start_trained_model_export_job async ¶

async def start_trained_model_export_job(
    self,
    name: "capo_cleanroomsml.types.name_string.NameString",
    trained_model_arn: "capo_cleanroomsml.types.trained_model_arn.TrainedModelArn",
    membership_identifier: "capo_cleanroomsml.types.uuid.UUID",
    output_configuration: "capo_cleanroomsml.types.trained_model_export_output_configuration.TrainedModelExportOutputConfiguration",
    *,
    config_overrides: Optional[AsyncCleanRoomsMLClientConfig] = None,
    trained_model_version_identifier: Optional[
        "capo_cleanroomsml.types.uuid.UUID"
    ] = None,
    description: Optional[
        "capo_cleanroomsml.types.resource_description.ResourceDescription"
    ] = None,
) -> None:
    """<p>Provides the information necessary to start a trained model export job.</p>

    Args:
        name: <p>The name of the trained model export job.</p>
        trained_model_arn: <p>The Amazon Resource Name (ARN) of the trained model that you want to export.</p>
        trained_model_version_identifier: <p>The version identifier of the trained model to export. This specifies which version of the trained model should be exported to the specified destination.</p>
        membership_identifier: <p>The membership ID of the member that is receiving the exported trained model artifacts.</p>
        output_configuration: <p>The output configuration information for the trained model export job.</p>
        description: <p>The description of the trained model export job.</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.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_cleanroomsml.types.start_trained_model_export_job_request.StartTrainedModelExportJobRequest]",
    ) -> AsyncOperationResponse[None]:
        import capo_cleanroomsml._operations.aws_stark_control_service.start_trained_model_export_job

        (
            output,
            http_response,
        ) = await capo_cleanroomsml._operations.aws_stark_control_service.start_trained_model_export_job.async_start_trained_model_export_job(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartTrainedModelExportJob")
    )
    input_: capo_cleanroomsml.types.start_trained_model_export_job_request.StartTrainedModelExportJobRequest = {
        "name": name,
        "trained_model_arn": trained_model_arn,
        "membership_identifier": membership_identifier,
        "output_configuration": output_configuration,
    }
    if trained_model_version_identifier is not None:
        input_["trained_model_version_identifier"] = (
            trained_model_version_identifier
        )
    if description is not None:
        input_["description"] = description

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