list_trained_model_inference_jobs ¶

def list_trained_model_inference_jobs(
    self,
    membership_identifier: "capo_cleanroomsml.types.uuid.UUID",
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
    next_token: Optional["capo_cleanroomsml.types.next_token.NextToken"] = None,
    max_results: Optional["capo_cleanroomsml.types.max_results.MaxResults"] = None,
    trained_model_arn: Optional[
        "capo_cleanroomsml.types.trained_model_arn.TrainedModelArn"
    ] = None,
    trained_model_version_identifier: Optional[
        "capo_cleanroomsml.types.uuid.UUID"
    ] = None,
) -> "capo_cleanroomsml.types.list_trained_model_inference_jobs_response.ListTrainedModelInferenceJobsResponse":
    """<p>Returns a list of trained model inference jobs that match the request parameters.</p>

    Args:
        next_token: <p>The token value retrieved from a previous call to access the next page of results.</p>
        max_results: <p>The maximum size of the results that is returned per call.</p>
        membership_identifier: <p>The membership </p>
        trained_model_arn: <p>The Amazon Resource Name (ARN) of a trained model that was used to create the trained model inference jobs that you are interested in.</p>
        trained_model_version_identifier: <p>The version identifier of the trained model to filter inference jobs by. When specified, only inference jobs that used this specific version of the trained model are returned.</p>

    Raises:
        capo_cleanroomsml.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</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.list_trained_model_inference_jobs_request.ListTrainedModelInferenceJobsRequest]",
    ) -> OperationResponse[
        "capo_cleanroomsml.types.list_trained_model_inference_jobs_response.ListTrainedModelInferenceJobsResponse"
    ]:
        import capo_cleanroomsml._operations.aws_stark_control_service.list_trained_model_inference_jobs

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListTrainedModelInferenceJobs")
    )
    input_: capo_cleanroomsml.types.list_trained_model_inference_jobs_request.ListTrainedModelInferenceJobsRequest = {
        "membership_identifier": membership_identifier
    }
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results
    if trained_model_arn is not None:
        input_["trained_model_arn"] = trained_model_arn
    if trained_model_version_identifier is not None:
        input_["trained_model_version_identifier"] = (
            trained_model_version_identifier
        )

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