start_ml_evaluation_task_run async ¶

async def start_ml_evaluation_task_run(
    self,
    transform_id: "capo_glue.types.hash_string.HashString",
    *,
    config_overrides: Optional[AsyncGlueClientConfig] = None,
) -> "capo_glue.types.start_ml_evaluation_task_run_response.StartMLEvaluationTaskRunResponse":
    """<p>Starts a task to estimate the quality of the transform. </p> <p>When you provide label sets as examples of truth, Glue machine learning uses some of those examples to learn from them. The rest of the labels are used as a test to estimate quality.</p> <p>Returns a unique identifier for the run. You can call <code>GetMLTaskRun</code> to get more information about the stats of the <code>EvaluationTaskRun</code>.</p>

    Args:
        transform_id: <p>The unique identifier of the machine learning transform.</p>

    Raises:
        capo_glue.errors.concurrent_runs_exceeded_exception.ConcurrentRunsExceededException: <p>Too many jobs are being run concurrently.</p>
        capo_glue.errors.entity_not_found_exception.EntityNotFoundException: <p>A specified entity does not exist</p>
        capo_glue.errors.internal_service_exception.InternalServiceException: <p>An internal service error occurred.</p>
        capo_glue.errors.invalid_input_exception.InvalidInputException: <p>The input provided was not valid.</p>
        capo_glue.errors.ml_transform_not_ready_exception.MLTransformNotReadyException: <p>The machine learning transform is not ready to run.</p>
        capo_glue.errors.operation_timeout_exception.OperationTimeoutException: <p>The operation timed out.</p>
        capo_glue.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_glue.types.start_ml_evaluation_task_run_request.StartMLEvaluationTaskRunRequest]",
    ) -> AsyncOperationResponse[
        "capo_glue.types.start_ml_evaluation_task_run_response.StartMLEvaluationTaskRunResponse"
    ]:
        import capo_glue._operations.aws_glue.start_ml_evaluation_task_run

        (
            output,
            http_response,
        ) = await capo_glue._operations.aws_glue.start_ml_evaluation_task_run.async_start_ml_evaluation_task_run(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartMLEvaluationTaskRun")
    )
    input_: capo_glue.types.start_ml_evaluation_task_run_request.StartMLEvaluationTaskRunRequest = {
        "transform_id": transform_id
    }

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output