text: # -*- coding: utf-8 -*-
  # Copyright 2020 Google LLC
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  #
  import warnings
  from typing import Callable, Dict, Optional, Sequence, Tuple, Union
  
  from google.api_core import grpc_helpers  # type: ignore
  from google.api_core import operations_v1  # type: ignore
  from google.api_core import gapic_v1  # type: ignore
  import google.auth  # type: ignore
  from google.auth import credentials as ga_credentials  # type: ignore
  from google.auth.transport.grpc import SslCredentials  # type: ignore
  
  import grpc  # type: ignore
  
  from google.cloud.aiplatform_v1beta1.types import model
  from google.cloud.aiplatform_v1beta1.types import model as gca_model
  from google.cloud.aiplatform_v1beta1.types import model_evaluation
  from google.cloud.aiplatform_v1beta1.types import model_evaluation_slice
  from google.cloud.aiplatform_v1beta1.types import model_service
  from google.longrunning import operations_pb2  # type: ignore
  from .base import ModelServiceTransport, DEFAULT_CLIENT_INFO
  
  
  class ModelServiceGrpcTransport(ModelServiceTransport):
      """gRPC backend transport for ModelService.
  
      A service for managing Vertex AI's machine learning Models.
  
      This class defines the same methods as the primary client, so the
      primary client can load the underlying transport implementation
      and call it.
  
      It sends protocol buffers over the wire using gRPC (which is built on
      top of HTTP/2); the ``grpcio`` package must be installed.
      """
  
      _stubs: Dict[str, Callable]
  
      def __init__(
          self,
          *,
          host: str = "aiplatform.googleapis.com",
          credentials: ga_credentials.Credentials = None,
          credentials_file: str = None,
          scopes: Sequence[str] = None,
          channel: grpc.Channel = None,
          api_mtls_endpoint: str = None,
          client_cert_source: Callable[[], Tuple[bytes, bytes]] = None,
          ssl_channel_credentials: grpc.ChannelCredentials = None,
          client_cert_source_for_mtls: Callable[[], Tuple[bytes, bytes]] = None,
          quota_project_id: Optional[str] = None,
          client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
      ) -> None:
          """Instantiate the transport.
  
          Args:
              host (Optional[str]):
                   The hostname to connect to.
              credentials (Optional[google.auth.credentials.Credentials]): The
                  authorization credentials to attach to requests. These
                  credentials identify the application to the service; if none
                  are specified, the client will attempt to ascertain the
                  credentials from the environment.
                  This argument is ignored if ``channel`` is provided.
              credentials_file (Optional[str]): A file with credentials that can
                  be loaded with :func:`google.auth.load_credentials_from_file`.
                  This argument is ignored if ``channel`` is provided.
              scopes (Optional(Sequence[str])): A list of scopes. This argument is
                  ignored if ``channel`` is provided.
              channel (Optional[grpc.Channel]): A ``Channel`` instance through
                  which to make calls.
              api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint.
                  If provided, it overrides the ``host`` argument and tries to create
                  a mutual TLS channel with client SSL credentials from
                  ``client_cert_source`` or applicatin default SSL credentials.
              client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]):
                  Deprecated. A callback to provide client SSL certificate bytes and
                  private key bytes, both in PEM format. It is ignored if
                  ``api_mtls_endpoint`` is None.
              ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials
                  for grpc channel. It is ignored if ``channel`` is provided.
              client_cert_source_for_mtls (Optional[Callable[[], Tuple[bytes, bytes]]]):
                  A callback to provide client certificate bytes and private key bytes,
                  both in PEM format. It is used to configure mutual TLS channel. It is
                  ignored if ``channel`` or ``ssl_channel_credentials`` is provided.
              quota_project_id (Optional[str]): An optional project to use for billing
                  and quota.
              client_info (google.api_core.gapic_v1.client_info.ClientInfo):
                  The client info used to send a user-agent string along with
                  API requests. If ``None``, then default info will be used.
                  Generally, you only need to set this if you're developing
                  your own client library.
  
          Raises:
            google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
                creation failed for any reason.
            google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials``
                and ``credentials_file`` are passed.
          """
          self._grpc_channel = None
          self._ssl_channel_credentials = ssl_channel_credentials
          self._stubs: Dict[str, Callable] = {}
          self._operations_client = None
  
          if api_mtls_endpoint:
              warnings.warn("api_mtls_endpoint is deprecated", DeprecationWarning)
          if client_cert_source:
              warnings.warn("client_cert_source is deprecated", DeprecationWarning)
  
          if channel:
              # Ignore credentials if a channel was passed.
              credentials = False
              # If a channel was explicitly provided, set it.
              self._grpc_channel = channel
              self._ssl_channel_credentials = None
  
          else:
              if api_mtls_endpoint:
                  host = api_mtls_endpoint
  
                  # Create SSL credentials with client_cert_source or application
                  # default SSL credentials.
                  if client_cert_source:
                      cert, key = client_cert_source()
                      self._ssl_channel_credentials = grpc.ssl_channel_credentials(
                          certificate_chain=cert, private_key=key
                      )
                  else:
                      self._ssl_channel_credentials = SslCredentials().ssl_credentials
  
              else:
                  if client_cert_source_for_mtls and not ssl_channel_credentials:
                      cert, key = client_cert_source_for_mtls()
                      self._ssl_channel_credentials = grpc.ssl_channel_credentials(
                          certificate_chain=cert, private_key=key
                      )
  
          # The base transport sets the host, credentials and scopes
          super().__init__(
              host=host,
              credentials=credentials,
              credentials_file=credentials_file,
              scopes=scopes,
              quota_project_id=quota_project_id,
              client_info=client_info,
          )
  
          if not self._grpc_channel:
              self._grpc_channel = type(self).create_channel(
                  self._host,
                  credentials=self._credentials,
                  credentials_file=credentials_file,
                  scopes=self._scopes,
                  ssl_credentials=self._ssl_channel_credentials,
                  quota_project_id=quota_project_id,
                  options=[
                      ("grpc.max_send_message_length", -1),
                      ("grpc.max_receive_message_length", -1),
                  ],
              )
  
          # Wrap messages. This must be done after self._grpc_channel exists
          self._prep_wrapped_messages(client_info)
  
      @classmethod
      def create_channel(
          cls,
          host: str = "aiplatform.googleapis.com",
          credentials: ga_credentials.Credentials = None,
          credentials_file: str = None,
          scopes: Optional[Sequence[str]] = None,
          quota_project_id: Optional[str] = None,
          **kwargs,
      ) -> grpc.Channel:
          """Create and return a gRPC channel object.
          Args:
              host (Optional[str]): The host for the channel to use.
              credentials (Optional[~.Credentials]): The
                  authorization credentials to attach to requests. These
                  credentials identify this application to the service. If
                  none are specified, the client will attempt to ascertain
                  the credentials from the environment.
              credentials_file (Optional[str]): A file with credentials that can
                  be loaded with :func:`google.auth.load_credentials_from_file`.
                  This argument is mutually exclusive with credentials.
              scopes (Optional[Sequence[str]]): A optional list of scopes needed for this
                  service. These are only used when credentials are not specified and
                  are passed to :func:`google.auth.default`.
              quota_project_id (Optional[str]): An optional project to use for billing
                  and quota.
              kwargs (Optional[dict]): Keyword arguments, which are passed to the
                  channel creation.
          Returns:
              grpc.Channel: A gRPC channel object.
  
          Raises:
              google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials``
                and ``credentials_file`` are passed.
          """
  
          self_signed_jwt_kwargs = cls._get_self_signed_jwt_kwargs(host, scopes)
  
          return grpc_helpers.create_channel(
              host,
              credentials=credentials,
              credentials_file=credentials_file,
              quota_project_id=quota_project_id,
              **self_signed_jwt_kwargs,
              **kwargs,
          )
  
      @property
      def grpc_channel(self) -> grpc.Channel:
          """Return the channel designed to connect to this service.
          """
          return self._grpc_channel
  
      @property
      def operations_client(self) -> operations_v1.OperationsClient:
          """Create the client designed to process long-running operations.
  
          This property caches on the instance; repeated calls return the same
          client.
          """
          # Sanity check: Only create a new client if we do not already have one.
          if self._operations_client is None:
              self._operations_client = operations_v1.OperationsClient(self.grpc_channel)
  
          # Return the client from cache.
          return self._operations_client
  
      @property
      def upload_model(
          self,
      ) -> Callable[[model_service.UploadModelRequest], operations_pb2.Operation]:
          r"""Return a callable for the upload model method over gRPC.
  
          Uploads a Model artifact into Vertex AI.
  
          Returns:
              Callable[[~.UploadModelRequest],
                      ~.Operation]:
                  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 "upload_model" not in self._stubs:
              self._stubs["upload_model"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/UploadModel",
                  request_serializer=model_service.UploadModelRequest.serialize,
                  response_deserializer=operations_pb2.Operation.FromString,
              )
          return self._stubs["upload_model"]
  
      @property
      def get_model(self) -> Callable[[model_service.GetModelRequest], model.Model]:
          r"""Return a callable for the get model method over gRPC.
  
          Gets a Model.
  
          Returns:
              Callable[[~.GetModelRequest],
                      ~.Model]:
                  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 "get_model" not in self._stubs:
              self._stubs["get_model"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/GetModel",
                  request_serializer=model_service.GetModelRequest.serialize,
                  response_deserializer=model.Model.deserialize,
              )
          return self._stubs["get_model"]
  
      @property
      def list_models(
          self,
      ) -> Callable[[model_service.ListModelsRequest], model_service.ListModelsResponse]:
          r"""Return a callable for the list models method over gRPC.
  
          Lists Models in a Location.
  
          Returns:
              Callable[[~.ListModelsRequest],
                      ~.ListModelsResponse]:
                  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 "list_models" not in self._stubs:
              self._stubs["list_models"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/ListModels",
                  request_serializer=model_service.ListModelsRequest.serialize,
                  response_deserializer=model_service.ListModelsResponse.deserialize,
              )
          return self._stubs["list_models"]
  
      @property
      def update_model(
          self,
      ) -> Callable[[model_service.UpdateModelRequest], gca_model.Model]:
          r"""Return a callable for the update model method over gRPC.
  
          Updates a Model.
  
          Returns:
              Callable[[~.UpdateModelRequest],
                      ~.Model]:
                  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 "update_model" not in self._stubs:
              self._stubs["update_model"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/UpdateModel",
                  request_serializer=model_service.UpdateModelRequest.serialize,
                  response_deserializer=gca_model.Model.deserialize,
              )
          return self._stubs["update_model"]
  
      @property
      def delete_model(
          self,
      ) -> Callable[[model_service.DeleteModelRequest], operations_pb2.Operation]:
          r"""Return a callable for the delete model method over gRPC.
  
          Deletes a Model.
          Note: Model can only be deleted if there are no
          DeployedModels created from it.
  
          Returns:
              Callable[[~.DeleteModelRequest],
                      ~.Operation]:
                  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 "delete_model" not in self._stubs:
              self._stubs["delete_model"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/DeleteModel",
                  request_serializer=model_service.DeleteModelRequest.serialize,
                  response_deserializer=operations_pb2.Operation.FromString,
              )
          return self._stubs["delete_model"]
  
      @property
      def export_model(
          self,
      ) -> Callable[[model_service.ExportModelRequest], operations_pb2.Operation]:
          r"""Return a callable for the export model method over gRPC.
  
          Exports a trained, exportable, Model to a location specified by
          the user. A Model is considered to be exportable if it has at
          least one [supported export
          format][google.cloud.aiplatform.v1beta1.Model.supported_export_formats].
  
          Returns:
              Callable[[~.ExportModelRequest],
                      ~.Operation]:
                  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 "export_model" not in self._stubs:
              self._stubs["export_model"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/ExportModel",
                  request_serializer=model_service.ExportModelRequest.serialize,
                  response_deserializer=operations_pb2.Operation.FromString,
              )
          return self._stubs["export_model"]
  
      @property
      def get_model_evaluation(
          self,
      ) -> Callable[
          [model_service.GetModelEvaluationRequest], model_evaluation.ModelEvaluation
      ]:
          r"""Return a callable for the get model evaluation method over gRPC.
  
          Gets a ModelEvaluation.
  
          Returns:
              Callable[[~.GetModelEvaluationRequest],
                      ~.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 "get_model_evaluation" not in self._stubs:
              self._stubs["get_model_evaluation"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/GetModelEvaluation",
                  request_serializer=model_service.GetModelEvaluationRequest.serialize,
                  response_deserializer=model_evaluation.ModelEvaluation.deserialize,
              )
          return self._stubs["get_model_evaluation"]
  
      @property
      def list_model_evaluations(
          self,
      ) -> Callable[
          [model_service.ListModelEvaluationsRequest],
          model_service.ListModelEvaluationsResponse,
      ]:
          r"""Return a callable for the list model evaluations method over gRPC.
  
          Lists ModelEvaluations in a Model.
  
          Returns:
              Callable[[~.ListModelEvaluationsRequest],
                      ~.ListModelEvaluationsResponse]:
                  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 "list_model_evaluations" not in self._stubs:
              self._stubs["list_model_evaluations"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/ListModelEvaluations",
                  request_serializer=model_service.ListModelEvaluationsRequest.serialize,
                  response_deserializer=model_service.ListModelEvaluationsResponse.deserialize,
              )
          return self._stubs["list_model_evaluations"]
  
      @property
      def get_model_evaluation_slice(
          self,
      ) -> Callable[
          [model_service.GetModelEvaluationSliceRequest],
          model_evaluation_slice.ModelEvaluationSlice,
      ]:
          r"""Return a callable for the get model evaluation slice method over gRPC.
  
          Gets a ModelEvaluationSlice.
  
          Returns:
              Callable[[~.GetModelEvaluationSliceRequest],
                      ~.ModelEvaluationSlice]:
                  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 "get_model_evaluation_slice" not in self._stubs:
              self._stubs["get_model_evaluation_slice"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/GetModelEvaluationSlice",
                  request_serializer=model_service.GetModelEvaluationSliceRequest.serialize,
                  response_deserializer=model_evaluation_slice.ModelEvaluationSlice.deserialize,
              )
          return self._stubs["get_model_evaluation_slice"]
  
      @property
      def list_model_evaluation_slices(
          self,
      ) -> Callable[
          [model_service.ListModelEvaluationSlicesRequest],
          model_service.ListModelEvaluationSlicesResponse,
      ]:
          r"""Return a callable for the list model evaluation slices method over gRPC.
  
          Lists ModelEvaluationSlices in a ModelEvaluation.
  
          Returns:
              Callable[[~.ListModelEvaluationSlicesRequest],
                      ~.ListModelEvaluationSlicesResponse]:
                  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 "list_model_evaluation_slices" not in self._stubs:
              self._stubs["list_model_evaluation_slices"] = self.grpc_channel.unary_unary(
                  "/google.cloud.aiplatform.v1beta1.ModelService/ListModelEvaluationSlices",
                  request_serializer=model_service.ListModelEvaluationSlicesRequest.serialize,
                  response_deserializer=model_service.ListModelEvaluationSlicesResponse.deserialize,
              )
          return self._stubs["list_model_evaluation_slices"]
  
  
  __all__ = ("ModelServiceGrpcTransport",)
  