提交 24a80011 编写于 作者: D dongdaxiang

make -DWITH_PSLIB=ON compilable

上级 67b1d6d7
#windows treat symbolic file as a real file, which is different with unix
#We create a hidden file and compile it instead of origin source file.
function(windows_symbolic TARGET)
......@@ -22,9 +23,11 @@ endfunction()
add_subdirectory(ir)
add_subdirectory(details)
add_subdirectory(fleet)
#ddim lib
proto_library(framework_proto SRCS framework.proto)
proto_library(async_executor_proto SRCS data_feed.proto)
proto_library(trainer_desc_proto SRCS trainer_desc.proto)
cc_library(ddim SRCS ddim.cc DEPS eigen3 boost enforce)
cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
......@@ -129,9 +132,16 @@ cc_test(version_test SRCS version_test.cc DEPS version)
cc_library(proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS shape_inference op_info operator glog version)
cc_library(op_registry SRCS op_registry.cc DEPS op_proto_maker op_info operator glog proto_desc memory_optimize_helper)
if(WITH_NGRAPH)
cc_library(ngraph_bridge SRCS ngraph_bridge.cc DEPS operator framework_proto ngraph)
cc_library(ngraph_operator SRCS ngraph_operator.cc DEPS ngraph_bridge operator op_info device_context tensor scope glog
shape_inference data_transform lod_tensor profiler)
endif(WITH_NGRAPH)
nv_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry)
py_proto_compile(framework_py_proto SRCS framework.proto data_feed.proto)
py_proto_compile(trainer_py_proto SRCS trainer_desc.proto data_feed.proto)
#Generate an empty \
#__init__.py to make framework_py_proto as a valid python module.
add_custom_target(framework_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
......@@ -172,7 +182,11 @@ if(WITH_DISTRIBUTE)
set(DISTRIBUTE_COMPILE_FLAGS "-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor")
set_source_files_properties(executor.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
else()
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass variable_helper ${NGRAPH_EXE_DEPS})
if(WITH_NGRAPH)
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass ngraph_operator variable_helper)
else(WITH_NGRAPH)
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass variable_helper)
endif(WITH_NGRAPH)
cc_test(test_naive_executor SRCS naive_executor_test.cc DEPS naive_executor elementwise_add_op)
endif()
......@@ -184,9 +198,23 @@ cc_library(parallel_executor SRCS parallel_executor.cc DEPS
fast_threaded_ssa_graph_executor variable_helper)
if(WITH_PSLIB)
cc_library(async_executor SRCS async_executor.cc data_feed.cc data_feed_factory.cc executor_thread_worker.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass async_executor_proto variable_helper pslib_brpc pslib timer)
cc_library(async_executor SRCS async_executor.cc data_feed.cc data_feed_factory.cc
executor_thread_worker.cc multi_trainer.cc dist_multi_trainer.cc
trainer_factory.cc trainer.cc device_worker.cc hogwild_worker.cc
downpour_worker.cc pull_dense_worker.cc device_worker_factory.cc
DEPS op_registry device_context scope framework_proto
trainer_desc_proto glog lod_rank_table
feed_fetch_method graph_to_program_pass async_executor_proto
variable_helper pslib_brpc pslib timer)
else()
cc_library(async_executor SRCS async_executor.cc data_feed.cc data_feed_factory.cc executor_thread_worker.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass async_executor_proto variable_helper timer)
cc_library(async_executor SRCS async_executor.cc data_feed.cc data_feed_factory.cc
executor_thread_worker.cc multi_trainer.cc dist_multi_trainer.cc
trainer_factory.cc trainer.cc device_worker.cc hogwild_worker.cc
downpour_worker.cc pull_dense_worker.cc device_worker_factory.cc
DEPS op_registry device_context scope framework_proto
trainer_desc_proto glog lod_rank_table
feed_fetch_method graph_to_program_pass async_executor_proto
variable_helper timer)
endif(WITH_PSLIB)
......@@ -211,24 +239,3 @@ endif (NOT WIN32)
cc_library(dlpack_tensor SRCS dlpack_tensor.cc DEPS tensor dlpack)
cc_test(dlpack_tensor_test SRCS dlpack_tensor_test.cc DEPS dlpack_tensor glog)
# Get the current working branch
execute_process(
COMMAND git rev-parse --abbrev-ref HEAD
WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
OUTPUT_VARIABLE PADDLE_BRANCH
OUTPUT_STRIP_TRAILING_WHITESPACE
)
# Get the latest abbreviated commit hash of the working branch
execute_process(
COMMAND git log -1 --format=%h
WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
OUTPUT_VARIABLE PADDLE_COMMIT
OUTPUT_STRIP_TRAILING_WHITESPACE
)
message(STATUS "commit: ${PADDLE_COMMIT}")
message(STATUS "branch: ${PADDLE_BRANCH}")
configure_file(commit.h.in commit.h)
......@@ -26,6 +26,7 @@ limitations under the License. */
#include "paddle/fluid/framework/lod_tensor_array.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/framework/trainer_desc.pb.h"
#include "paddle/fluid/inference/io.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/pybind/pybind.h"
......@@ -56,52 +57,9 @@ void AsyncExecutor::GatherServers(const std::vector<uint64_t>& host_sign_list,
fleet_ptr_->GatherServers(host_sign_list, node_num);
}
void AsyncExecutor::InitModel() {
for (auto table_id : _param_config.dense_table_id) {
std::vector<paddle::ps::Region> regions;
for (auto& t : _param_config.dense_variable_name[table_id]) {
Variable* var = root_scope_->FindVar(t);
CHECK(var != nullptr) << "var[" << t << "] not found";
LoDTensor* tensor = var->GetMutable<LoDTensor>();
void AsyncExecutor::InitModel() {}
float* g = tensor->data<float>();
CHECK(g != nullptr) << "var[" << t << "] value not initialized";
float init_range = 0.2;
int rown = tensor->dims()[0];
init_range /= sqrt(rown);
std::normal_distribution<float> ndistr(0.0, 1.0);
for (auto i = 0u; i < tensor->numel(); ++i) {
g[i] = ndistr(local_random_engine()) * init_range;
}
paddle::ps::Region reg(g, tensor->numel());
regions.emplace_back(std::move(reg));
}
auto push_status = _pslib_ptr->_worker_ptr->push_dense_param(
regions.data(), regions.size(), table_id);
push_status.wait();
auto status = push_status.get();
if (status != 0) {
LOG(FATAL) << "push dense param failed, status[" << status << "]";
exit(-1);
}
}
}
void AsyncExecutor::SaveModel(const std::string& path) {
auto ret = _pslib_ptr->_worker_ptr->flush();
ret.wait();
ret = _pslib_ptr->_worker_ptr->save(path, 0);
ret.wait();
int32_t feasign_cnt = ret.get();
if (feasign_cnt == -1) { // (colourful-tree) TODO should be feasign_cnt < 0
LOG(FATAL) << "save model failed";
exit(-1);
}
}
void AsyncExecutor::SaveModel(const std::string& path) {}
void AsyncExecutor::RunFromFile(const ProgramDesc& main_program,
<<<<<<< HEAD
......
......@@ -27,6 +27,7 @@ limitations under the License. */
#include "paddle/fluid/framework/data_feed.pb.h"
#include "paddle/fluid/framework/executor.h"
#include "paddle/fluid/framework/executor_thread_worker.h"
#include "paddle/fluid/framework/fleet/fleet_wrapper.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/scope.h"
......@@ -62,11 +63,7 @@ class AsyncExecutor {
AsyncExecutor(Scope* scope, const platform::Place& place);
virtual ~AsyncExecutor() {}
void RunFromFile(const ProgramDesc& main_program,
const std::string& data_feed_desc_str,
const std::vector<std::string>& filelist,
const int thread_num,
const std::vector<std::string>& fetch_names,
const std::string& mode, const bool debug = false);
const std::string& trainer_desc_str, const bool debug);
void InitServer(const std::string& dist_desc, int index);
void InitWorker(const std::string& dist_desc,
......
/* Copyright (c) 2018 PaddlePaddle Authors. 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. */
#include "paddle/fluid/framework/device_worker.h"
namespace paddle {
namespace framework {
void DeviceWorker::SetRootScope(Scope* root_scope) { root_scope_ = root_scope; }
void DeviceWorker::SetDataFeed(const std::shared_ptr<DataFeed>& data_feed) {
device_reader_ = data_feed;
}
} // namespace framework
} // namespace paddle
cc_library(fleet_wrapper SRCS fleet_wrapper.cc)
/* Copyright (c) 2016 PaddlePaddle Authors. 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. */
#include "paddle/fluid/framework/trainer.h"
namespace paddle {
namespace framework {
void TrainerBase::SetScope(Scope* root_scope) { root_scope_ = root_scope; }
void TrainerBase::Initialize(const TrainerDesc& trainer_desc) { return; }
} // end namespace framework
} // end namespace paddle
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