# BatchTransformInputProperty

Input object for the batch transform job.

- 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 batchTransformInputProperty: sagemaker.CfnModelExplainabilityJobDefinition.BatchTransformInputProperty = {
  dataCapturedDestinationS3Uri: 'dataCapturedDestinationS3Uri',
  datasetFormat: {
    csv: {
      header: false,
    },
    json: {
      line: false,
    },
    parquet: false,
  },
  localPath: 'localPath',

  // the properties below are optional
  featuresAttribute: 'featuresAttribute',
  inferenceAttribute: 'inferenceAttribute',
  probabilityAttribute: 'probabilityAttribute',
  s3DataDistributionType: 's3DataDistributionType',
  s3InputMode: 's3InputMode',
};
```

## Properties

- `dataCapturedDestinationS3Uri`: string (required) — The Amazon S3 location being used to capture the data.

- `datasetFormat`: [IResolvable](/cdk/api/v2/docs/aws-cdk-lib.IResolvable.html) | [CfnModelExplainabilityJobDefinition.DatasetFormatProperty](/cdk/api/v2/docs/aws-cdk-lib.aws_sagemaker.CfnModelExplainabilityJobDefinition.DatasetFormatProperty.html) (required) — The dataset format for your batch transform job.

- `featuresAttribute`: string — The attributes of the input data that are the input features.

- `inferenceAttribute`: string — The attribute of the input data that represents the ground truth label.

- `localPath`: string (required) — Path to the filesystem where the batch transform data is available to the container.

- `probabilityAttribute`: string — In a classification problem, the attribute that represents the class probability.

- `s3DataDistributionType`: string — Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key.

  Defaults to `FullyReplicated`

- `s3InputMode`: string — Whether the `Pipe` or `File` is used as the input mode for transferring data for the monitoring job.

  `Pipe` mode is recommended for large datasets. `File` mode is useful for small files that fit in memory. Defaults to `File` .