Smaws_Client_SageMaker.CreateTransformJobStarts 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 and AMI image versions for the transform job.For more information about how batch transformation works, see Batch Transform.
val error_to_string :
[ Smaws_Lib.Protocols.AwsJson.error
| `ResourceInUse of Types.resource_in_use
| `ResourceLimitExceeded of Types.resource_limit_exceeded
| `ResourceNotFound of Types.resource_not_found ] ->
stringval request :
'http_type Smaws_Lib.Context.t ->
Types.create_transform_job_request ->
(Types.create_transform_job_response,
[> Smaws_Lib.Protocols.AwsJson.error
| `ResourceInUse of Types.resource_in_use
| `ResourceLimitExceeded of Types.resource_limit_exceeded
| `ResourceNotFound of Types.resource_not_found ])
Stdlib.resultval request_with_metadata :
'http_type Smaws_Lib.Context.t ->
Types.create_transform_job_request ->
(Types.create_transform_job_response Smaws_Lib.Response.t,
[> Smaws_Lib.Protocols.AwsJson.error
| `ResourceInUse of Types.resource_in_use
| `ResourceLimitExceeded of Types.resource_limit_exceeded
| `ResourceNotFound of Types.resource_not_found ]
* Smaws_Lib.Response.metadata)
Stdlib.result