Stops a batch transform job.
When Amazon SageMaker receives a StopTransformJob request, the status of the job changes to Stopping. After Amazon SageMaker stops the job, the status is set to Stopped. When you stop a batch transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
Parameters:
Raises:
Source code in docs_src/capo_sagemaker/_services/sage_maker.py
| def stop_transform_job(
self,
*,
config_overrides: Optional[SageMakerClientConfig] = None,
transform_job_name: Optional[
"capo_sagemaker.types.transform_job_name.TransformJobName"
] = None,
) -> None:
"""<p>Stops a batch transform job.</p> <p>When Amazon SageMaker receives a <code>StopTransformJob</code> request, the status of the job changes to <code>Stopping</code>. After Amazon SageMaker stops the job, the status is set to <code>Stopped</code>. When you stop a batch transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.</p>
Args:
transform_job_name: <p>The name of the batch transform job to stop.</p>
Raises:
capo_sagemaker.errors.resource_not_found.ResourceNotFound: <p>Resource being access is not found.</p>
capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_sagemaker.types.stop_transform_job_request.StopTransformJobRequest]",
) -> OperationResponse[None]:
import capo_sagemaker._operations.sage_maker.stop_transform_job
output, http_response = (
capo_sagemaker._operations.sage_maker.stop_transform_job.stop_transform_job(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("StopTransformJob")
)
input_: capo_sagemaker.types.stop_transform_job_request.StopTransformJobRequest = {}
if transform_job_name is not None:
input_["transform_job_name"] = transform_job_name
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|