feat: add UpdateDeploymentResourcePool method to DeploymentResourcePo…

…olService v1beta1

feat: add use_effective_order field to BleuSpec v1beta1
feat: add satisfies_pzs and satisfies_pzi fields to Model v1beta1
docs: update comments of AutoscalingSpec v1beta1
feat: add deploy_metadata to PublisherModel.Deploy v1beta1
feat: add satisfies_pzs and satisfies_pzi fields to Tensorboard v1beta1

COPYBARA_INTEGRATE_REVIEW=#4028 from googleapis:owl-bot-copy 6330787
PiperOrigin-RevId: 648506252

google/cloud/aiplatform_v1beta1/__init__.py

@@ -196,6 +196,7 @@
 from .types.deployment_resource_pool_service import (
  UpdateDeploymentResourcePoolOperationMetadata,
 )
+from .types.deployment_resource_pool_service import UpdateDeploymentResourcePoolRequest
 from .types.encryption_spec import EncryptionSpec
 from .types.endpoint import DeployedModel
 from .types.endpoint import Endpoint
@@ -1939,6 +1940,7 @@
  "UpdateDatasetRequest",
  "UpdateDatasetVersionRequest",
  "UpdateDeploymentResourcePoolOperationMetadata",
+ "UpdateDeploymentResourcePoolRequest",
  "UpdateEndpointRequest",
  "UpdateEntityTypeRequest",
  "UpdateExecutionRequest",

google/cloud/aiplatform_v1beta1/gapic_metadata.json

@@ -338,6 +338,11 @@
  "methods": [
  "query_deployed_models"
  ]
+ },
+ "UpdateDeploymentResourcePool": {
+ "methods": [
+ "update_deployment_resource_pool"
+ ]
  }
  }
  },
@@ -368,6 +373,11 @@
  "methods": [
  "query_deployed_models"
  ]
+ },
+ "UpdateDeploymentResourcePool": {
+ "methods": [
+ "update_deployment_resource_pool"
+ ]
  }
  }
  },
@@ -398,6 +408,11 @@
  "methods": [
  "query_deployed_models"
  ]
+ },
+ "UpdateDeploymentResourcePool": {
+ "methods": [
+ "update_deployment_resource_pool"
+ ]
  }
  }
  }

google/cloud/aiplatform_v1beta1/services/deployment_resource_pool_service/async_client.py

@@ -63,6 +63,7 @@
 from google.iam.v1 import policy_pb2 # type: ignore
 from google.longrunning import operations_pb2 # type: ignore
 from google.protobuf import empty_pb2 # type: ignore
+from google.protobuf import field_mask_pb2 # type: ignore
 from google.protobuf import timestamp_pb2 # type: ignore
 from .transports.base import DeploymentResourcePoolServiceTransport, DEFAULT_CLIENT_INFO
 from .transports.grpc_asyncio import DeploymentResourcePoolServiceGrpcAsyncIOTransport
@@ -718,6 +719,164 @@ async def sample_list_deployment_resource_pools():
  # Done; return the response.
  return response
 
+ async def update_deployment_resource_pool(
+ self,
+ request: Optional[
+ Union[
+ deployment_resource_pool_service.UpdateDeploymentResourcePoolRequest,
+ dict,
+ ]
+ ] = None,
+ *,
+ deployment_resource_pool: Optional[
+ gca_deployment_resource_pool.DeploymentResourcePool
+ ] = None,
+ update_mask: Optional[field_mask_pb2.FieldMask] = None,
+ retry: OptionalRetry = gapic_v1.method.DEFAULT,
+ timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+ metadata: Sequence[Tuple[str, str]] = (),
+ ) -> operation_async.AsyncOperation:
+ r"""Update a DeploymentResourcePool.
+
+ .. code-block:: python
+
+ # This snippet has been automatically generated and should be regarded as a
+ # code template only.
+ # It will require modifications to work:
+ # - It may require correct/in-range values for request initialization.
+ # - It may require specifying regional endpoints when creating the service
+ # client as shown in:
+ # https://googleapis.dev/python/google-api-core/latest/client_options.html
+ from google.cloud import aiplatform_v1beta1
+
+ async def sample_update_deployment_resource_pool():
+ # Create a client
+ client = aiplatform_v1beta1.DeploymentResourcePoolServiceAsyncClient()
+
+ # Initialize request argument(s)
+ deployment_resource_pool = aiplatform_v1beta1.DeploymentResourcePool()
+ deployment_resource_pool.dedicated_resources.min_replica_count = 1803
+
+ request = aiplatform_v1beta1.UpdateDeploymentResourcePoolRequest(
+ deployment_resource_pool=deployment_resource_pool,
+ )
+
+ # Make the request
+ operation = client.update_deployment_resource_pool(request=request)
+
+ print("Waiting for operation to complete...")
+
+ response = (await operation).result()
+
+ # Handle the response
+ print(response)
+
+ Args:
+ request (Optional[Union[google.cloud.aiplatform_v1beta1.types.UpdateDeploymentResourcePoolRequest, dict]]):
+ The request object. Request message for
+ UpdateDeploymentResourcePool method.
+ deployment_resource_pool (:class:`google.cloud.aiplatform_v1beta1.types.DeploymentResourcePool`):
+ Required. The DeploymentResourcePool to update.
+
+ The DeploymentResourcePool's ``name`` field is used to
+ identify the DeploymentResourcePool to update. Format:
+ ``projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}``
+
+ This corresponds to the ``deployment_resource_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 list of fields to
+ update.
+
+ 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_async.AsyncRetry): 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.DeploymentResourcePool` A description of resources that can be shared by multiple DeployedModels,
+ whose underlying specification consists of a
+ DedicatedResources.
+
+ """
+ # 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([deployment_resource_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."
+ )
+
+ # - Use the request object if provided (there's no risk of modifying the input as
+ # there are no flattened fields), or create one.
+ if not isinstance(
+ request,
+ deployment_resource_pool_service.UpdateDeploymentResourcePoolRequest,
+ ):
+ request = (
+ deployment_resource_pool_service.UpdateDeploymentResourcePoolRequest(
+ request
+ )
+ )
+
+ # If we have keyword arguments corresponding to fields on the
+ # request, apply these.
+ if deployment_resource_pool is not None:
+ request.deployment_resource_pool = deployment_resource_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._client._transport._wrapped_methods[
+ self._client._transport.update_deployment_resource_pool
+ ]
+
+ # Certain fields should be provided within the metadata header;
+ # add these here.
+ metadata = tuple(metadata) + (
+ gapic_v1.routing_header.to_grpc_metadata(
+ (
+ (
+ "deployment_resource_pool.name",
+ request.deployment_resource_pool.name,
+ ),
+ )
+ ),
+ )
+
+ # Validate the universe domain.
+ self._client._validate_universe_domain()
+
+ # 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_deployment_resource_pool.DeploymentResourcePool,
+ metadata_type=deployment_resource_pool_service.UpdateDeploymentResourcePoolOperationMetadata,
+ )
+
+ # Done; return the response.
+ return response
+
  async def delete_deployment_resource_pool(
  self,
  request: Optional[

google/cloud/aiplatform_v1beta1/services/deployment_resource_pool_service/client.py

@@ -67,6 +67,7 @@
 from google.iam.v1 import policy_pb2 # type: ignore
 from google.longrunning import operations_pb2 # type: ignore
 from google.protobuf import empty_pb2 # type: ignore
+from google.protobuf import field_mask_pb2 # type: ignore
 from google.protobuf import timestamp_pb2 # type: ignore
 from .transports.base import DeploymentResourcePoolServiceTransport, DEFAULT_CLIENT_INFO
 from .transports.grpc import DeploymentResourcePoolServiceGrpcTransport
@@ -1172,6 +1173,163 @@ def sample_list_deployment_resource_pools():
  # Done; return the response.
  return response
 
+ def update_deployment_resource_pool(
+ self,
+ request: Optional[
+ Union[
+ deployment_resource_pool_service.UpdateDeploymentResourcePoolRequest,
+ dict,
+ ]
+ ] = None,
+ *,
+ deployment_resource_pool: Optional[
+ gca_deployment_resource_pool.DeploymentResourcePool
+ ] = None,
+ update_mask: Optional[field_mask_pb2.FieldMask] = None,
+ retry: OptionalRetry = gapic_v1.method.DEFAULT,
+ timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+ metadata: Sequence[Tuple[str, str]] = (),
+ ) -> gac_operation.Operation:
+ r"""Update a DeploymentResourcePool.
+
+ .. code-block:: python
+
+ # This snippet has been automatically generated and should be regarded as a
+ # code template only.
+ # It will require modifications to work:
+ # - It may require correct/in-range values for request initialization.
+ # - It may require specifying regional endpoints when creating the service
+ # client as shown in:
+ # https://googleapis.dev/python/google-api-core/latest/client_options.html
+ from google.cloud import aiplatform_v1beta1
+
+ def sample_update_deployment_resource_pool():
+ # Create a client
+ client = aiplatform_v1beta1.DeploymentResourcePoolServiceClient()
+
+ # Initialize request argument(s)
+ deployment_resource_pool = aiplatform_v1beta1.DeploymentResourcePool()
+ deployment_resource_pool.dedicated_resources.min_replica_count = 1803
+
+ request = aiplatform_v1beta1.UpdateDeploymentResourcePoolRequest(
+ deployment_resource_pool=deployment_resource_pool,
+ )
+
+ # Make the request
+ operation = client.update_deployment_resource_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.UpdateDeploymentResourcePoolRequest, dict]):
+ The request object. Request message for
+ UpdateDeploymentResourcePool method.
+ deployment_resource_pool (google.cloud.aiplatform_v1beta1.types.DeploymentResourcePool):
+ Required. The DeploymentResourcePool to update.
+
+ The DeploymentResourcePool's ``name`` field is used to
+ identify the DeploymentResourcePool to update. Format:
+ ``projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}``
+
+ This corresponds to the ``deployment_resource_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 list of fields to
+ update.
+
+ 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.DeploymentResourcePool` A description of resources that can be shared by multiple DeployedModels,
+ whose underlying specification consists of a
+ DedicatedResources.
+
+ """
+ # 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([deployment_resource_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."
+ )
+
+ # - Use the request object if provided (there's no risk of modifying the input as
+ # there are no flattened fields), or create one.
+ if not isinstance(
+ request,
+ deployment_resource_pool_service.UpdateDeploymentResourcePoolRequest,
+ ):
+ request = (
+ deployment_resource_pool_service.UpdateDeploymentResourcePoolRequest(
+ request
+ )
+ )
+ # If we have keyword arguments corresponding to fields on the
+ # request, apply these.
+ if deployment_resource_pool is not None:
+ request.deployment_resource_pool = deployment_resource_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_deployment_resource_pool
+ ]
+
+ # Certain fields should be provided within the metadata header;
+ # add these here.
+ metadata = tuple(metadata) + (
+ gapic_v1.routing_header.to_grpc_metadata(
+ (
+ (
+ "deployment_resource_pool.name",
+ request.deployment_resource_pool.name,
+ ),
+ )
+ ),
+ )
+
+ # Validate the universe domain.
+ self._validate_universe_domain()
+
+ # 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_deployment_resource_pool.DeploymentResourcePool,
+ metadata_type=deployment_resource_pool_service.UpdateDeploymentResourcePoolOperationMetadata,
+ )
+
+ # Done; return the response.
+ return response
+
  def delete_deployment_resource_pool(
  self,
  request: Optional[