def cancel_training_pipeline( self, request: pipeline_service.CancelTrainingPipelineRequest = None, *, name: str = None, retry: retries.Retry = gapic_v1.method.DEFAULT, timeout: float = None, metadata: Sequence[Tuple[str, str]] = (), ) -> None: r"""Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use ``PipelineService.GetTrainingPipeline`` or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a ``TrainingPipeline.error`` value with a ``google.rpc.Status.code`` of 1, corresponding to ``Code.CANCELLED``, and ``TrainingPipeline.state`` is set to ``CANCELLED``. Args: request (:class:`~.pipeline_service.CancelTrainingPipelineRequest`): The request object. Request message for ``PipelineService.CancelTrainingPipeline``. name (:class:`str`): Required. The name of the TrainingPipeline to cancel. Format: ``projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`` This corresponds to the ``name`` field on the ``request`` instance; if ``request`` is provided, this should not be set. retry (google.api_core.retry.Retry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, str]]): Strings which should be sent along with the request as metadata. """ # Create or coerce a protobuf request object. # Sanity check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([name]) if request is not None and has_flattened_params: raise ValueError("If the `request` argument is set, then none of " "the individual field arguments should be set.") # Minor optimization to avoid making a copy if the user passes # in a pipeline_service.CancelTrainingPipelineRequest. # There's no risk of modifying the input as we've already verified # there are no flattened fields. if not isinstance(request, pipeline_service.CancelTrainingPipelineRequest): request = pipeline_service.CancelTrainingPipelineRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[ self._transport.cancel_training_pipeline] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + (gapic_v1.routing_header.to_grpc_metadata( (("name", request.name), )), ) # Send the request. rpc( request, retry=retry, timeout=timeout, metadata=metadata, )
async def cancel_training_pipeline( self, request: pipeline_service.CancelTrainingPipelineRequest = None, *, name: str = None, retry: retries.Retry = gapic_v1.method.DEFAULT, timeout: float = None, metadata: Sequence[Tuple[str, str]] = (), ) -> None: r"""Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.GetTrainingPipeline] or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a [TrainingPipeline.error][google.cloud.aiplatform.v1beta1.TrainingPipeline.error] value with a [google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to ``Code.CANCELLED``, and [TrainingPipeline.state][google.cloud.aiplatform.v1beta1.TrainingPipeline.state] is set to ``CANCELLED``. Args: request (:class:`google.cloud.aiplatform_v1beta1.types.CancelTrainingPipelineRequest`): The request object. Request message for [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.CancelTrainingPipeline]. name (:class:`str`): Required. The name of the TrainingPipeline to cancel. Format: ``projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}`` This corresponds to the ``name`` field on the ``request`` instance; if ``request`` is provided, this should not be set. retry (google.api_core.retry.Retry): Designation of what errors, if any, should be retried. timeout (float): The timeout for this request. metadata (Sequence[Tuple[str, str]]): Strings which should be sent along with the request as metadata. """ # Create or coerce a protobuf request object. # Sanity check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([name]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) request = pipeline_service.CancelTrainingPipelineRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = gapic_v1.method_async.wrap_method( self._client._transport.cancel_training_pipeline, default_timeout=5.0, client_info=DEFAULT_CLIENT_INFO, ) # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)), ) # Send the request. await rpc( request, retry=retry, timeout=timeout, metadata=metadata, )