. Padding is not removed if the value of <code>BatchStrategy</code> is set to <code>MultiRecord</code>.</p> <p>For more information about <code>RecordIO</code>, see <a href="https://mxnet.apache.org/api/faq/recordio">Create a Dataset Using RecordIO</a> in the MXNet documentation. For more information about <code>TFRecord</code>, see <a href="https://www.tensorflow.org/guide/data#consuming_tfrecord_data">Consuming TFRecord data</a> in the TensorFlow documentation.</p> </note>"""