class Aws::SageMaker::Types::TransformInput
Describes the input source of a transform job and the way the transform job consumes it.
@note When making an API call, you may pass TransformInput
data as a hash: { data_source: { # required s3_data_source: { # required s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile s3_uri: "S3Uri", # required }, }, content_type: "ContentType", compression_type: "None", # accepts None, Gzip split_type: "None", # accepts None, Line, RecordIO, TFRecord }
@!attribute [rw] data_source
Describes the location of the channel data, which is, the S3 location of the input data that the model can consume. @return [Types::TransformDataSource]
@!attribute [rw] content_type
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. @return [String]
@!attribute [rw] compression_type
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`. @return [String]
@!attribute [rw] split_type
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. <note markdown="1"> 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][1] in the MXNet documentation. For more information about `TFRecord`, see [Consuming TFRecord data][2] in the TensorFlow documentation. </note> [1]: https://mxnet.apache.org/api/faq/recordio [2]: https://www.tensorflow.org/guide/data#consuming_tfrecord_data @return [String]
@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformInput AWS API Documentation
Constants
- SENSITIVE