cancel_trained_model_inference_job ¶

cancel_trained_model_inference_job(
    membership_identifier: UUID,
    trained_model_inference_job_arn: TrainedModelInferenceJobArn,
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
) -> None

Submits a request to cancel a trained model inference job.

Parameters:

membership_identifier (UUID) –

The membership ID of the trained model inference job that you want to cancel.
trained_model_inference_job_arn (TrainedModelInferenceJobArn) –

The Amazon Resource Name (ARN) of the trained model inference job that you want to cancel.

Raises:

AccessDeniedException –

You do not have sufficient access to perform this action.
ConflictException –

You can't complete this action because another resource depends on this resource.
ResourceNotFoundException –

The resource you are requesting does not exist.
ThrottlingException –

The request was denied due to request throttling.
ValidationException –

The request parameters for this request are incorrect.
UnknownServiceError –

The service returned an error code this client does not model.

Source code in docs_src/capo_cleanroomsml/_services/clean_rooms_ml.py

def cancel_trained_model_inference_job(
    self,
    membership_identifier: "capo_cleanroomsml.types.uuid.UUID",
    trained_model_inference_job_arn: "capo_cleanroomsml.types.trained_model_inference_job_arn.TrainedModelInferenceJobArn",
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
) -> None:
    """<p>Submits a request to cancel a trained model inference job.</p>

    Args:
        membership_identifier: <p>The membership ID of the trained model inference job that you want to cancel.</p>
        trained_model_inference_job_arn: <p>The Amazon Resource Name (ARN) of the trained model inference job that you want to cancel.</p>

    Raises:
        capo_cleanroomsml.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_cleanroomsml.errors.conflict_exception.ConflictException: <p>You can't complete this action because another resource depends on this resource.</p>
        capo_cleanroomsml.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource you are requesting does not exist.</p>
        capo_cleanroomsml.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_cleanroomsml.errors.validation_exception.ValidationException: <p>The request parameters for this request are incorrect.</p>
        capo_cleanroomsml.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_cleanroomsml.types.cancel_trained_model_inference_job_request.CancelTrainedModelInferenceJobRequest]",
    ) -> OperationResponse[None]:
        import capo_cleanroomsml._operations.aws_stark_control_service.cancel_trained_model_inference_job

        output, http_response = (
            capo_cleanroomsml._operations.aws_stark_control_service.cancel_trained_model_inference_job.cancel_trained_model_inference_job(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CancelTrainedModelInferenceJob")
    )
    input_: capo_cleanroomsml.types.cancel_trained_model_inference_job_request.CancelTrainedModelInferenceJobRequest = {
        "membership_identifier": membership_identifier,
        "trained_model_inference_job_arn": trained_model_inference_job_arn,
    }

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output