未验证 提交 24fda392 编写于 作者: D dzhwinter 提交者: GitHub

Feature/global context (#6537)

* "add DeviceContextPool"

* "add devicecontextpool in pybind"

* "add comments in python side "

* "fix static link error"

* "fix CI error"

* "add executor.py"

* "fix CI error"

* "add with gpu macro"

* "remove comment out codes"

* "add TODO items"

* "update init devices"
上级 93a2d9c5
...@@ -58,3 +58,6 @@ cc_test(var_type_inference_test SRCS var_type_inference_test.cc DEPS op_registry ...@@ -58,3 +58,6 @@ cc_test(var_type_inference_test SRCS var_type_inference_test.cc DEPS op_registry
proto_desc) proto_desc)
cc_library(selected_rows SRCS selected_rows.cc DEPS tensor) cc_library(selected_rows SRCS selected_rows.cc DEPS tensor)
cc_test(selected_rows_test SRCS selected_rows_test.cc DEPS selected_rows) cc_test(selected_rows_test SRCS selected_rows_test.cc DEPS selected_rows)
cc_library(init SRCS init.cc DEPS gflags executor place stringpiece)
cc_test(init_test SRCS init_test.cc DEPS init)
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 <sstream> #include <sstream>
#include <vector> #include <vector>
......
...@@ -33,32 +33,12 @@ namespace framework { ...@@ -33,32 +33,12 @@ namespace framework {
const std::string kFeedOpType = "feed"; const std::string kFeedOpType = "feed";
const std::string kFetchOpType = "fetch"; const std::string kFetchOpType = "fetch";
Executor::Executor(const std::vector<platform::Place>& places) : own_(true) { DeviceContextPool* DeviceContextPool::pool = nullptr;
PADDLE_ENFORCE_GT(places.size(), 0);
device_contexts_.resize(places.size());
for (size_t i = 0; i < places.size(); i++) {
if (platform::is_cpu_place(places[i])) {
device_contexts_[i] = new platform::CPUDeviceContext(
boost::get<platform::CPUPlace>(places[i]));
} else if (platform::is_gpu_place(places[i])) {
#ifdef PADDLE_WITH_CUDA
device_contexts_[i] = new platform::CUDADeviceContext(
boost::get<platform::GPUPlace>(places[i]));
#else
PADDLE_THROW(
"'GPUPlace' is not supported, Please re-compile with WITH_GPU "
"option");
#endif
}
}
}
Executor::~Executor() { Executor::Executor(const std::vector<platform::Place>& places) {
if (own_) { DeviceContextPool& pool = DeviceContextPool::Get();
for (auto& device_context : device_contexts_) { auto borrowed_contexts = pool.Borrow(places);
delete device_context; device_contexts_.swap(borrowed_contexts);
}
}
} }
static void CreateTensor(Variable* var, VarDesc::VarType var_type) { static void CreateTensor(Variable* var, VarDesc::VarType var_type) {
...@@ -132,8 +112,5 @@ void Executor::Run(const ProgramDescBind& pdesc, Scope* scope, int block_id, ...@@ -132,8 +112,5 @@ void Executor::Run(const ProgramDescBind& pdesc, Scope* scope, int block_id,
} }
} }
Executor::Executor(const platform::DeviceContext& device)
: device_contexts_({&device}), own_(false) {}
} // namespace framework } // namespace framework
} // namespace paddle } // namespace paddle
...@@ -14,19 +14,98 @@ limitations under the License. */ ...@@ -14,19 +14,98 @@ limitations under the License. */
#pragma once #pragma once
#include <map>
#include <unordered_map>
#include "paddle/framework/op_info.h" #include "paddle/framework/op_info.h"
#include "paddle/framework/program_desc.h" #include "paddle/framework/program_desc.h"
#include "paddle/framework/scope.h" #include "paddle/framework/scope.h"
#include "paddle/framework/tensor.h" #include "paddle/framework/tensor.h"
#include "paddle/platform/device_context.h"
namespace paddle { namespace paddle {
namespace framework { namespace framework {
class DeviceContextPool {
public:
static DeviceContextPool& Get() {
PADDLE_ENFORCE_NOT_NULL(pool, "Need to Create DeviceContextPool first!");
return *pool;
}
static DeviceContextPool& Create(const std::vector<platform::Place>& places) {
if (pool == nullptr) {
pool = new DeviceContextPool(places);
}
return *pool;
}
std::vector<const platform::DeviceContext*> Borrow(
const std::vector<platform::Place>& places) {
PADDLE_ENFORCE_GT(places.size(), 0);
PADDLE_ENFORCE_LE(places.size(), device_contexts_.size());
std::vector<const platform::DeviceContext*> borrowed_contexts;
for (auto& place : places) {
auto range = device_contexts_.equal_range(place);
if (range.first == range.second) {
PADDLE_THROW(
"'Place' is not supported, Please re-compile with WITH_GPU "
"option");
}
// TODO(dzhwinter) : assign the first found device. Will enhanced later.
// device load balancer maybe useful here.
borrowed_contexts.emplace_back(range.first->second);
}
return borrowed_contexts;
}
explicit DeviceContextPool(const std::vector<platform::Place>& places) {
PADDLE_ENFORCE_GT(places.size(), 0);
for (size_t i = 0; i < places.size(); i++) {
if (platform::is_cpu_place(places[i])) {
device_contexts_.emplace(
places[i], new platform::CPUDeviceContext(
boost::get<platform::CPUPlace>(places[i])));
} else if (platform::is_gpu_place(places[i])) {
#ifdef PADDLE_WITH_CUDA
device_contexts_.emplace(
places[i], new platform::CUDADeviceContext(
boost::get<platform::GPUPlace>(places[i])));
#else
PADDLE_THROW(
"'GPUPlace' is not supported, Please re-compile with WITH_GPU "
"option");
#endif
}
}
}
~DeviceContextPool() {}
private:
static DeviceContextPool* pool;
struct Hash {
std::hash<int> hash_;
size_t operator()(const platform::Place& place) const {
return hash_(place.which());
}
};
std::unordered_multimap<const platform::Place, const platform::DeviceContext*,
Hash>
device_contexts_;
DISABLE_COPY_AND_ASSIGN(DeviceContextPool);
};
class Executor { class Executor {
public: public:
// TODO(dzhwinter) : Do not rely on this function, it will be removed
explicit Executor(const platform::DeviceContext& device)
: Executor(std::vector<platform::Place>({device.GetPlace()})) {}
explicit Executor(const platform::Place& place)
: Executor(std::vector<platform::Place>({place})) {}
explicit Executor(const std::vector<platform::Place>& places); explicit Executor(const std::vector<platform::Place>& places);
explicit Executor(const platform::DeviceContext& devices);
~Executor();
/* @Brief /* @Brief
* Runtime evaluation of the given ProgramDesc under certain Scope * Runtime evaluation of the given ProgramDesc under certain Scope
...@@ -39,7 +118,6 @@ class Executor { ...@@ -39,7 +118,6 @@ class Executor {
private: private:
std::vector<const platform::DeviceContext*> device_contexts_; std::vector<const platform::DeviceContext*> device_contexts_;
bool own_;
}; };
} // namespace framework } // namespace framework
......
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 <algorithm>
#include <string>
#include "paddle/framework/executor.h"
#include "paddle/framework/init.h"
#include "paddle/platform/place.h"
#include "paddle/string/piece.h"
namespace paddle {
namespace framework {
std::once_flag gflags_init_flag;
// TODO(qijun) move init gflags to init.cc
void InitGflags(std::vector<std::string> &argv) {
std::call_once(gflags_init_flag, [&]() {
int argc = argv.size();
char **arr = new char *[argv.size()];
std::string line;
for (size_t i = 0; i < argv.size(); i++) {
arr[i] = &argv[i][0];
line += argv[i];
line += ' ';
}
google::ParseCommandLineFlags(&argc, &arr, true);
VLOG(1) << "Init commandline: " << line;
});
}
bool InitDevices(const std::vector<std::string> &devices) {
// device format
// CPU
// GPU:1
// TODO(dzhwinter) : add device format annotation for users.
std::vector<platform::Place> places;
for (auto &device : devices) {
auto p = string::Piece(device);
if (string::Find(p, ':', 0) == string::Piece::npos) {
places.emplace_back(platform::CPUPlace());
} else if (string::HasPrefix(p, "GPU")) {
#ifdef PADDLE_WITH_CUDA
auto pos = string::RFind(p, ':', string::Piece::npos);
auto number = device.substr(pos + 1);
places.emplace_back(platform::GPUPlace(std::stoi(number)));
#else
LOG(WARNING)
<< "'GPU' is not supported, Please re-compile with WITH_GPU option";
#endif
} else {
return false;
}
}
if (std::find_if(places.begin(), places.end(),
[&](const platform::Place &place) {
return platform::is_cpu_place(place);
}) == places.end()) {
places.emplace_back(platform::CPUPlace());
LOG(WARNING) << "Not specified any device, use CPU by Default.";
}
DeviceContextPool::Create(places);
return true;
return true;
}
} // namespace framework
} // namespace paddle
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#pragma once
#include <mutex>
#include "gflags/gflags.h"
#include "glog/logging.h"
namespace paddle {
namespace framework {
void InitGflags(std::vector<std::string> &argv);
bool InitDevices(const std::vector<std::string> &devices);
} // namespace framework
} // namespace paddle
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 "gtest/gtest.h"
#include "paddle/framework/init.h"
TEST(Init, InitDevices) {
using paddle::framework::InitDevices;
std::vector<std::string> ds1 = {"CPU"};
ASSERT_EQ(InitDevices(ds1), true);
#ifdef PADDLE_WITH_CUDA
std::vector<std::string> ds2 = {"CPU", "GPU:0", "GPU:1"};
ASSERT_EQ(InitDevices(ds2), true);
#endif
}
if(WITH_PYTHON) if(WITH_PYTHON)
cc_library(paddle_pybind SHARED cc_library(paddle_pybind SHARED
SRCS pybind.cc exception.cc protobuf.cc SRCS pybind.cc exception.cc protobuf.cc
DEPS pybind python backward proto_desc paddle_memory executor prune DEPS pybind python backward proto_desc paddle_memory executor prune init
${GLOB_OP_LIB}) ${GLOB_OP_LIB})
endif(WITH_PYTHON) endif(WITH_PYTHON)
......
...@@ -16,11 +16,11 @@ limitations under the License. */ ...@@ -16,11 +16,11 @@ limitations under the License. */
#include <mutex> // for call_once #include <mutex> // for call_once
#include <unordered_map> #include <unordered_map>
#include "gflags/gflags.h"
#include "paddle/framework/backward.h" #include "paddle/framework/backward.h"
#include "paddle/framework/executor.h" #include "paddle/framework/executor.h"
#include "paddle/framework/feed_fetch_method.h" #include "paddle/framework/feed_fetch_method.h"
#include "paddle/framework/framework.pb.h" #include "paddle/framework/framework.pb.h"
#include "paddle/framework/init.h"
#include "paddle/framework/lod_rank_table.h" #include "paddle/framework/lod_rank_table.h"
#include "paddle/framework/lod_tensor.h" #include "paddle/framework/lod_tensor.h"
#include "paddle/framework/lod_tensor_array.h" #include "paddle/framework/lod_tensor_array.h"
...@@ -51,24 +51,6 @@ static size_t UniqueIntegerGenerator(const std::string &prefix) { ...@@ -51,24 +51,6 @@ static size_t UniqueIntegerGenerator(const std::string &prefix) {
return generators[prefix].fetch_add(1); return generators[prefix].fetch_add(1);
} }
std::once_flag gflags_init_flag;
// TODO(qijun) move init gflags to init.cc
void InitGflags(std::vector<std::string> &argv) {
std::call_once(gflags_init_flag, [&]() {
int argc = argv.size();
char **arr = new char *[argv.size()];
std::string line;
for (size_t i = 0; i < argv.size(); i++) {
arr[i] = &argv[i][0];
line += argv[i];
line += ' ';
}
google::ParseCommandLineFlags(&argc, &arr, true);
VLOG(1) << "Init commandline: " << line;
});
}
bool IsCompileGPU() { bool IsCompileGPU() {
#ifndef PADDLE_WITH_CUDA #ifndef PADDLE_WITH_CUDA
return false; return false;
...@@ -438,7 +420,8 @@ All parameter, weight, gradient are variables in Paddle. ...@@ -438,7 +420,8 @@ All parameter, weight, gradient are variables in Paddle.
.def("run", &Executor::Run); .def("run", &Executor::Run);
m.def("unique_integer", UniqueIntegerGenerator); m.def("unique_integer", UniqueIntegerGenerator);
m.def("init_gflags", InitGflags); m.def("init_gflags", framework::InitGflags);
m.def("init_devices", &framework::InitDevices);
m.def("is_compile_gpu", IsCompileGPU); m.def("is_compile_gpu", IsCompileGPU);
m.def("set_feed_variable", framework::SetFeedVariable); m.def("set_feed_variable", framework::SetFeedVariable);
......
...@@ -46,6 +46,13 @@ class Executor(object): ...@@ -46,6 +46,13 @@ class Executor(object):
p.set_place(each) p.set_place(each)
act_places.append(p) act_places.append(p)
# TODO(dzhwinter) : consider that our fluid tests all written in
# GPUPlace(gpu_id), this will be changed in next PR.
if core.is_compile_gpu():
core.init_devices(["CPU", "GPU:0"])
else:
core.init_devices(["CPU"])
self.executor = core.Executor(act_places) self.executor = core.Executor(act_places)
self.places = places self.places = places
......
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