delete_ai_workload_config async ¶

async def delete_ai_workload_config(
    self,
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
    ai_workload_config_name: Optional[
        "capo_sagemaker.types.ai_entity_name.AIEntityName"
    ] = None,
) -> "capo_sagemaker.types.delete_ai_workload_config_response.DeleteAIWorkloadConfigResponse":
    """<p>Deletes the specified AI workload configuration. You cannot delete a configuration that is referenced by an active benchmark job.</p>

    Args:
        ai_workload_config_name: <p>The name of the AI workload configuration to delete.</p>

    Raises:
        capo_sagemaker.errors.resource_in_use.ResourceInUse: <p>Resource being accessed is in use.</p>
        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.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_sagemaker.types.delete_ai_workload_config_request.DeleteAIWorkloadConfigRequest]",
    ) -> AsyncOperationResponse[
        "capo_sagemaker.types.delete_ai_workload_config_response.DeleteAIWorkloadConfigResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.delete_ai_workload_config

        (
            output,
            http_response,
        ) = await capo_sagemaker._operations.sage_maker.delete_ai_workload_config.async_delete_ai_workload_config(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteAIWorkloadConfig")
    )
    input_: capo_sagemaker.types.delete_ai_workload_config_request.DeleteAIWorkloadConfigRequest = {}
    if ai_workload_config_name is not None:
        input_["ai_workload_config_name"] = ai_workload_config_name

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