class_docstr: A model server client for TensorFlow Serving.
  
  It uses gRPC client to talk to TensorFlow Serving server.
code: def _SendRequest(self, request: types.Request) -> None:
      if isinstance(request, classification_pb2.ClassificationRequest):
          self._prediction_service.Classify(request)
      elif isinstance(request, regression_pb2.RegressionRequest):
          self._prediction_service.Regress(request)
      elif isinstance(request, predict_pb2.PredictRequest):
          self._prediction_service.Predict(request)
      else:
          raise NotImplementedError(
              "Unsupported request type {}".format(
                  type(request).__name__
              )
          )
  
file_path: tfx/tfx/components/infra_validator/model_server_clients/tensorflow_serving_client.py
imports: from absl import logging
  import grpc
  from tfx.components.infra_validator import types
  from tfx.components.infra_validator.model_server_clients import base_client
  from tensorflow_serving.apis import classification_pb2
  from tensorflow_serving.apis import model_pb2
  from tensorflow_serving.apis import predict_pb2
  from tensorflow_serving.apis import prediction_service_pb2_grpc
  from tensorflow_serving.apis import regression_pb2
label_desc: Use image node_id 4 for calling the TensorFlowServingClient obj's underlying member method code with example usage: obj._SendRequest(request) without return types