def update_specialist_pool( self, request: specialist_pool_service. UpdateSpecialistPoolRequest = None, *, specialist_pool: gca_specialist_pool.SpecialistPool = None, update_mask: field_mask_pb2.FieldMask = None, retry: retries.Retry = gapic_v1.method.DEFAULT, timeout: float = None, metadata: Sequence[Tuple[str, str]] = (), ) -> gac_operation.Operation: r"""Updates a SpecialistPool. Args: request (google.cloud.aiplatform_v1beta1.types.UpdateSpecialistPoolRequest): The request object. Request message for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.UpdateSpecialistPool]. specialist_pool (google.cloud.aiplatform_v1beta1.types.SpecialistPool): Required. The SpecialistPool which replaces the resource on the server. This corresponds to the ``specialist_pool`` field on the ``request`` instance; if ``request`` is provided, this should not be set. update_mask (google.protobuf.field_mask_pb2.FieldMask): Required. The update mask applies to the resource. This corresponds to the ``update_mask`` 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. Returns: google.api_core.operation.Operation: An object representing a long-running operation. The result type for the operation will be :class:`google.cloud.aiplatform_v1beta1.types.SpecialistPool` SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers who are responsible for managing the labelers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and labelers work with the jobs using CrowdCompute console. """ # 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([specialist_pool, update_mask]) 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 specialist_pool_service.UpdateSpecialistPoolRequest. # There's no risk of modifying the input as we've already verified # there are no flattened fields. if not isinstance(request, specialist_pool_service.UpdateSpecialistPoolRequest): request = specialist_pool_service.UpdateSpecialistPoolRequest( request) # If we have keyword arguments corresponding to fields on the # request, apply these. if specialist_pool is not None: request.specialist_pool = specialist_pool if update_mask is not None: request.update_mask = update_mask # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[ self._transport.update_specialist_pool] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + (gapic_v1.routing_header.to_grpc_metadata( (("specialist_pool.name", request.specialist_pool.name), )), ) # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Wrap the response in an operation future. response = gac_operation.from_gapic( response, self._transport.operations_client, gca_specialist_pool.SpecialistPool, metadata_type=specialist_pool_service. UpdateSpecialistPoolOperationMetadata, ) # Done; return the response. return response
async def update_specialist_pool( self, request: Union[specialist_pool_service.UpdateSpecialistPoolRequest, dict] = None, *, specialist_pool: gca_specialist_pool.SpecialistPool = None, update_mask: field_mask_pb2.FieldMask = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: float = None, metadata: Sequence[Tuple[str, str]] = (), ) -> operation_async.AsyncOperation: r"""Updates a SpecialistPool. .. code-block:: from google.cloud import aiplatform_v1beta1 def sample_update_specialist_pool(): # Create a client client = aiplatform_v1beta1.SpecialistPoolServiceClient() # Initialize request argument(s) specialist_pool = aiplatform_v1beta1.SpecialistPool() specialist_pool.name = "name_value" specialist_pool.display_name = "display_name_value" request = aiplatform_v1beta1.UpdateSpecialistPoolRequest( specialist_pool=specialist_pool, ) # Make the request operation = client.update_specialist_pool(request=request) print("Waiting for operation to complete...") response = operation.result() # Handle the response print(response) Args: request (Union[google.cloud.aiplatform_v1beta1.types.UpdateSpecialistPoolRequest, dict]): The request object. Request message for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.UpdateSpecialistPool]. specialist_pool (:class:`google.cloud.aiplatform_v1beta1.types.SpecialistPool`): Required. The SpecialistPool which replaces the resource on the server. This corresponds to the ``specialist_pool`` field on the ``request`` instance; if ``request`` is provided, this should not be set. update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`): Required. The update mask applies to the resource. This corresponds to the ``update_mask`` 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. Returns: google.api_core.operation_async.AsyncOperation: An object representing a long-running operation. The result type for the operation will be :class:`google.cloud.aiplatform_v1beta1.types.SpecialistPool` SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console. """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([specialist_pool, update_mask]) 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 = specialist_pool_service.UpdateSpecialistPoolRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if specialist_pool is not None: request.specialist_pool = specialist_pool if update_mask is not None: request.update_mask = update_mask # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = gapic_v1.method_async.wrap_method( self._client._transport.update_specialist_pool, 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( (("specialist_pool.name", request.specialist_pool.name), )), ) # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Wrap the response in an operation future. response = operation_async.from_gapic( response, self._client._transport.operations_client, gca_specialist_pool.SpecialistPool, metadata_type=specialist_pool_service. UpdateSpecialistPoolOperationMetadata, ) # Done; return the response. return response