feat: add ImportModelEvaluation in aiplatform v1 model_service.proto

google/cloud/aiplatform_v1/__init__.py

@@ -348,6 +348,7 @@
 from .types.model_service import GetModelEvaluationRequest
 from .types.model_service import GetModelEvaluationSliceRequest
 from .types.model_service import GetModelRequest
+from .types.model_service import ImportModelEvaluationRequest
 from .types.model_service import ListModelEvaluationSlicesRequest
 from .types.model_service import ListModelEvaluationSlicesResponse
 from .types.model_service import ListModelEvaluationsRequest
@@ -720,6 +721,7 @@
     "ImportFeatureValuesOperationMetadata",
     "ImportFeatureValuesRequest",
     "ImportFeatureValuesResponse",
+    "ImportModelEvaluationRequest",
     "Index",
     "IndexEndpoint",
     "IndexEndpointServiceClient",

google/cloud/aiplatform_v1/gapic_metadata.json

@@ -1291,6 +1291,11 @@
                 "get_model_evaluation_slice"
               ]
             },
+            "ImportModelEvaluation": {
+              "methods": [
+                "import_model_evaluation"
+              ]
+            },
             "ListModelEvaluationSlices": {
               "methods": [
                 "list_model_evaluation_slices"
@@ -1346,6 +1351,11 @@
                 "get_model_evaluation_slice"
               ]
             },
+            "ImportModelEvaluation": {
+              "methods": [
+                "import_model_evaluation"
+              ]
+            },
             "ListModelEvaluationSlices": {
               "methods": [
                 "list_model_evaluation_slices"

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

@@ -40,6 +40,7 @@
 from google.cloud.aiplatform_v1.types import model
 from google.cloud.aiplatform_v1.types import model as gca_model
 from google.cloud.aiplatform_v1.types import model_evaluation
+from google.cloud.aiplatform_v1.types import model_evaluation as gca_model_evaluation
 from google.cloud.aiplatform_v1.types import model_evaluation_slice
 from google.cloud.aiplatform_v1.types import model_service
 from google.cloud.aiplatform_v1.types import operation as gca_operation
@@ -886,6 +887,108 @@ def sample_export_model():
         # Done; return the response.
         return response
 
+    async def import_model_evaluation(
+        self,
+        request: Union[model_service.ImportModelEvaluationRequest, dict] = None,
+        *,
+        parent: str = None,
+        model_evaluation: gca_model_evaluation.ModelEvaluation = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: float = None,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> gca_model_evaluation.ModelEvaluation:
+        r"""Imports an externally generated ModelEvaluation.
+
+        .. code-block:: python
+
+            from google.cloud import aiplatform_v1
+
+            def sample_import_model_evaluation():
+                # Create a client
+                client = aiplatform_v1.ModelServiceClient()
+
+                # Initialize request argument(s)
+                request = aiplatform_v1.ImportModelEvaluationRequest(
+                    parent="parent_value",
+                )
+
+                # Make the request
+                response = client.import_model_evaluation(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Union[google.cloud.aiplatform_v1.types.ImportModelEvaluationRequest, dict]):
+                The request object. Request message for
+                [ModelService.ImportModelEvaluation][google.cloud.aiplatform.v1.ModelService.ImportModelEvaluation]
+            parent (:class:`str`):
+                Required. The name of the parent model resource. Format:
+                ``projects/{project}/locations/{location}/models/{model}``
+
+                This corresponds to the ``parent`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            model_evaluation (:class:`google.cloud.aiplatform_v1.types.ModelEvaluation`):
+                Required. Model evaluation resource
+                to be imported.
+
+                This corresponds to the ``model_evaluation`` 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.cloud.aiplatform_v1.types.ModelEvaluation:
+                A collection of metrics calculated by
+                comparing Model's predictions on all of
+                the test data against annotations from
+                the test data.
+
+        """
+        # 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([parent, model_evaluation])
+        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.ImportModelEvaluationRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if parent is not None:
+            request.parent = parent
+        if model_evaluation is not None:
+            request.model_evaluation = model_evaluation
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = gapic_v1.method_async.wrap_method(
+            self._client._transport.import_model_evaluation,
+            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((("parent", request.parent),)),
+        )
+
+        # Send the request.
+        response = await rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
+
+        # Done; return the response.
+        return response
+
     async def get_model_evaluation(
         self,
         request: Union[model_service.GetModelEvaluationRequest, dict] = None,

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

@@ -43,6 +43,7 @@
 from google.cloud.aiplatform_v1.types import model
 from google.cloud.aiplatform_v1.types import model as gca_model
 from google.cloud.aiplatform_v1.types import model_evaluation
+from google.cloud.aiplatform_v1.types import model_evaluation as gca_model_evaluation
 from google.cloud.aiplatform_v1.types import model_evaluation_slice
 from google.cloud.aiplatform_v1.types import model_service
 from google.cloud.aiplatform_v1.types import operation as gca_operation
@@ -1143,6 +1144,108 @@ def sample_export_model():
         # Done; return the response.
         return response
 
+    def import_model_evaluation(
+        self,
+        request: Union[model_service.ImportModelEvaluationRequest, dict] = None,
+        *,
+        parent: str = None,
+        model_evaluation: gca_model_evaluation.ModelEvaluation = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: float = None,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> gca_model_evaluation.ModelEvaluation:
+        r"""Imports an externally generated ModelEvaluation.
+
+        .. code-block:: python
+
+            from google.cloud import aiplatform_v1
+
+            def sample_import_model_evaluation():
+                # Create a client
+                client = aiplatform_v1.ModelServiceClient()
+
+                # Initialize request argument(s)
+                request = aiplatform_v1.ImportModelEvaluationRequest(
+                    parent="parent_value",
+                )
+
+                # Make the request
+                response = client.import_model_evaluation(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Union[google.cloud.aiplatform_v1.types.ImportModelEvaluationRequest, dict]):
+                The request object. Request message for
+                [ModelService.ImportModelEvaluation][google.cloud.aiplatform.v1.ModelService.ImportModelEvaluation]
+            parent (str):
+                Required. The name of the parent model resource. Format:
+                ``projects/{project}/locations/{location}/models/{model}``
+
+                This corresponds to the ``parent`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            model_evaluation (google.cloud.aiplatform_v1.types.ModelEvaluation):
+                Required. Model evaluation resource
+                to be imported.
+
+                This corresponds to the ``model_evaluation`` 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.cloud.aiplatform_v1.types.ModelEvaluation:
+                A collection of metrics calculated by
+                comparing Model's predictions on all of
+                the test data against annotations from
+                the test data.
+
+        """
+        # 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([parent, model_evaluation])
+        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.ImportModelEvaluationRequest.
+        # There's no risk of modifying the input as we've already verified
+        # there are no flattened fields.
+        if not isinstance(request, model_service.ImportModelEvaluationRequest):
+            request = model_service.ImportModelEvaluationRequest(request)
+            # If we have keyword arguments corresponding to fields on the
+            # request, apply these.
+            if parent is not None:
+                request.parent = parent
+            if model_evaluation is not None:
+                request.model_evaluation = model_evaluation
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._transport._wrapped_methods[self._transport.import_model_evaluation]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
+        )
+
+        # Send the request.
+        response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
+
+        # Done; return the response.
+        return response
+
     def get_model_evaluation(
         self,
         request: Union[model_service.GetModelEvaluationRequest, dict] = None,

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

@@ -29,6 +29,7 @@
 from google.cloud.aiplatform_v1.types import model
 from google.cloud.aiplatform_v1.types import model as gca_model
 from google.cloud.aiplatform_v1.types import model_evaluation
+from google.cloud.aiplatform_v1.types import model_evaluation as gca_model_evaluation
 from google.cloud.aiplatform_v1.types import model_evaluation_slice
 from google.cloud.aiplatform_v1.types import model_service
 from google.longrunning import operations_pb2  # type: ignore
@@ -144,6 +145,11 @@ def _prep_wrapped_messages(self, client_info):
             self.export_model: gapic_v1.method.wrap_method(
                 self.export_model, default_timeout=None, client_info=client_info,
             ),
+            self.import_model_evaluation: gapic_v1.method.wrap_method(
+                self.import_model_evaluation,
+                default_timeout=None,
+                client_info=client_info,
+            ),
             self.get_model_evaluation: gapic_v1.method.wrap_method(
                 self.get_model_evaluation,
                 default_timeout=None,
@@ -236,6 +242,18 @@ def export_model(
     ]:
         raise NotImplementedError()
 
+    @property
+    def import_model_evaluation(
+        self,
+    ) -> Callable[
+        [model_service.ImportModelEvaluationRequest],
+        Union[
+            gca_model_evaluation.ModelEvaluation,
+            Awaitable[gca_model_evaluation.ModelEvaluation],
+        ],
+    ]:
+        raise NotImplementedError()
+
     @property
     def get_model_evaluation(
         self,

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

@@ -28,6 +28,7 @@
 from google.cloud.aiplatform_v1.types import model
 from google.cloud.aiplatform_v1.types import model as gca_model
 from google.cloud.aiplatform_v1.types import model_evaluation
+from google.cloud.aiplatform_v1.types import model_evaluation as gca_model_evaluation
 from google.cloud.aiplatform_v1.types import model_evaluation_slice
 from google.cloud.aiplatform_v1.types import model_service
 from google.longrunning import operations_pb2  # type: ignore
@@ -413,6 +414,35 @@ def export_model(
             )
         return self._stubs["export_model"]
 
+    @property
+    def import_model_evaluation(
+        self,
+    ) -> Callable[
+        [model_service.ImportModelEvaluationRequest],
+        gca_model_evaluation.ModelEvaluation,
+    ]:
+        r"""Return a callable for the import model evaluation method over gRPC.
+
+        Imports an externally generated ModelEvaluation.
+
+        Returns:
+            Callable[[~.ImportModelEvaluationRequest],
+                    ~.ModelEvaluation]:
+                A function that, when called, will call the underlying RPC
+                on the server.
+        """
+        # Generate a "stub function" on-the-fly which will actually make
+        # the request.
+        # gRPC handles serialization and deserialization, so we just need
+        # to pass in the functions for each.
+        if "import_model_evaluation" not in self._stubs:
+            self._stubs["import_model_evaluation"] = self.grpc_channel.unary_unary(
+                "/google.cloud.aiplatform.v1.ModelService/ImportModelEvaluation",
+                request_serializer=model_service.ImportModelEvaluationRequest.serialize,
+                response_deserializer=gca_model_evaluation.ModelEvaluation.deserialize,
+            )
+        return self._stubs["import_model_evaluation"]
+
     @property
     def get_model_evaluation(
         self,