# TransformInputProperty

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

- Source: Generated code
- Type last changed: v2.93.0 · 23 Aug 2023

## Example

```ts
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import { aws_sagemaker as sagemaker } from 'aws-cdk-lib';
const transformInputProperty: sagemaker.CfnModelPackage.TransformInputProperty = {
  dataSource: {
    s3DataSource: {
      s3DataType: 's3DataType',
      s3Uri: 's3Uri',
    },
  },

  // the properties below are optional
  compressionType: 'compressionType',
  contentType: 'contentType',
  splitType: 'splitType',
};
```

## Properties

- `compressionType`: 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` .

- `contentType`: 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.

- `dataSource`: [IResolvable](/cdk/api/v2/docs/aws-cdk-lib.IResolvable.html) | [CfnModelPackage.DataSourceProperty](/cdk/api/v2/docs/aws-cdk-lib.aws_sagemaker.CfnModelPackage.DataSourceProperty.html) (required) — Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.

- `splitType`: 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.

  > 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://docs.aws.amazon.com/https://mxnet.apache.org/api/faq/recordio) in the MXNet documentation. For more information about `TFRecord` , see [Consuming TFRecord data](https://docs.aws.amazon.com/https://www.tensorflow.org/guide/data#consuming_tfrecord_data) in the TensorFlow documentation.