# TransformInput
<a name="API_TransformInput"></a>

Describes the input source of a transform job and the way the transform job consumes it.

## Contents
<a name="API_TransformInput_Contents"></a>

 ** DataSource **   <a name="sagemaker-Type-TransformInput-DataSource"></a>
Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.  
Type: [TransformDataSource](API_TransformDataSource.md) object  
Required: Yes

 ** CompressionType **   <a name="sagemaker-Type-TransformInput-CompressionType"></a>
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`.  
Type: String  
Valid Values: `None | Gzip`   
Required: No

 ** ContentType **   <a name="sagemaker-Type-TransformInput-ContentType"></a>
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.  
Type: String  
Length Constraints: Minimum length of 0. Maximum length of 256.  
Pattern: `.*`   
Required: No

 ** SplitType **   <a name="sagemaker-Type-TransformInput-SplitType"></a>
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.  
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](https://mxnet.apache.org/api/faq/recordio) in the MXNet documentation. For more information about `TFRecord`, see [Consuming TFRecord data](https://www.tensorflow.org/guide/data#consuming_tfrecord_data) in the TensorFlow documentation.
Type: String  
Valid Values: `None | Line | RecordIO | TFRecord`   
Required: No

## See Also
<a name="API_TransformInput_SeeAlso"></a>

For more information about using this API in one of the language-specific AWS SDKs, see the following:
+  [AWS SDK for C\$1\$1](https://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/TransformInput) 
+  [AWS SDK for Java V2](https://docs.aws.amazon.com/goto/SdkForJavaV2/sagemaker-2017-07-24/TransformInput) 
+  [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/sagemaker-2017-07-24/TransformInput)