Viewing file:  model_service_pb2.py (3.93 KB) -rw-r--r--
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# Copyright 2018 Google Inc. All Rights Reserved.
#
# 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.
# ==============================================================================
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: tensorflow_serving/apis/model_service.proto
# To regenerate run
# python -m grpc.tools.protoc --python_out=. --grpc_python_out=. -I. tensorflow_serving/apis/model_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()
from tensorboard._vendor.tensorflow_serving.apis import get_model_status_pb2 as tensorflow__serving_dot_apis_dot_get__model__status__pb2
from tensorboard._vendor.tensorflow_serving.apis import model_management_pb2 as tensorflow__serving_dot_apis_dot_model__management__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='tensorflow_serving/apis/model_service.proto',
package='tensorflow.serving',
syntax='proto3',
serialized_pb=_b(
'\n+tensorflow_serving/apis/model_service.proto\x12\x12tensorflow.serving\x1a.tensorflow_serving/apis/get_model_status.proto\x1a.tensorflow_serving/apis/model_management.proto2\xe7\x01\n\x0cModelService\x12g\n\x0eGetModelStatus\x12).tensorflow.serving.GetModelStatusRequest\x1a*.tensorflow.serving.GetModelStatusResponse\x12n\n\x19HandleReloadConfigRequest\x12\'.tensorflow.serving.ReloadConfigRequest\x1a(.tensorflow.serving.ReloadConfigResponseB\x03\xf8\x01\x01\x62\x06proto3'
),
dependencies=[
tensorflow__serving_dot_apis_dot_get__model__status__pb2.DESCRIPTOR,
tensorflow__serving_dot_apis_dot_model__management__pb2.DESCRIPTOR,
])
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
DESCRIPTOR.has_options = True
DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\370\001\001'))
_MODELSERVICE = _descriptor.ServiceDescriptor(
name='ModelService',
full_name='tensorflow.serving.ModelService',
file=DESCRIPTOR,
index=0,
options=None,
serialized_start=164,
serialized_end=395,
methods=[
_descriptor.MethodDescriptor(
name='GetModelStatus',
full_name='tensorflow.serving.ModelService.GetModelStatus',
index=0,
containing_service=None,
input_type=tensorflow__serving_dot_apis_dot_get__model__status__pb2.
_GETMODELSTATUSREQUEST,
output_type=tensorflow__serving_dot_apis_dot_get__model__status__pb2.
_GETMODELSTATUSRESPONSE,
options=None,
),
_descriptor.MethodDescriptor(
name='HandleReloadConfigRequest',
full_name=
'tensorflow.serving.ModelService.HandleReloadConfigRequest',
index=1,
containing_service=None,
input_type=tensorflow__serving_dot_apis_dot_model__management__pb2.
_RELOADCONFIGREQUEST,
output_type=tensorflow__serving_dot_apis_dot_model__management__pb2.
_RELOADCONFIGRESPONSE,
options=None,
),
])
_sym_db.RegisterServiceDescriptor(_MODELSERVICE)
DESCRIPTOR.services_by_name['ModelService'] = _MODELSERVICE
# @@protoc_insertion_point(module_scope)
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