prediction_service_pb2.py

# Generated by the protocol buffer compiler.  DO NOT EDIT!
# source: prediction_service.proto

import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)

_sym_db = _symbol_database.Default()


import predict_pb2 as predict__pb2


DESCRIPTOR = _descriptor.FileDescriptor(
  name='prediction_service.proto',
  package='tensorflow.serving',
  syntax='proto3',
  serialized_pb=_b('\n\x18prediction_service.proto\x12\x12tensorflow.serving\x1a\rpredict.proto2g\n\x11PredictionService\x12R\n\x07Predict\x12\".tensorflow.serving.PredictRequest\x1a#.tensorflow.serving.PredictResponseB\x03\xf8\x01\x01\x62\x06proto3')
  ,
  dependencies=[predict__pb2.DESCRIPTOR,])
_sym_db.RegisterFileDescriptor(DESCRIPTOR)





DESCRIPTOR.has_options = True
DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\370\001\001'))
import grpc
from grpc.beta import implementations as beta_implementations
from grpc.beta import interfaces as beta_interfaces
from grpc.framework.common import cardinality
from grpc.framework.interfaces.face import utilities as face_utilities


class PredictionServiceStub(object):
  """PredictionService provides access to machine-learned models loaded by
  model_servers.
  """

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

    Args:
      channel: A grpc.Channel.
    """
    self.Predict = channel.unary_unary(
        '/tensorflow.serving.PredictionService/Predict',
        request_serializer=predict__pb2.PredictRequest.SerializeToString,
        response_deserializer=predict__pb2.PredictResponse.FromString,
        )


class PredictionServiceServicer(object):
  """PredictionService provides access to machine-learned models loaded by
  model_servers.
  """

  def Predict(self, request, context):
    """Predict -- provides access to loaded TensorFlow model.
    """
    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
    context.set_details('Method not implemented!')
    raise NotImplementedError('Method not implemented!')


def add_PredictionServiceServicer_to_server(servicer, server):
  rpc_method_handlers = {
      'Predict': grpc.unary_unary_rpc_method_handler(
          servicer.Predict,
          request_deserializer=predict__pb2.PredictRequest.FromString,
          response_serializer=predict__pb2.PredictResponse.SerializeToString,
      ),
  }
  generic_handler = grpc.method_handlers_generic_handler(
      'tensorflow.serving.PredictionService', rpc_method_handlers)
  server.add_generic_rpc_handlers((generic_handler,))


class BetaPredictionServiceServicer(object):
  """PredictionService provides access to machine-learned models loaded by
  model_servers.
  """
  def Predict(self, request, context):
    """Predict -- provides access to loaded TensorFlow model.
    """
    context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)


class BetaPredictionServiceStub(object):
  """PredictionService provides access to machine-learned models loaded by
  model_servers.
  """
  def Predict(self, request, timeout, metadata=None, with_call=False, protocol_options=None):
    """Predict -- provides access to loaded TensorFlow model.
    """
    raise NotImplementedError()
  Predict.future = None


def beta_create_PredictionService_server(servicer, pool=None, pool_size=None, default_timeout=None, maximum_timeout=None):
  request_deserializers = {
    ('tensorflow.serving.PredictionService', 'Predict'): predict__pb2.PredictRequest.FromString,
  }
  response_serializers = {
    ('tensorflow.serving.PredictionService', 'Predict'): predict__pb2.PredictResponse.SerializeToString,
  }
  method_implementations = {
    ('tensorflow.serving.PredictionService', 'Predict'): face_utilities.unary_unary_inline(servicer.Predict),
  }
  server_options = beta_implementations.server_options(request_deserializers=request_deserializers, response_serializers=response_serializers, thread_pool=pool, thread_pool_size=pool_size, default_timeout=default_timeout, maximum_timeout=maximum_timeout)
  return beta_implementations.server(method_implementations, options=server_options)


def beta_create_PredictionService_stub(channel, host=None, metadata_transformer=None, pool=None, pool_size=None):
  request_serializers = {
    ('tensorflow.serving.PredictionService', 'Predict'): predict__pb2.PredictRequest.SerializeToString,
  }
  response_deserializers = {
    ('tensorflow.serving.PredictionService', 'Predict'): predict__pb2.PredictResponse.FromString,
  }
  cardinalities = {
    'Predict': cardinality.Cardinality.UNARY_UNARY,
  }
  stub_options = beta_implementations.stub_options(host=host, metadata_transformer=metadata_transformer, request_serializers=request_serializers, response_deserializers=response_deserializers, thread_pool=pool, thread_pool_size=pool_size)
  return beta_implementations.dynamic_stub(channel, 'tensorflow.serving.PredictionService', cardinalities, options=stub_options)
# @@protoc_insertion_point(module_scope)