🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

google/cloud/aiplatform_v1/__init__.py

@@ -424,6 +424,9 @@
 from .types.model_service import ListModelVersionsRequest
 from .types.model_service import ListModelVersionsResponse
 from .types.model_service import MergeVersionAliasesRequest
+from .types.model_service import UpdateExplanationDatasetOperationMetadata
+from .types.model_service import UpdateExplanationDatasetRequest
+from .types.model_service import UpdateExplanationDatasetResponse
 from .types.model_service import UpdateModelRequest
 from .types.model_service import UploadModelOperationMetadata
 from .types.model_service import UploadModelRequest
@@ -1068,6 +1071,9 @@
     "UpdateEndpointRequest",
     "UpdateEntityTypeRequest",
     "UpdateExecutionRequest",
+    "UpdateExplanationDatasetOperationMetadata",
+    "UpdateExplanationDatasetRequest",
+    "UpdateExplanationDatasetResponse",
     "UpdateFeatureRequest",
     "UpdateFeaturestoreOperationMetadata",
     "UpdateFeaturestoreRequest",

google/cloud/aiplatform_v1/gapic_metadata.json

@@ -1549,6 +1549,11 @@
                 "merge_version_aliases"
               ]
             },
+            "UpdateExplanationDataset": {
+              "methods": [
+                "update_explanation_dataset"
+              ]
+            },
             "UpdateModel": {
               "methods": [
                 "update_model"
@@ -1639,6 +1644,11 @@
                 "merge_version_aliases"
               ]
             },
+            "UpdateExplanationDataset": {
+              "methods": [
+                "update_explanation_dataset"
+              ]
+            },
             "UpdateModel": {
               "methods": [
                 "update_model"

google/cloud/aiplatform_v1/services/migration_service/client.py

@@ -208,23 +208,18 @@ def parse_annotated_dataset_path(path: str) -> Dict[str, str]:
     @staticmethod
     def dataset_path(
         project: str,
-        location: str,
         dataset: str,
     ) -> str:
         """Returns a fully-qualified dataset string."""
-        return "projects/{project}/locations/{location}/datasets/{dataset}".format(
+        return "projects/{project}/datasets/{dataset}".format(
             project=project,
-            location=location,
             dataset=dataset,
         )
 
     @staticmethod
     def parse_dataset_path(path: str) -> Dict[str, str]:
         """Parses a dataset path into its component segments."""
-        m = re.match(
-            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/datasets/(?P<dataset>.+?)$",
-            path,
-        )
+        m = re.match(r"^projects/(?P<project>.+?)/datasets/(?P<dataset>.+?)$", path)
         return m.groupdict() if m else {}
 
     @staticmethod
@@ -252,18 +247,23 @@ def parse_dataset_path(path: str) -> Dict[str, str]:
     @staticmethod
     def dataset_path(
         project: str,
+        location: str,
         dataset: str,
     ) -> str:
         """Returns a fully-qualified dataset string."""
-        return "projects/{project}/datasets/{dataset}".format(
+        return "projects/{project}/locations/{location}/datasets/{dataset}".format(
             project=project,
+            location=location,
             dataset=dataset,
         )
 
     @staticmethod
     def parse_dataset_path(path: str) -> Dict[str, str]:
         """Parses a dataset path into its component segments."""
-        m = re.match(r"^projects/(?P<project>.+?)/datasets/(?P<dataset>.+?)$", path)
+        m = re.match(
+            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/datasets/(?P<dataset>.+?)$",
+            path,
+        )
         return m.groupdict() if m else {}
 
     @staticmethod

google/cloud/aiplatform_v1/services/model_service/async_client.py

@@ -856,6 +856,127 @@ async def sample_update_model():
         # Done; return the response.
         return response
 
+    async def update_explanation_dataset(
+        self,
+        request: Optional[
+            Union[model_service.UpdateExplanationDatasetRequest, dict]
+        ] = None,
+        *,
+        model: Optional[str] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> operation_async.AsyncOperation:
+        r"""Incrementally update the dataset used for an examples
+        model.
+
+        .. 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_v1
+
+            async def sample_update_explanation_dataset():
+                # Create a client
+                client = aiplatform_v1.ModelServiceAsyncClient()
+
+                # Initialize request argument(s)
+                request = aiplatform_v1.UpdateExplanationDatasetRequest(
+                    model="model_value",
+                )
+
+                # Make the request
+                operation = client.update_explanation_dataset(request=request)
+
+                print("Waiting for operation to complete...")
+
+                response = (await operation).result()
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Optional[Union[google.cloud.aiplatform_v1.types.UpdateExplanationDatasetRequest, dict]]):
+                The request object. Request message for
+                [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset].
+            model (:class:`str`):
+                Required. The resource name of the Model to update.
+                Format:
+                ``projects/{project}/locations/{location}/models/{model}``
+
+                This corresponds to the ``model`` 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_v1.types.UpdateExplanationDatasetResponse` Response message of
+                   [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset]
+                   operation.
+
+        """
+        # 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([model])
+        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 = model_service.UpdateExplanationDatasetRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if model is not None:
+            request.model = model
+
+        # 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_explanation_dataset,
+            default_timeout=None,
+            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((("model", request.model),)),
+        )
+
+        # 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,
+            model_service.UpdateExplanationDatasetResponse,
+            metadata_type=model_service.UpdateExplanationDatasetOperationMetadata,
+        )
+
+        # Done; return the response.
+        return response
+
     async def delete_model(
         self,
         request: Optional[Union[model_service.DeleteModelRequest, dict]] = None,

google/cloud/aiplatform_v1/services/model_service/client.py

@@ -1183,6 +1183,129 @@ def sample_update_model():
         # Done; return the response.
         return response
 
+    def update_explanation_dataset(
+        self,
+        request: Optional[
+            Union[model_service.UpdateExplanationDatasetRequest, dict]
+        ] = None,
+        *,
+        model: Optional[str] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> gac_operation.Operation:
+        r"""Incrementally update the dataset used for an examples
+        model.
+
+        .. 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_v1
+
+            def sample_update_explanation_dataset():
+                # Create a client
+                client = aiplatform_v1.ModelServiceClient()
+
+                # Initialize request argument(s)
+                request = aiplatform_v1.UpdateExplanationDatasetRequest(
+                    model="model_value",
+                )
+
+                # Make the request
+                operation = client.update_explanation_dataset(request=request)
+
+                print("Waiting for operation to complete...")
+
+                response = operation.result()
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Union[google.cloud.aiplatform_v1.types.UpdateExplanationDatasetRequest, dict]):
+                The request object. Request message for
+                [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset].
+            model (str):
+                Required. The resource name of the Model to update.
+                Format:
+                ``projects/{project}/locations/{location}/models/{model}``
+
+                This corresponds to the ``model`` 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_v1.types.UpdateExplanationDatasetResponse` Response message of
+                   [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset]
+                   operation.
+
+        """
+        # 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([model])
+        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 model_service.UpdateExplanationDatasetRequest.
+        # There's no risk of modifying the input as we've already verified
+        # there are no flattened fields.
+        if not isinstance(request, model_service.UpdateExplanationDatasetRequest):
+            request = model_service.UpdateExplanationDatasetRequest(request)
+            # If we have keyword arguments corresponding to fields on the
+            # request, apply these.
+            if model is not None:
+                request.model = model
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._transport._wrapped_methods[
+            self._transport.update_explanation_dataset
+        ]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("model", request.model),)),
+        )
+
+        # 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,
+            model_service.UpdateExplanationDatasetResponse,
+            metadata_type=model_service.UpdateExplanationDatasetOperationMetadata,
+        )
+
+        # Done; return the response.
+        return response
+
     def delete_model(
         self,
         request: Optional[Union[model_service.DeleteModelRequest, dict]] = None,

google/cloud/aiplatform_v1/services/model_service/transports/base.py

@@ -159,6 +159,11 @@ def _prep_wrapped_messages(self, client_info):
                 default_timeout=None,
                 client_info=client_info,
             ),
+            self.update_explanation_dataset: gapic_v1.method.wrap_method(
+                self.update_explanation_dataset,
+                default_timeout=None,
+                client_info=client_info,
+            ),
             self.delete_model: gapic_v1.method.wrap_method(
                 self.delete_model,
                 default_timeout=None,
@@ -285,6 +290,15 @@ def update_model(
     ]:
         raise NotImplementedError()
 
+    @property
+    def update_explanation_dataset(
+        self,
+    ) -> Callable[
+        [model_service.UpdateExplanationDatasetRequest],
+        Union[operations_pb2.Operation, Awaitable[operations_pb2.Operation]],
+    ]:
+        raise NotImplementedError()
+
     @property
     def delete_model(
         self,