describe_inference_recommendations_job ¶

def describe_inference_recommendations_job(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    job_name: Optional[
        "capo_sagemaker.types.recommendation_job_name.RecommendationJobName"
    ] = None,
) -> "capo_sagemaker.types.describe_inference_recommendations_job_response.DescribeInferenceRecommendationsJobResponse":
    """<p>Provides the results of the Inference Recommender job. One or more recommendation jobs are returned.</p>

    Args:
        job_name: <p>The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.</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.describe_inference_recommendations_job_request.DescribeInferenceRecommendationsJobRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.describe_inference_recommendations_job_response.DescribeInferenceRecommendationsJobResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.describe_inference_recommendations_job

        output, http_response = (
            capo_sagemaker._operations.sage_maker.describe_inference_recommendations_job.describe_inference_recommendations_job(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DescribeInferenceRecommendationsJob")
    )
    input_: capo_sagemaker.types.describe_inference_recommendations_job_request.DescribeInferenceRecommendationsJobRequest = {}
    if job_name is not None:
        input_["job_name"] = job_name

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