From ba5fa502cce67cc0df5aad3c2849bbb41c8ccc65 Mon Sep 17 00:00:00 2001 From: hexia Date: Wed, 22 Jul 2020 15:29:38 +0800 Subject: [PATCH] restructure --- CMakeLists.txt | 1 + serving/core/ms_service_pb2.py | 318 ------------------ serving/core/ms_service_pb2_grpc.py | 96 ------ serving/cpp_example/ms_server.cc | 67 ---- .../cpp_client}/CMakeLists.txt | 66 ++-- .../cpp_client}/ms_client.cc | 105 +----- serving/example/export_model/add_model.py | 46 +++ .../python_client/ms_client.py} | 35 +- serving/python_example/ms_client.py | 57 ---- serving/python_example/ms_server.py | 55 --- serving/python_example/test_cpu_lenet.py | 91 ----- 11 files changed, 107 insertions(+), 830 deletions(-) delete mode 100644 serving/core/ms_service_pb2.py delete mode 100644 serving/core/ms_service_pb2_grpc.py delete mode 100644 serving/cpp_example/ms_server.cc rename serving/{cpp_example => example/cpp_client}/CMakeLists.txt (51%) rename serving/{cpp_example => example/cpp_client}/ms_client.cc (73%) create mode 100644 serving/example/export_model/add_model.py rename serving/{python_example/ms_client_test_call.py => example/python_client/ms_client.py} (52%) delete mode 100644 serving/python_example/ms_client.py delete mode 100644 serving/python_example/ms_server.py delete mode 100644 serving/python_example/test_cpu_lenet.py diff --git a/CMakeLists.txt b/CMakeLists.txt index ef07971b1d..60d061ee12 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -106,6 +106,7 @@ endif() # NOT ENABLE_ACL if (ENABLE_SERVING) add_subdirectory(serving) + add_subdirectory(serving/example/cpp_client) endif() if (NOT ENABLE_ACL) diff --git a/serving/core/ms_service_pb2.py b/serving/core/ms_service_pb2.py deleted file mode 100644 index 9feec026f9..0000000000 --- a/serving/core/ms_service_pb2.py +++ /dev/null @@ -1,318 +0,0 @@ -# -*- coding: utf-8 -*- -# Generated by the protocol buffer compiler. DO NOT EDIT! -# source: ms_service.proto - -from google.protobuf.internal import enum_type_wrapper -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 -# @@protoc_insertion_point(imports) - -_sym_db = _symbol_database.Default() - - - - -DESCRIPTOR = _descriptor.FileDescriptor( - name='ms_service.proto', - package='ms_serving', - syntax='proto3', - serialized_options=None, - serialized_pb=b'\n\x10ms_service.proto\x12\nms_serving\"2\n\x0ePredictRequest\x12 \n\x04\x64\x61ta\x18\x01 \x03(\x0b\x32\x12.ms_serving.Tensor\"2\n\x0cPredictReply\x12\"\n\x06result\x18\x01 \x03(\x0b\x32\x12.ms_serving.Tensor\"\x1b\n\x0bTensorShape\x12\x0c\n\x04\x64ims\x18\x01 \x03(\x03\"p\n\x06Tensor\x12-\n\x0ctensor_shape\x18\x01 \x01(\x0b\x32\x17.ms_serving.TensorShape\x12)\n\x0btensor_type\x18\x02 \x01(\x0e\x32\x14.ms_serving.DataType\x12\x0c\n\x04\x64\x61ta\x18\x03 \x01(\x0c*\xc9\x01\n\x08\x44\x61taType\x12\x0e\n\nMS_UNKNOWN\x10\x00\x12\x0b\n\x07MS_BOOL\x10\x01\x12\x0b\n\x07MS_INT8\x10\x02\x12\x0c\n\x08MS_UINT8\x10\x03\x12\x0c\n\x08MS_INT16\x10\x04\x12\r\n\tMS_UINT16\x10\x05\x12\x0c\n\x08MS_INT32\x10\x06\x12\r\n\tMS_UINT32\x10\x07\x12\x0c\n\x08MS_INT64\x10\x08\x12\r\n\tMS_UINT64\x10\t\x12\x0e\n\nMS_FLOAT16\x10\n\x12\x0e\n\nMS_FLOAT32\x10\x0b\x12\x0e\n\nMS_FLOAT64\x10\x0c\x32\x8e\x01\n\tMSService\x12\x41\n\x07Predict\x12\x1a.ms_serving.PredictRequest\x1a\x18.ms_serving.PredictReply\"\x00\x12>\n\x04Test\x12\x1a.ms_serving.PredictRequest\x1a\x18.ms_serving.PredictReply\"\x00\x62\x06proto3' -) - -_DATATYPE = _descriptor.EnumDescriptor( - name='DataType', - full_name='ms_serving.DataType', - filename=None, - file=DESCRIPTOR, - values=[ - _descriptor.EnumValueDescriptor( - name='MS_UNKNOWN', index=0, number=0, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_BOOL', index=1, number=1, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_INT8', index=2, number=2, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_UINT8', index=3, number=3, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_INT16', index=4, number=4, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_UINT16', index=5, number=5, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_INT32', index=6, number=6, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_UINT32', index=7, number=7, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_INT64', index=8, number=8, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_UINT64', index=9, number=9, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_FLOAT16', index=10, number=10, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_FLOAT32', index=11, number=11, - serialized_options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='MS_FLOAT64', index=12, number=12, - serialized_options=None, - type=None), - ], - containing_type=None, - serialized_options=None, - serialized_start=280, - serialized_end=481, -) -_sym_db.RegisterEnumDescriptor(_DATATYPE) - -DataType = enum_type_wrapper.EnumTypeWrapper(_DATATYPE) -MS_UNKNOWN = 0 -MS_BOOL = 1 -MS_INT8 = 2 -MS_UINT8 = 3 -MS_INT16 = 4 -MS_UINT16 = 5 -MS_INT32 = 6 -MS_UINT32 = 7 -MS_INT64 = 8 -MS_UINT64 = 9 -MS_FLOAT16 = 10 -MS_FLOAT32 = 11 -MS_FLOAT64 = 12 - - - -_PREDICTREQUEST = _descriptor.Descriptor( - name='PredictRequest', - full_name='ms_serving.PredictRequest', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='data', full_name='ms_serving.PredictRequest.data', index=0, - number=1, type=11, cpp_type=10, label=3, - has_default_value=False, default_value=[], - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - serialized_options=None, file=DESCRIPTOR), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - serialized_options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=32, - serialized_end=82, -) - - -_PREDICTREPLY = _descriptor.Descriptor( - name='PredictReply', - full_name='ms_serving.PredictReply', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='result', full_name='ms_serving.PredictReply.result', index=0, - number=1, type=11, cpp_type=10, label=3, - has_default_value=False, default_value=[], - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - serialized_options=None, file=DESCRIPTOR), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - serialized_options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=84, - serialized_end=134, -) - - -_TENSORSHAPE = _descriptor.Descriptor( - name='TensorShape', - full_name='ms_serving.TensorShape', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='dims', full_name='ms_serving.TensorShape.dims', index=0, - number=1, type=3, cpp_type=2, label=3, - has_default_value=False, default_value=[], - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - serialized_options=None, file=DESCRIPTOR), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - serialized_options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=136, - serialized_end=163, -) - - -_TENSOR = _descriptor.Descriptor( - name='Tensor', - full_name='ms_serving.Tensor', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='tensor_shape', full_name='ms_serving.Tensor.tensor_shape', index=0, - number=1, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - serialized_options=None, file=DESCRIPTOR), - _descriptor.FieldDescriptor( - name='tensor_type', full_name='ms_serving.Tensor.tensor_type', index=1, - number=2, type=14, cpp_type=8, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - serialized_options=None, file=DESCRIPTOR), - _descriptor.FieldDescriptor( - name='data', full_name='ms_serving.Tensor.data', index=2, - number=3, type=12, cpp_type=9, label=1, - has_default_value=False, default_value=b"", - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - serialized_options=None, file=DESCRIPTOR), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - serialized_options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=165, - serialized_end=277, -) - -_PREDICTREQUEST.fields_by_name['data'].message_type = _TENSOR -_PREDICTREPLY.fields_by_name['result'].message_type = _TENSOR -_TENSOR.fields_by_name['tensor_shape'].message_type = _TENSORSHAPE -_TENSOR.fields_by_name['tensor_type'].enum_type = _DATATYPE -DESCRIPTOR.message_types_by_name['PredictRequest'] = _PREDICTREQUEST -DESCRIPTOR.message_types_by_name['PredictReply'] = _PREDICTREPLY -DESCRIPTOR.message_types_by_name['TensorShape'] = _TENSORSHAPE -DESCRIPTOR.message_types_by_name['Tensor'] = _TENSOR -DESCRIPTOR.enum_types_by_name['DataType'] = _DATATYPE -_sym_db.RegisterFileDescriptor(DESCRIPTOR) - -PredictRequest = _reflection.GeneratedProtocolMessageType('PredictRequest', (_message.Message,), { - 'DESCRIPTOR' : _PREDICTREQUEST, - '__module__' : 'ms_service_pb2' - # @@protoc_insertion_point(class_scope:ms_serving.PredictRequest) - }) -_sym_db.RegisterMessage(PredictRequest) - -PredictReply = _reflection.GeneratedProtocolMessageType('PredictReply', (_message.Message,), { - 'DESCRIPTOR' : _PREDICTREPLY, - '__module__' : 'ms_service_pb2' - # @@protoc_insertion_point(class_scope:ms_serving.PredictReply) - }) -_sym_db.RegisterMessage(PredictReply) - -TensorShape = _reflection.GeneratedProtocolMessageType('TensorShape', (_message.Message,), { - 'DESCRIPTOR' : _TENSORSHAPE, - '__module__' : 'ms_service_pb2' - # @@protoc_insertion_point(class_scope:ms_serving.TensorShape) - }) -_sym_db.RegisterMessage(TensorShape) - -Tensor = _reflection.GeneratedProtocolMessageType('Tensor', (_message.Message,), { - 'DESCRIPTOR' : _TENSOR, - '__module__' : 'ms_service_pb2' - # @@protoc_insertion_point(class_scope:ms_serving.Tensor) - }) -_sym_db.RegisterMessage(Tensor) - - - -_MSSERVICE = _descriptor.ServiceDescriptor( - name='MSService', - full_name='ms_serving.MSService', - file=DESCRIPTOR, - index=0, - serialized_options=None, - serialized_start=484, - serialized_end=626, - methods=[ - _descriptor.MethodDescriptor( - name='Predict', - full_name='ms_serving.MSService.Predict', - index=0, - containing_service=None, - input_type=_PREDICTREQUEST, - output_type=_PREDICTREPLY, - serialized_options=None, - ), - _descriptor.MethodDescriptor( - name='Test', - full_name='ms_serving.MSService.Test', - index=1, - containing_service=None, - input_type=_PREDICTREQUEST, - output_type=_PREDICTREPLY, - serialized_options=None, - ), -]) -_sym_db.RegisterServiceDescriptor(_MSSERVICE) - -DESCRIPTOR.services_by_name['MSService'] = _MSSERVICE - -# @@protoc_insertion_point(module_scope) diff --git a/serving/core/ms_service_pb2_grpc.py b/serving/core/ms_service_pb2_grpc.py deleted file mode 100644 index e6f21a0de3..0000000000 --- a/serving/core/ms_service_pb2_grpc.py +++ /dev/null @@ -1,96 +0,0 @@ -# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! -import grpc - -import ms_service_pb2 as ms__service__pb2 - - -class MSServiceStub(object): - """Missing associated documentation comment in .proto file""" - - def __init__(self, channel): - """Constructor. - - Args: - channel: A grpc.Channel. - """ - self.Predict = channel.unary_unary( - '/ms_serving.MSService/Predict', - request_serializer=ms__service__pb2.PredictRequest.SerializeToString, - response_deserializer=ms__service__pb2.PredictReply.FromString, - ) - self.Test = channel.unary_unary( - '/ms_serving.MSService/Test', - request_serializer=ms__service__pb2.PredictRequest.SerializeToString, - response_deserializer=ms__service__pb2.PredictReply.FromString, - ) - - -class MSServiceServicer(object): - """Missing associated documentation comment in .proto file""" - - def Predict(self, request, context): - """Missing associated documentation comment in .proto file""" - context.set_code(grpc.StatusCode.UNIMPLEMENTED) - context.set_details('Method not implemented!') - raise NotImplementedError('Method not implemented!') - - def Test(self, request, context): - """Missing associated documentation comment in .proto file""" - context.set_code(grpc.StatusCode.UNIMPLEMENTED) - context.set_details('Method not implemented!') - raise NotImplementedError('Method not implemented!') - - -def add_MSServiceServicer_to_server(servicer, server): - rpc_method_handlers = { - 'Predict': grpc.unary_unary_rpc_method_handler( - servicer.Predict, - request_deserializer=ms__service__pb2.PredictRequest.FromString, - response_serializer=ms__service__pb2.PredictReply.SerializeToString, - ), - 'Test': grpc.unary_unary_rpc_method_handler( - servicer.Test, - request_deserializer=ms__service__pb2.PredictRequest.FromString, - response_serializer=ms__service__pb2.PredictReply.SerializeToString, - ), - } - generic_handler = grpc.method_handlers_generic_handler( - 'ms_serving.MSService', rpc_method_handlers) - server.add_generic_rpc_handlers((generic_handler,)) - - - # This class is part of an EXPERIMENTAL API. -class MSService(object): - """Missing associated documentation comment in .proto file""" - - @staticmethod - def Predict(request, - target, - options=(), - channel_credentials=None, - call_credentials=None, - compression=None, - wait_for_ready=None, - timeout=None, - metadata=None): - return grpc.experimental.unary_unary(request, target, '/ms_serving.MSService/Predict', - ms__service__pb2.PredictRequest.SerializeToString, - ms__service__pb2.PredictReply.FromString, - options, channel_credentials, - call_credentials, compression, wait_for_ready, timeout, metadata) - - @staticmethod - def Test(request, - target, - options=(), - channel_credentials=None, - call_credentials=None, - compression=None, - wait_for_ready=None, - timeout=None, - metadata=None): - return grpc.experimental.unary_unary(request, target, '/ms_serving.MSService/Test', - ms__service__pb2.PredictRequest.SerializeToString, - ms__service__pb2.PredictReply.FromString, - options, channel_credentials, - call_credentials, compression, wait_for_ready, timeout, metadata) diff --git a/serving/cpp_example/ms_server.cc b/serving/cpp_example/ms_server.cc deleted file mode 100644 index f6021ef000..0000000000 --- a/serving/cpp_example/ms_server.cc +++ /dev/null @@ -1,67 +0,0 @@ -/** - * Copyright 2020 Huawei Technologies Co., Ltd - * - * 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. - */ -#include -#include -#include -#include - -#include "./ms_service.grpc.pb.h" - -using grpc::Server; -using grpc::ServerBuilder; -using grpc::ServerContext; -using grpc::Status; -using ms_serving::MSService; -using ms_serving::PredictReply; -using ms_serving::PredictRequest; - -// Logic and data behind the server's behavior. -class MSServiceImpl final : public MSService::Service { - Status Predict(ServerContext *context, const PredictRequest *request, PredictReply *reply) override { - std::cout << "server eval" << std::endl; - return Status::OK; - } -}; - -void RunServer() { - std::string server_address("0.0.0.0:50051"); - MSServiceImpl service; - - grpc::EnableDefaultHealthCheckService(true); - grpc::reflection::InitProtoReflectionServerBuilderPlugin(); - auto option = grpc::MakeChannelArgumentOption(GRPC_ARG_ALLOW_REUSEPORT, 0); - - ServerBuilder builder; - builder.SetOption(std::move(option)); - // Listen on the given address without any authentication mechanism. - builder.AddListeningPort(server_address, grpc::InsecureServerCredentials()); - // Register "service" as the instance through which we'll communicate with - // clients. In this case it corresponds to an *synchronous* service. - builder.RegisterService(&service); - // Finally assemble the server. - std::unique_ptr server(builder.BuildAndStart()); - std::cout << "Server listening on " << server_address << std::endl; - - // Wait for the server to shutdown. Note that some other thread must be - // responsible for shutting down the server for this call to ever return. - server->Wait(); -} - -int main(int argc, char **argv) { - RunServer(); - - return 0; -} diff --git a/serving/cpp_example/CMakeLists.txt b/serving/example/cpp_client/CMakeLists.txt similarity index 51% rename from serving/cpp_example/CMakeLists.txt rename to serving/example/cpp_client/CMakeLists.txt index bcb6ab0462..44df268e58 100644 --- a/serving/cpp_example/CMakeLists.txt +++ b/serving/example/cpp_client/CMakeLists.txt @@ -1,6 +1,6 @@ cmake_minimum_required(VERSION 3.5.1) -project(HelloWorld C CXX) +project(MSClient C CXX) set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11") add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0) @@ -12,17 +12,33 @@ find_package(Threads REQUIRED) # Find Protobuf installation # Looks for protobuf-config.cmake file installed by Protobuf's cmake installation. -set(protobuf_MODULE_COMPATIBLE TRUE) -find_package(Protobuf CONFIG REQUIRED) -message(STATUS "Using protobuf ${protobuf_VERSION}") +option(GRPC_PATH "set grpc path") +if(GRPC_PATH) + set(CMAKE_PREFIX_PATH ${GRPC_PATH}) + set(protobuf_MODULE_COMPATIBLE TRUE) + find_package(Protobuf CONFIG REQUIRED) + message(STATUS "Using protobuf ${protobuf_VERSION}, CMAKE_PREFIX_PATH : ${CMAKE_PREFIX_PATH}") +elseif(NOT GRPC_PATH) + if (EXISTS ${grpc_ROOT}/lib64) + set(gRPC_DIR "${grpc_ROOT}/lib64/cmake/grpc") + elseif(EXISTS ${grpc_ROOT}/lib) + set(gRPC_DIR "${grpc_ROOT}/lib/cmake/grpc") + endif() + add_library(protobuf::libprotobuf ALIAS protobuf::protobuf) + add_executable(protobuf::libprotoc ALIAS protobuf::protoc) + message(STATUS "serving using grpc_DIR : " ${gRPC_DIR}) +elseif(NOT gRPC_DIR AND NOT GRPC_PATH) + message("please check gRPC. If the client is compiled separately，you can use the command: cmake -D GRPC_PATH=xxx") + message("XXX is the gRPC installation path") +endif() set(_PROTOBUF_LIBPROTOBUF protobuf::libprotobuf) set(_REFLECTION gRPC::grpc++_reflection) -if (CMAKE_CROSSCOMPILING) - find_program(_PROTOBUF_PROTOC protoc) -else () - set(_PROTOBUF_PROTOC $) -endif () +if(CMAKE_CROSSCOMPILING) + find_program(_PROTOBUF_PROTOC protoc) +else() + set(_PROTOBUF_PROTOC $) +endif() # Find gRPC installation # Looks for gRPCConfig.cmake file installed by gRPC's cmake installation. @@ -30,14 +46,14 @@ find_package(gRPC CONFIG REQUIRED) message(STATUS "Using gRPC ${gRPC_VERSION}") set(_GRPC_GRPCPP gRPC::grpc++) -if (CMAKE_CROSSCOMPILING) - find_program(_GRPC_CPP_PLUGIN_EXECUTABLE grpc_cpp_plugin) -else () - set(_GRPC_CPP_PLUGIN_EXECUTABLE $) -endif () +if(CMAKE_CROSSCOMPILING) + find_program(_GRPC_CPP_PLUGIN_EXECUTABLE grpc_cpp_plugin) +else() + set(_GRPC_CPP_PLUGIN_EXECUTABLE $) +endif() # Proto file -get_filename_component(hw_proto "../ms_service.proto" ABSOLUTE) +get_filename_component(hw_proto "../../ms_service.proto" ABSOLUTE) get_filename_component(hw_proto_path "${hw_proto}" PATH) # Generated sources @@ -59,13 +75,13 @@ add_custom_command( include_directories("${CMAKE_CURRENT_BINARY_DIR}") # Targets greeter_[async_](client|server) -foreach (_target - ms_client ms_server) - add_executable(${_target} "${_target}.cc" - ${hw_proto_srcs} - ${hw_grpc_srcs}) - target_link_libraries(${_target} - ${_REFLECTION} - ${_GRPC_GRPCPP} - ${_PROTOBUF_LIBPROTOBUF}) -endforeach () +foreach(_target + ms_client) + add_executable(${_target} "${_target}.cc" + ${hw_proto_srcs} + ${hw_grpc_srcs}) + target_link_libraries(${_target} + ${_REFLECTION} + ${_GRPC_GRPCPP} + ${_PROTOBUF_LIBPROTOBUF}) +endforeach() diff --git a/serving/cpp_example/ms_client.cc b/serving/example/cpp_client/ms_client.cc similarity index 73% rename from serving/cpp_example/ms_client.cc rename to serving/example/cpp_client/ms_client.cc index 3be4a7798d..3a9cac77e4 100644 --- a/serving/cpp_example/ms_client.cc +++ b/serving/example/cpp_client/ms_client.cc @@ -211,77 +211,12 @@ PredictRequest ReadBertInput() { return request; } -PredictRequest ReadLenetInput() { - size_t size; - auto buf = ReadFile("lenet_img.bin", &size); - if (buf == nullptr) { - std::cout << "read file failed" << std::endl; - return PredictRequest(); - } - PredictRequest request; - auto cur = buf; - if (size > 0) { - Tensor data; - TensorShape shape; - // set type - data.set_tensor_type(ms_serving::MS_FLOAT32); - - // set shape - shape.add_dims(size / sizeof(float)); - *data.mutable_tensor_shape() = shape; - - // set data - data.set_data(cur, size); - *request.add_data() = data; - } - std::cout << "get input data size " << size << std::endl; - return request; -} - -PredictRequest ReadOtherInput(const std::string &data_file) { - size_t size; - auto buf = ReadFile(data_file.c_str(), &size); - if (buf == nullptr) { - std::cout << "read file failed" << std::endl; - return PredictRequest(); - } - PredictRequest request; - auto cur = buf; - if (size > 0) { - Tensor data; - TensorShape shape; - // set type - data.set_tensor_type(ms_serving::MS_FLOAT32); - - // set shape - shape.add_dims(size / sizeof(float)); - *data.mutable_tensor_shape() = shape; - - // set data - data.set_data(cur, size); - *request.add_data() = data; - } - std::cout << "get input data size " << size << std::endl; - return request; -} - -template -void print_array_item(const DT *data, size_t size) { - for (size_t i = 0; i < size && i < 100; i++) { - std::cout << data[i] << '\t'; - if ((i + 1) % 10 == 0) { - std::cout << std::endl; - } - } - std::cout << std::endl; -} - class MSClient { public: explicit MSClient(std::shared_ptr channel) : stub_(MSService::NewStub(channel)) {} ~MSClient() = default; - std::string Predict(const std::string &type, const std::string &data_file) { + std::string Predict(const std::string &type) { // Data we are sending to the server. PredictRequest request; if (type == "add") { @@ -299,10 +234,6 @@ class MSClient { *request.add_data() = data; } else if (type == "bert") { request = ReadBertInput(); - } else if (type == "lenet") { - request = ReadLenetInput(); - } else if (type == "other") { - request = ReadOtherInput(data_file); } else { std::cout << "type only support bert or add, but input is " << type << std::endl; } @@ -325,20 +256,6 @@ class MSClient { // Act upon its status. if (status.ok()) { - for (size_t i = 0; i < reply.result_size(); i++) { - auto result = reply.result(i); - if (result.tensor_type() == ms_serving::DataType::MS_FLOAT32) { - print_array_item(reinterpret_cast(result.data().data()), result.data().size() / sizeof(float)); - } else if (result.tensor_type() == ms_serving::DataType::MS_INT32) { - print_array_item(reinterpret_cast(result.data().data()), - result.data().size() / sizeof(int32_t)); - } else if (result.tensor_type() == ms_serving::DataType::MS_UINT32) { - print_array_item(reinterpret_cast(result.data().data()), - result.data().size() / sizeof(uint32_t)); - } else { - std::cout << "output datatype " << result.tensor_type() << std::endl; - } - } return "RPC OK"; } else { std::cout << status.error_code() << ": " << status.error_message() << std::endl; @@ -360,8 +277,6 @@ int main(int argc, char **argv) { std::string arg_target_str("--target"); std::string type; std::string arg_type_str("--type"); - std::string arg_data_str("--data"); - std::string data = "default_data.bin"; if (argc > 2) { { // parse target @@ -389,33 +304,19 @@ int main(int argc, char **argv) { if (arg_val2[start_pos] == '=') { type = arg_val2.substr(start_pos + 1); } else { - std::cout << "The only correct argument syntax is --type=" << std::endl; + std::cout << "The only correct argument syntax is --target=" << std::endl; return 0; } } else { type = "add"; } } - if (argc > 3) { - // parse type - std::string arg_val3 = argv[3]; - size_t start_pos = arg_val3.find(arg_data_str); - if (start_pos != std::string::npos) { - start_pos += arg_data_str.size(); - if (arg_val3[start_pos] == '=') { - data = arg_val3.substr(start_pos + 1); - } else { - std::cout << "The only correct argument syntax is --data=" << std::endl; - return 0; - } - } - } } else { target_str = "localhost:5500"; type = "add"; } MSClient client(grpc::CreateChannel(target_str, grpc::InsecureChannelCredentials())); - std::string reply = client.Predict(type, data); + std::string reply = client.Predict(type); std::cout << "client received: " << reply << std::endl; return 0; diff --git a/serving/example/export_model/add_model.py b/serving/example/export_model/add_model.py new file mode 100644 index 0000000000..caf354cc5a --- /dev/null +++ b/serving/example/export_model/add_model.py @@ -0,0 +1,46 @@ +# Copyright 2020 Huawei Technologies Co., Ltd +# +# 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. +# ============================================================================ +import numpy as np + +import mindspore.context as context +import mindspore.nn as nn +from mindspore.ops import operations as P +from mindspore import Tensor +from mindspore.train.serialization import export + +context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") + +class Net(nn.Cell): + def __init__(self): + super(Net, self).__init__() + self.add = P.TensorAdd() + + def construct(self, x_, y_): + return self.add(x_, y_) + +x = np.ones(4).astype(np.float32) +y = np.ones(4).astype(np.float32) + +def export_net(): + add = Net() + output = add(Tensor(x), Tensor(y)) + export(add, Tensor(x), Tensor(y), file_name='tensor_add.pb', file_format='BINARY') + print(x) + print(y) + print(output.asnumpy()) + +if __name__ == "__main__": + export_net() + \ No newline at end of file diff --git a/serving/python_example/ms_client_test_call.py b/serving/example/python_client/ms_client.py similarity index 52% rename from serving/python_example/ms_client_test_call.py rename to serving/example/python_client/ms_client.py index 56643d8351..898c543563 100644 --- a/serving/python_example/ms_client_test_call.py +++ b/serving/example/python_client/ms_client.py @@ -19,28 +19,25 @@ import ms_service_pb2_grpc def run(): - channel = grpc.insecure_channel('localhost:50051') + channel = grpc.insecure_channel('localhost:5050') stub = ms_service_pb2_grpc.MSServiceStub(channel) - # request = ms_service_pb2.EvalRequest() - # request.name = 'haha' - # response = stub.Eval(request) - # print("ms client received: " + response.message) - request = ms_service_pb2.PredictRequest() - request.data.tensor_shape.dims.extend([32, 1, 32, 32]) - request.data.tensor_type = ms_service_pb2.MS_FLOAT32 - request.data.data = (np.ones([32, 1, 32, 32]).astype(np.float32) * 0.01).tobytes() - - request.label.tensor_shape.dims.extend([32]) - request.label.tensor_type = ms_service_pb2.MS_INT32 - request.label.data = np.ones([32]).astype(np.int32).tobytes() - - result = stub.Test(request) - #result_np = np.frombuffer(result.result.data, dtype=np.float32).reshape(result.result.tensor_shape.dims) - print("ms client test call received: ") - #print(result_np) - + x = request.data.add() + x.tensor_shape.dims.extend([4]) + x.tensor_type = ms_service_pb2.MS_FLOAT32 + x.data = (np.ones([4]).astype(np.float32)).tobytes() + + y = request.data.add() + y.tensor_shape.dims.extend([4]) + y.tensor_type = ms_service_pb2.MS_FLOAT32 + y.data = (np.ones([4]).astype(np.float32)).tobytes() + + result = stub.Predict(request) + print(result) + result_np = np.frombuffer(result.result[0].data, dtype=np.float32).reshape(result.result[0].tensor_shape.dims) + print("ms client received: ") + print(result_np) if __name__ == '__main__': run() diff --git a/serving/python_example/ms_client.py b/serving/python_example/ms_client.py deleted file mode 100644 index d567d089b8..0000000000 --- a/serving/python_example/ms_client.py +++ /dev/null @@ -1,57 +0,0 @@ -# Copyright 2020 Huawei Technologies Co., Ltd -# -# 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. -# ============================================================================ -import grpc -import numpy as np -import ms_service_pb2 -import ms_service_pb2_grpc - - -def run(): - channel = grpc.insecure_channel('localhost:50051') - stub = ms_service_pb2_grpc.MSServiceStub(channel) - # request = ms_service_pb2.PredictRequest() - # request.name = 'haha' - # response = stub.Eval(request) - # print("ms client received: " + response.message) - - request = ms_service_pb2.PredictRequest() - request.data.tensor_shape.dims.extend([32, 1, 32, 32]) - request.data.tensor_type = ms_service_pb2.MS_FLOAT32 - request.data.data = (np.ones([32, 1, 32, 32]).astype(np.float32) * 0.01).tobytes() - - request.label.tensor_shape.dims.extend([32]) - request.label.tensor_type = ms_service_pb2.MS_INT32 - request.label.data = np.ones([32]).astype(np.int32).tobytes() - - result = stub.Predict(request) - #result_np = np.frombuffer(result.result.data, dtype=np.float32).reshape(result.result.tensor_shape.dims) - print("ms client received: ") - #print(result_np) - - # future_list = [] - # times = 1000 - # for i in range(times): - # async_future = stub.Eval.future(request) - # future_list.append(async_future) - # print("async call, future list add item " + str(i)); - # - # for i in range(len(future_list)): - # async_result = future_list[i].result() - # print("ms client async get result of item " + str(i)) - - - -if __name__ == '__main__': - run() diff --git a/serving/python_example/ms_server.py b/serving/python_example/ms_server.py deleted file mode 100644 index f538856804..0000000000 --- a/serving/python_example/ms_server.py +++ /dev/null @@ -1,55 +0,0 @@ -# Copyright 2020 Huawei Technologies Co., Ltd -# -# 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. -# ============================================================================ -from concurrent import futures -import time -import grpc -import numpy as np -import ms_service_pb2 -import ms_service_pb2_grpc -import test_cpu_lenet -from mindspore import Tensor - -class MSService(ms_service_pb2_grpc.MSServiceServicer): - def Predict(self, request, context): - request_data = request.data - request_label = request.label - - data_from_buffer = np.frombuffer(request_data.data, dtype=np.float32) - data_from_buffer = data_from_buffer.reshape(request_data.tensor_shape.dims) - data = Tensor(data_from_buffer) - - label_from_buffer = np.frombuffer(request_label.data, dtype=np.int32) - label_from_buffer = label_from_buffer.reshape(request_label.tensor_shape.dims) - label = Tensor(label_from_buffer) - - result = test_cpu_lenet.test_lenet(data, label) - result_reply = ms_service_pb2.PredictReply() - result_reply.result.tensor_shape.dims.extend(result.shape()) - result_reply.result.data = result.asnumpy().tobytes() - return result_reply - -def serve(): - server = grpc.server(futures.ThreadPoolExecutor(max_workers=1)) - ms_service_pb2_grpc.add_MSServiceServicer_to_server(MSService(), server) - server.add_insecure_port('[::]:50051') - server.start() - try: - while True: - time.sleep(60*60*24) # one day in seconds - except KeyboardInterrupt: - server.stop(0) - -if __name__ == '__main__': - serve() diff --git a/serving/python_example/test_cpu_lenet.py b/serving/python_example/test_cpu_lenet.py deleted file mode 100644 index a609c9b924..0000000000 --- a/serving/python_example/test_cpu_lenet.py +++ /dev/null @@ -1,91 +0,0 @@ -# Copyright 2019 Huawei Technologies Co., Ltd -# -# 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. -# ============================================================================ -import numpy as np -import mindspore.context as context -import mindspore.nn as nn -from mindspore import Tensor -from mindspore.nn import TrainOneStepCell, WithLossCell -from mindspore.nn.optim import Momentum -from mindspore.ops import operations as P -import ms_service_pb2 - - -class LeNet(nn.Cell): - def __init__(self): - super(LeNet, self).__init__() - self.relu = P.ReLU() - self.batch_size = 32 - - self.conv1 = nn.Conv2d(1, 6, kernel_size=5, stride=1, padding=0, has_bias=False, pad_mode='valid') - self.conv2 = nn.Conv2d(6, 16, kernel_size=5, stride=1, padding=0, has_bias=False, pad_mode='valid') - self.pool = nn.MaxPool2d(kernel_size=2, stride=2) - self.reshape = P.Reshape() - self.fc1 = nn.Dense(400, 120) - self.fc2 = nn.Dense(120, 84) - self.fc3 = nn.Dense(84, 10) - - def construct(self, input_x): - output = self.conv1(input_x) - output = self.relu(output) - output = self.pool(output) - output = self.conv2(output) - output = self.relu(output) - output = self.pool(output) - output = self.reshape(output, (self.batch_size, -1)) - output = self.fc1(output) - output = self.relu(output) - output = self.fc2(output) - output = self.relu(output) - output = self.fc3(output) - return output - - -def train(net, data, label): - learning_rate = 0.01 - momentum = 0.9 - - optimizer = Momentum(filter(lambda x: x.requires_grad, net.get_parameters()), learning_rate, momentum) - criterion = nn.SoftmaxCrossEntropyWithLogits(is_grad=False, sparse=True) - net_with_criterion = WithLossCell(net, criterion) - train_network = TrainOneStepCell(net_with_criterion, optimizer) # optimizer - train_network.set_train() - res = train_network(data, label) - print("+++++++++Loss+++++++++++++") - print(res) - print("+++++++++++++++++++++++++++") - assert res - return res - -def test_lenet(data, label): - context.set_context(mode=context.GRAPH_MODE, device_target="CPU") - net = LeNet() - return train(net, data, label) - -if __name__ == '__main__': - tensor = ms_service_pb2.Tensor() - tensor.tensor_shape.dim.extend([32, 1, 32, 32]) - # tensor.tensor_shape.dim.add() = 1 - # tensor.tensor_shape.dim.add() = 32 - # tensor.tensor_shape.dim.add() = 32 - tensor.tensor_type = ms_service_pb2.MS_FLOAT32 - tensor.data = np.ones([32, 1, 32, 32]).astype(np.float32).tobytes() - - data_from_buffer = np.frombuffer(tensor.data, dtype=np.float32) - print(tensor.tensor_shape.dim) - data_from_buffer = data_from_buffer.reshape(tensor.tensor_shape.dim) - print(data_from_buffer.shape) - input_data = Tensor(data_from_buffer * 0.01) - input_label = Tensor(np.ones([32]).astype(np.int32)) - test_lenet(input_data, input_label)