describe_cluster_scheduler_config ¶

def describe_cluster_scheduler_config(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    cluster_scheduler_config_id: Optional[
        "capo_sagemaker.types.cluster_scheduler_config_id.ClusterSchedulerConfigId"
    ] = None,
    cluster_scheduler_config_version: Optional[
        "capo_sagemaker.types.integer.Integer"
    ] = None,
) -> "capo_sagemaker.types.describe_cluster_scheduler_config_response.DescribeClusterSchedulerConfigResponse":
    """<p>Description of the cluster policy. This policy is used for task prioritization and fair-share allocation. This helps prioritize critical workloads and distributes idle compute across entities.</p>

    Args:
        cluster_scheduler_config_id: <p>ID of the cluster policy.</p>
        cluster_scheduler_config_version: <p>Version of the cluster policy.</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_cluster_scheduler_config_request.DescribeClusterSchedulerConfigRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.describe_cluster_scheduler_config_response.DescribeClusterSchedulerConfigResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.describe_cluster_scheduler_config

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DescribeClusterSchedulerConfig")
    )
    input_: capo_sagemaker.types.describe_cluster_scheduler_config_request.DescribeClusterSchedulerConfigRequest = {}
    if cluster_scheduler_config_id is not None:
        input_["cluster_scheduler_config_id"] = cluster_scheduler_config_id
    if cluster_scheduler_config_version is not None:
        input_["cluster_scheduler_config_version"] = (
            cluster_scheduler_config_version
        )

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