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# Copyright 2016 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 gRPC Python protocol compiler plugin. DO NOT EDIT!
# source: tensorflow_serving/apis/prediction_service.proto
# To regenerate run
# python -m grpc.tools.protoc --python_out=. --grpc_python_out=. -I. tensorflow_serving/apis/prediction_service.proto
import grpc
from tensorboard._vendor.tensorflow_serving.apis import classification_pb2 as tensorflow__serving_dot_apis_dot_classification__pb2
from tensorboard._vendor.tensorflow_serving.apis import get_model_metadata_pb2 as tensorflow__serving_dot_apis_dot_get__model__metadata__pb2
from tensorboard._vendor.tensorflow_serving.apis import inference_pb2 as tensorflow__serving_dot_apis_dot_inference__pb2
from tensorboard._vendor.tensorflow_serving.apis import predict_pb2 as tensorflow__serving_dot_apis_dot_predict__pb2
from tensorboard._vendor.tensorflow_serving.apis import regression_pb2 as tensorflow__serving_dot_apis_dot_regression__pb2
class PredictionServiceStub(object):
"""open source marker; do not remove
PredictionService provides access to machine-learned models loaded by
model_servers.
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
self.Classify = channel.unary_unary(
'/tensorflow.serving.PredictionService/Classify',
request_serializer=tensorflow__serving_dot_apis_dot_classification__pb2.ClassificationRequest.SerializeToString,
response_deserializer=tensorflow__serving_dot_apis_dot_classification__pb2.ClassificationResponse.FromString,
)
self.Regress = channel.unary_unary(
'/tensorflow.serving.PredictionService/Regress',
request_serializer=tensorflow__serving_dot_apis_dot_regression__pb2.RegressionRequest.SerializeToString,
response_deserializer=tensorflow__serving_dot_apis_dot_regression__pb2.RegressionResponse.FromString,
)
self.Predict = channel.unary_unary(
'/tensorflow.serving.PredictionService/Predict',
request_serializer=tensorflow__serving_dot_apis_dot_predict__pb2.PredictRequest.SerializeToString,
response_deserializer=tensorflow__serving_dot_apis_dot_predict__pb2.PredictResponse.FromString,
)
self.MultiInference = channel.unary_unary(
'/tensorflow.serving.PredictionService/MultiInference',
request_serializer=tensorflow__serving_dot_apis_dot_inference__pb2.MultiInferenceRequest.SerializeToString,
response_deserializer=tensorflow__serving_dot_apis_dot_inference__pb2.MultiInferenceResponse.FromString,
)
self.GetModelMetadata = channel.unary_unary(
'/tensorflow.serving.PredictionService/GetModelMetadata',
request_serializer=tensorflow__serving_dot_apis_dot_get__model__metadata__pb2.GetModelMetadataRequest.SerializeToString,
response_deserializer=tensorflow__serving_dot_apis_dot_get__model__metadata__pb2.GetModelMetadataResponse.FromString,
)
class PredictionServiceServicer(object):
"""open source marker; do not remove
PredictionService provides access to machine-learned models loaded by
model_servers.
"""
def Classify(self, request, context):
"""Classify.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def Regress(self, request, context):
"""Regress.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
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 MultiInference(self, request, context):
"""MultiInference API for multi-headed models.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def GetModelMetadata(self, request, context):
"""GetModelMetadata - provides access to metadata for loaded models.
"""
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 = {
'Classify': grpc.unary_unary_rpc_method_handler(
servicer.Classify,
request_deserializer=tensorflow__serving_dot_apis_dot_classification__pb2.ClassificationRequest.FromString,
response_serializer=tensorflow__serving_dot_apis_dot_classification__pb2.ClassificationResponse.SerializeToString,
),
'Regress': grpc.unary_unary_rpc_method_handler(
servicer.Regress,
request_deserializer=tensorflow__serving_dot_apis_dot_regression__pb2.RegressionRequest.FromString,
response_serializer=tensorflow__serving_dot_apis_dot_regression__pb2.RegressionResponse.SerializeToString,
),
'Predict': grpc.unary_unary_rpc_method_handler(
servicer.Predict,
request_deserializer=tensorflow__serving_dot_apis_dot_predict__pb2.PredictRequest.FromString,
response_serializer=tensorflow__serving_dot_apis_dot_predict__pb2.PredictResponse.SerializeToString,
),
'MultiInference': grpc.unary_unary_rpc_method_handler(
servicer.MultiInference,
request_deserializer=tensorflow__serving_dot_apis_dot_inference__pb2.MultiInferenceRequest.FromString,
response_serializer=tensorflow__serving_dot_apis_dot_inference__pb2.MultiInferenceResponse.SerializeToString,
),
'GetModelMetadata': grpc.unary_unary_rpc_method_handler(
servicer.GetModelMetadata,
request_deserializer=tensorflow__serving_dot_apis_dot_get__model__metadata__pb2.GetModelMetadataRequest.FromString,
response_serializer=tensorflow__serving_dot_apis_dot_get__model__metadata__pb2.GetModelMetadataResponse.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
'tensorflow.serving.PredictionService', rpc_method_handlers)
server.add_generic_rpc_handlers((generic_handler,))
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