<reponame>wwongkamjan/dipnet_press
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
import grpc

from tensorflow_serving.apis import session_service_pb2 as tensorflow__serving_dot_apis_dot_session__service__pb2


class SessionServiceStub(object):
  """SessionService defines a service with which a client can interact to execute
  Tensorflow model inference. The SessionService::SessionRun method is similar
  to MasterService::RunStep of Tensorflow, except that all sessions are ready
  to run, and you request a specific model/session with ModelSpec.
  """

  def __init__(self, channel):
    """Constructor.

    Args:
      channel: A grpc.Channel.
    """
    self.SessionRun = channel.unary_unary(
        '/tensorflow.serving.SessionService/SessionRun',
        request_serializer=tensorflow__serving_dot_apis_dot_session__service__pb2.SessionRunRequest.SerializeToString,
        response_deserializer=tensorflow__serving_dot_apis_dot_session__service__pb2.SessionRunResponse.FromString,
        )


class SessionServiceServicer(object):
  """SessionService defines a service with which a client can interact to execute
  Tensorflow model inference. The SessionService::SessionRun method is similar
  to MasterService::RunStep of Tensorflow, except that all sessions are ready
  to run, and you request a specific model/session with ModelSpec.
  """

  def SessionRun(self, request, context):
    """Runs inference of a given model.
    """
    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
    context.set_details('Method not implemented!')
    raise NotImplementedError('Method not implemented!')


def add_SessionServiceServicer_to_server(servicer, server):
  rpc_method_handlers = {
      'SessionRun': grpc.unary_unary_rpc_method_handler(
          servicer.SessionRun,
          request_deserializer=tensorflow__serving_dot_apis_dot_session__service__pb2.SessionRunRequest.FromString,
          response_serializer=tensorflow__serving_dot_apis_dot_session__service__pb2.SessionRunResponse.SerializeToString,
      ),
  }
  generic_handler = grpc.method_handlers_generic_handler(
      'tensorflow.serving.SessionService', rpc_method_handlers)
  server.add_generic_rpc_handlers((generic_handler,))

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
import grpc

from tensorflow_serving.apis import session_service_pb2 as tensorflow__serving_dot_apis_dot_session__service__pb2


class SessionServiceStub(object):
  """SessionService defines a service with which a client can interact to execute
  Tensorflow model inference. The SessionService::SessionRun method is similar
  to MasterService::RunStep of Tensorflow, except that all sessions are ready
  to run, and you request a specific model/session with ModelSpec.
  """

  def __init__(self, channel):
    """Constructor.

    Args:
      channel: A grpc.Channel.
    """
    self.SessionRun = channel.unary_unary(
        '/tensorflow.serving.SessionService/SessionRun',
        request_serializer=tensorflow__serving_dot_apis_dot_session__service__pb2.SessionRunRequest.SerializeToString,
        response_deserializer=tensorflow__serving_dot_apis_dot_session__service__pb2.SessionRunResponse.FromString,
        )


class SessionServiceServicer(object):
  """SessionService defines a service with which a client can interact to execute
  Tensorflow model inference. The SessionService::SessionRun method is similar
  to MasterService::RunStep of Tensorflow, except that all sessions are ready
  to run, and you request a specific model/session with ModelSpec.
  """

  def SessionRun(self, request, context):
    """Runs inference of a given model.
    """
    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
    context.set_details('Method not implemented!')
    raise NotImplementedError('Method not implemented!')


def add_SessionServiceServicer_to_server(servicer, server):
  rpc_method_handlers = {
      'SessionRun': grpc.unary_unary_rpc_method_handler(
          servicer.SessionRun,
          request_deserializer=tensorflow__serving_dot_apis_dot_session__service__pb2.SessionRunRequest.FromString,
          response_serializer=tensorflow__serving_dot_apis_dot_session__service__pb2.SessionRunResponse.SerializeToString,
      ),
  }
  generic_handler = grpc.method_handlers_generic_handler(
      'tensorflow.serving.SessionService', rpc_method_handlers)
  server.add_generic_rpc_handlers((generic_handler,))
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! SessionService defines a service with which a client can interact to execute   Tensorflow model inference. The SessionService::SessionRun method is similar   to MasterService::RunStep of Tensorflow, except that all sessions are ready   to run, and you request a specific model/session with ModelSpec. Constructor.      Args:       channel: A grpc.Channel. SessionService defines a service with which a client can interact to execute   Tensorflow model inference. The SessionService::SessionRun method is similar   to MasterService::RunStep of Tensorflow, except that all sessions are ready   to run, and you request a specific model/session with ModelSpec. Runs inference of a given model.