Class: Aws::SageMaker::Types::TransformInput
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::TransformInput
- Includes:
- Aws::Structure
- Defined in:
- lib/aws-sdk-sagemaker/types.rb
Overview
Describes the input source of a transform job and the way the transform job consumes it.
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#compression_type ⇒ String
If your transform data is compressed, specify the compression type.
-
#content_type ⇒ String
The multipurpose internet mail extension (MIME) type of the data.
-
#data_source ⇒ Types::TransformDataSource
Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
-
#split_type ⇒ String
The method to use to split the transform job’s data files into smaller batches.
Instance Attribute Details
#compression_type ⇒ String
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`.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 43661 class TransformInput < Struct.new( :data_source, :content_type, :compression_type, :split_type) SENSITIVE = [] include Aws::Structure end |
#content_type ⇒ String
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.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 43661 class TransformInput < Struct.new( :data_source, :content_type, :compression_type, :split_type) SENSITIVE = [] include Aws::Structure end |
#data_source ⇒ Types::TransformDataSource
Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 43661 class TransformInput < Struct.new( :data_source, :content_type, :compression_type, :split_type) SENSITIVE = [] include Aws::Structure end |
#split_type ⇒ String
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] in the MXNet documentation. For more information about ‘TFRecord`, see [Consuming TFRecord data] in the TensorFlow documentation.
</note>
[1]: mxnet.apache.org/api/faq/recordio [2]: www.tensorflow.org/guide/data#consuming_tfrecord_data
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# File 'lib/aws-sdk-sagemaker/types.rb', line 43661 class TransformInput < Struct.new( :data_source, :content_type, :compression_type, :split_type) SENSITIVE = [] include Aws::Structure end |