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Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
To perform batch transformations, you create a transform job and use the data that you have readily available.
In the request body, you provide the following:
TransformJobName - Identifies the transform job. The name must be unique within
an Amazon Web Services Region in an Amazon Web Services account.
ModelName - Identifies the model to use. ModelName must be the name
of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon
Web Services account. For information on creating a model, see CreateModel.
TransformInput - Describes the dataset to be transformed and the Amazon S3
location where it is stored.
TransformOutput - Identifies the Amazon S3 location where you want Amazon
SageMaker to save the results from the transform job.
TransformResources - Identifies the ML compute instances for the transform
job.
For more information about how batch transformation works, see Batch Transform.
For .NET Core this operation is only available in asynchronous form. Please refer to CreateTransformJobAsync.
Namespace: Amazon.SageMaker
Assembly: AWSSDK.SageMaker.dll
Version: 3.x.y.z
public abstract CreateTransformJobResponse CreateTransformJob( CreateTransformJobRequest request )
Container for the necessary parameters to execute the CreateTransformJob service method.
| Exception | Condition |
|---|---|
| ResourceInUseException | Resource being accessed is in use. |
| ResourceLimitExceededException | You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. |
| ResourceNotFoundException | Resource being access is not found. |
.NET Framework:
Supported in: 4.5, 4.0, 3.5