get_ml_configuration ¶

def get_ml_configuration(
    self,
    membership_identifier: "capo_cleanroomsml.types.uuid.UUID",
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
) -> "capo_cleanroomsml.types.get_ml_configuration_response.GetMLConfigurationResponse":
    """<p>Returns information about a specific ML configuration.</p>

    Args:
        membership_identifier: <p>The membership ID of the member that owns the ML configuration you want to return information about.</p>

    Raises:
        capo_cleanroomsml.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</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.
    """

    def _handler(
        req: "OperationRequest[capo_cleanroomsml.types.get_ml_configuration_request.GetMLConfigurationRequest]",
    ) -> OperationResponse[
        "capo_cleanroomsml.types.get_ml_configuration_response.GetMLConfigurationResponse"
    ]:
        import capo_cleanroomsml._operations.aws_stark_control_service.get_ml_configuration

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetMLConfiguration")
    )
    input_: capo_cleanroomsml.types.get_ml_configuration_request.GetMLConfigurationRequest = {
        "membership_identifier": membership_identifier
    }

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