提交 be04d99f 编写于 作者: M minqiyang

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into revert_vlog

test=develop
......@@ -199,8 +199,11 @@ elseif(CMAKE_BUILD_TYPE STREQUAL "MinSizeRel")
list(APPEND CUDA_NVCC_FLAGS ${CMAKE_CXX_FLAGS_RELEASE})
endif()
else(NOT WIN32)
list(APPEND CUDA_NVCC_FLAGS "--compiler-options;/bigobj")
if(CMAKE_BUILD_TYPE STREQUAL "Debug")
list(APPEND CUDA_NVCC_FLAGS "-g -G")
list(APPEND CUDA_NVCC_FLAGS "-g -G")
# match the cl's _ITERATOR_DEBUG_LEVEL
list(APPEND CUDA_NVCC_FLAGS "-D_DEBUG")
elseif(CMAKE_BUILD_TYPE STREQUAL "Release")
list(APPEND CUDA_NVCC_FLAGS "-O3 -DNDEBUG")
else()
......
......@@ -26,7 +26,7 @@ ExternalProject_Add(
extern_pybind
${EXTERNAL_PROJECT_LOG_ARGS}
GIT_REPOSITORY "https://github.com/pybind/pybind11.git"
GIT_TAG "v2.1.1"
GIT_TAG "v2.2.4"
PREFIX ${PYBIND_SOURCE_DIR}
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
......
......@@ -349,10 +349,17 @@ function(cc_test TARGET_NAME)
set(oneValueArgs "")
set(multiValueArgs SRCS DEPS ARGS)
cmake_parse_arguments(cc_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
if(WIN32)
list(APPEND win32_deps shlwapi)
if("${cc_test_DEPS};" MATCHES "python;")
list(REMOVE_ITEM cc_test_DEPS python)
list(APPEND win32_deps ${PYTHON_LIBRARIES})
endif()
endif(WIN32)
add_executable(${TARGET_NAME} ${cc_test_SRCS})
target_link_libraries(${TARGET_NAME} ${cc_test_DEPS} paddle_gtest_main lod_tensor memory gtest gflags glog)
if(WIN32)
target_link_libraries(${TARGET_NAME} shlwapi)
target_link_libraries(${TARGET_NAME} ${win32_deps})
endif(WIN32)
add_dependencies(${TARGET_NAME} ${cc_test_DEPS} paddle_gtest_main lod_tensor memory gtest gflags glog)
add_test(NAME ${TARGET_NAME}
......@@ -683,7 +690,7 @@ function(py_test TARGET_NAME)
set(multiValueArgs SRCS DEPS ARGS ENVS)
cmake_parse_arguments(py_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
add_test(NAME ${TARGET_NAME}
COMMAND env FLAGS_init_allocated_mem=true FLAGS_cudnn_deterministic=true
COMMAND ${CMAKE_COMMAND} -E env FLAGS_init_allocated_mem=true FLAGS_cudnn_deterministic=true
FLAGS_cpu_deterministic=true
PYTHONPATH=${PADDLE_BINARY_DIR}/python ${py_test_ENVS}
${PYTHON_EXECUTABLE} -u ${py_test_SRCS} ${py_test_ARGS}
......
......@@ -26,10 +26,10 @@ paddle.fluid.release_memory ArgSpec(args=['input_program', 'skip_opt_set'], vara
paddle.fluid.DistributeTranspilerConfig.__init__
paddle.fluid.ParallelExecutor.__init__ ArgSpec(args=['self', 'use_cuda', 'loss_name', 'main_program', 'share_vars_from', 'exec_strategy', 'build_strategy', 'num_trainers', 'trainer_id', 'scope'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 1, 0, None))
paddle.fluid.ParallelExecutor.run ArgSpec(args=['self', 'fetch_list', 'feed', 'feed_dict', 'return_numpy'], varargs=None, keywords=None, defaults=(None, None, True))
paddle.fluid.ExecutionStrategy.__init__ __init__(self: paddle.fluid.core.ExecutionStrategy) -> None
paddle.fluid.BuildStrategy.GradientScaleStrategy.__init__ __init__(self: paddle.fluid.core.GradientScaleStrategy, arg0: int) -> None
paddle.fluid.BuildStrategy.ReduceStrategy.__init__ __init__(self: paddle.fluid.core.ReduceStrategy, arg0: int) -> None
paddle.fluid.BuildStrategy.__init__ __init__(self: paddle.fluid.core.BuildStrategy) -> None
paddle.fluid.ExecutionStrategy.__init__ __init__(self: paddle.fluid.core.ParallelExecutor.ExecutionStrategy) -> None
paddle.fluid.BuildStrategy.GradientScaleStrategy.__init__ __init__(self: paddle.fluid.core.ParallelExecutor.BuildStrategy.GradientScaleStrategy, arg0: int) -> None
paddle.fluid.BuildStrategy.ReduceStrategy.__init__ __init__(self: paddle.fluid.core.ParallelExecutor.BuildStrategy.ReduceStrategy, arg0: int) -> None
paddle.fluid.BuildStrategy.__init__ __init__(self: paddle.fluid.core.ParallelExecutor.BuildStrategy) -> None
paddle.fluid.create_lod_tensor ArgSpec(args=['data', 'recursive_seq_lens', 'place'], varargs=None, keywords=None, defaults=None)
paddle.fluid.create_random_int_lodtensor ArgSpec(args=['recursive_seq_lens', 'base_shape', 'place', 'low', 'high'], varargs=None, keywords=None, defaults=None)
paddle.fluid.io.save_vars ArgSpec(args=['executor', 'dirname', 'main_program', 'vars', 'predicate', 'filename'], varargs=None, keywords=None, defaults=(None, None, None, None))
......
......@@ -116,14 +116,9 @@ cc_test(op_proto_maker_test SRCS op_proto_maker_test.cc DEPS op_proto_maker)
cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto)
cc_library(shape_inference SRCS shape_inference.cc DEPS ddim attribute device_context)
if (NOT WIN32)
cc_library(transfer_scope_cache SRCS transfer_scope_cache.cc DEPS scope framework_proto device_context)
cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope glog
shape_inference data_transform lod_tensor profiler transfer_scope_cache)
else()
cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope glog
shape_inference data_transform lod_tensor)
endif(NOT WIN32)
cc_test(operator_test SRCS operator_test.cc DEPS operator op_registry device_context)
......
......@@ -23,7 +23,7 @@ namespace paddle {
namespace framework {
namespace details {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
AllReduceOpHandle::AllReduceOpHandle(ir::Node *node,
const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
......@@ -74,7 +74,7 @@ void AllReduceOpHandle::RunImpl() {
}
if (platform::is_gpu_place(lod_tensors[0]->place())) {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
PADDLE_ENFORCE(nccl_ctxs_, "nccl_ctxs should not be nullptr.");
int dtype = -1;
size_t numel = 0;
......
......@@ -20,7 +20,7 @@
#include "paddle/fluid/framework/details/op_handle_base.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
#include "paddle/fluid/platform/nccl_helper.h"
#endif
......@@ -29,7 +29,7 @@ namespace framework {
namespace details {
struct AllReduceOpHandle : public OpHandleBase {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
AllReduceOpHandle(ir::Node *node, const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
const platform::NCCLContextMap *ctxs);
......@@ -49,7 +49,7 @@ struct AllReduceOpHandle : public OpHandleBase {
private:
std::vector<Scope *> local_scopes_;
std::vector<platform::Place> places_;
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
const platform::NCCLContextMap *nccl_ctxs_;
#endif
};
......
......@@ -82,7 +82,7 @@ void BroadcastOpHandle::BroadcastOneVar(
});
}
} else {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
VarHandle *out_handle = nullptr;
int root_id = boost::get<platform::CUDAPlace>(in_tensor.place()).device;
std::vector<std::function<void()>> broadcast_calls;
......
......@@ -24,7 +24,7 @@
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/platform/device_context.h"
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
#include "paddle/fluid/platform/nccl_helper.h"
#endif
......@@ -34,7 +34,7 @@ namespace details {
struct BroadcastOpHandle : public OpHandleBase {
public:
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
BroadcastOpHandle(ir::Node *node, const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
const platform::NCCLContextMap *nccl_ctxs)
......@@ -68,7 +68,7 @@ struct BroadcastOpHandle : public OpHandleBase {
std::vector<Scope *> local_scopes_;
std::vector<platform::Place> places_;
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
const platform::NCCLContextMap *nccl_ctxs_;
#endif
......
......@@ -42,7 +42,7 @@ struct TestBroadcastOpHandle {
std::vector<std::unique_ptr<ir::Node>> nodes_;
std::vector<p::Place> place_list_;
bool use_gpu_;
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
std::unique_ptr<platform::NCCLContextMap> nccl_ctxs_;
#endif
......@@ -50,7 +50,7 @@ struct TestBroadcastOpHandle {
for (size_t j = 0; j < ctxs_.size(); ++j) {
ctxs_[j]->Wait();
}
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
if (nccl_ctxs_) {
nccl_ctxs_->WaitAll();
}
......@@ -60,7 +60,7 @@ struct TestBroadcastOpHandle {
void InitCtxOnGpu(bool use_gpu) {
use_gpu_ = use_gpu;
if (use_gpu_) {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
int count = p::GetCUDADeviceCount();
if (count <= 1) {
LOG(WARNING) << "Cannot test multi-gpu Broadcast, because the CUDA "
......@@ -84,7 +84,7 @@ struct TestBroadcastOpHandle {
place_list_.push_back(p);
ctxs_.emplace_back(new p::CPUDeviceContext(p));
}
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
nccl_ctxs_.reset(nullptr);
#endif
}
......@@ -106,14 +106,14 @@ struct TestBroadcastOpHandle {
nodes_.emplace_back(
ir::CreateNodeForTest("node0", ir::Node::Type::kOperation));
if (use_gpu_) {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
op_handle_ = new BroadcastOpHandle(nodes_.back().get(), local_scopes_,
place_list_, nccl_ctxs_.get());
#else
PADDLE_THROW("CUDA is not support.");
#endif
} else {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
op_handle_ = new BroadcastOpHandle(nodes_.back().get(), local_scopes_,
place_list_, nccl_ctxs_.get());
#else
......
......@@ -96,7 +96,7 @@ std::unique_ptr<ir::Graph> BuildStrategy::Apply(
const std::string &loss_var_name,
const std::unordered_set<std::string> &param_names,
const std::vector<Scope *> &local_scopes,
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
const bool use_cuda, platform::NCCLContextMap *nccl_ctxs) const {
#else
const bool use_cuda) const {
......@@ -118,7 +118,7 @@ std::unique_ptr<ir::Graph> BuildStrategy::Apply(
pass->Erase("local_scopes");
pass->SetNotOwned<const std::vector<Scope *>>("local_scopes",
&local_scopes);
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
platform::NCCLContextMap *nctx = use_cuda ? nccl_ctxs : nullptr;
pass->Erase("nccl_ctxs");
pass->SetNotOwned<platform::NCCLContextMap>("nccl_ctxs", nctx);
......
......@@ -23,7 +23,7 @@
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/enforce.h"
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
#include "paddle/fluid/platform/nccl_helper.h"
#endif
......@@ -98,7 +98,7 @@ struct BuildStrategy {
const std::string &loss_var_name,
const std::unordered_set<std::string> &param_names,
const std::vector<Scope *> &local_scopes,
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
const bool use_cuda, platform::NCCLContextMap *nccl_ctxs) const;
#else
const bool use_cuda) const;
......
......@@ -20,7 +20,7 @@ namespace paddle {
namespace framework {
namespace details {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
DataBalanceOpHandle::DataBalanceOpHandle(
ir::Node *node, const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
......
......@@ -19,7 +19,7 @@
#include "paddle/fluid/framework/details/op_handle_base.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
#include "paddle/fluid/platform/nccl_helper.h"
#endif
......@@ -29,7 +29,7 @@ namespace details {
struct DataBalanceOpHandle : public OpHandleBase {
public:
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
DataBalanceOpHandle(ir::Node *node, const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
const platform::NCCLContextMap *ctxs);
......
......@@ -25,7 +25,7 @@
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/platform/device_context.h"
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
#include "paddle/fluid/platform/nccl_helper.h"
#endif
......@@ -35,7 +35,7 @@ namespace details {
struct FusedBroadcastOpHandle : public BroadcastOpHandle {
public:
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
FusedBroadcastOpHandle(ir::Node *node,
const std::vector<Scope *> local_scopes,
const std::vector<platform::Place> &places,
......
......@@ -44,14 +44,14 @@ struct TestFusedBroadcastOpHandle : TestBroadcastOpHandle {
nodes_.emplace_back(
ir::CreateNodeForTest("fused_broadcast", ir::Node::Type::kOperation));
if (use_gpu_) {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
op_handle_ = new FusedBroadcastOpHandle(
nodes_.back().get(), local_scopes_, place_list_, nccl_ctxs_.get());
#else
PADDLE_THROW("CUDA is not supported.");
#endif
} else {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
op_handle_ = new FusedBroadcastOpHandle(
nodes_.back().get(), local_scopes_, place_list_, nccl_ctxs_.get());
#else
......
......@@ -142,7 +142,7 @@ void MultiDevSSAGraphBuilder::Init() const {
places_ = Get<const std::vector<platform::Place>>(kPlaces);
local_scopes_ = Get<const std::vector<Scope *>>(kLocalScopes);
strategy_ = Get<const BuildStrategy>(kStrategy);
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
nccl_ctxs_ = &Get<platform::NCCLContextMap>("nccl_ctxs");
#endif
......@@ -431,7 +431,7 @@ std::unique_ptr<ir::Graph> MultiDevSSAGraphBuilder::ApplyImpl(
}
}
bool use_gpu = false;
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
use_gpu = nccl_ctxs_ != nullptr;
#endif
......@@ -478,7 +478,7 @@ bool MultiDevSSAGraphBuilder::IsSparseGradient(const std::string &og) const {
void MultiDevSSAGraphBuilder::SetCommunicationContext(
OpHandleBase *op_handle, const platform::Place &p) const {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
if (nccl_ctxs_ == nullptr) {
op_handle->SetDeviceContext(p,
platform::DeviceContextPool::Instance().Get(p));
......@@ -492,7 +492,7 @@ void MultiDevSSAGraphBuilder::SetCommunicationContext(
void MultiDevSSAGraphBuilder::CreateBroadcastOp(ir::Graph *result,
const std::string &p_name,
size_t src_dev_id) const {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
auto *op_handle = new BroadcastOpHandle(
result->CreateEmptyNode("broadcast", ir::Node::Type::kOperation),
local_scopes_, places_, nccl_ctxs_);
......@@ -522,7 +522,7 @@ void MultiDevSSAGraphBuilder::CreateBroadcastOp(ir::Graph *result,
void MultiDevSSAGraphBuilder::CreateFusedBroadcastOp(
ir::Graph *result,
const std::vector<std::unordered_set<std::string>> &bcast_varnames) const {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
auto *op_handle = new FusedBroadcastOpHandle(
result->CreateEmptyNode("fused_broadcast", ir::Node::Type::kOperation),
local_scopes_, places_, nccl_ctxs_);
......@@ -568,7 +568,7 @@ void MultiDevSSAGraphBuilder::CreateComputationalOp(ir::Graph *result,
void MultiDevSSAGraphBuilder::InsertAllReduceOp(ir::Graph *result,
const std::string &og) const {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
result->Get<GraphOps>(kGraphOps).emplace_back(new AllReduceOpHandle(
result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation),
local_scopes_, places_, nccl_ctxs_));
......@@ -597,7 +597,7 @@ void MultiDevSSAGraphBuilder::InsertAllReduceOp(ir::Graph *result,
void MultiDevSSAGraphBuilder::InsertDataBalanceOp(
ir::Graph *result, const std::vector<std::string> &datas) const {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
result->Get<GraphOps>(kGraphOps).emplace_back(new DataBalanceOpHandle(
result->CreateEmptyNode("data_balance", ir::Node::Type::kOperation),
local_scopes_, places_, nccl_ctxs_));
......@@ -694,7 +694,7 @@ void MultiDevSSAGraphBuilder::CreateComputationalOps(ir::Graph *result,
VarHandle *MultiDevSSAGraphBuilder::CreateReduceOp(ir::Graph *result,
const std::string &og,
int dst_dev_id) const {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
result->Get<GraphOps>(kGraphOps).emplace_back(new ReduceOpHandle(
result->CreateEmptyNode("reduce", ir::Node::Type::kOperation),
local_scopes_, places_, nccl_ctxs_));
......
......@@ -40,7 +40,7 @@ class MultiDevSSAGraphBuilder : public ir::Pass {
size_t device_id) const;
void Init() const;
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
mutable platform::NCCLContextMap *nccl_ctxs_;
#endif
......
......@@ -125,7 +125,7 @@ void ReduceOpHandle::RunImpl() {
}
});
} else if (paddle::platform::is_gpu_place(lod_tensors[0]->place())) {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
auto pre_in = pre_in_var->Get<framework::LoDTensor>();
VariableVisitor::ShareDimsAndLoD(*pre_in_var, out_var);
VariableVisitor::GetMutableTensor(out_var).mutable_data(
......
......@@ -23,7 +23,7 @@
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/platform/device_context.h"
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
#include "paddle/fluid/platform/nccl_helper.h"
#endif
......@@ -35,7 +35,7 @@ struct ReduceOpHandle : public OpHandleBase {
std::vector<Scope *> local_scopes_;
std::vector<platform::Place> places_;
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
const platform::NCCLContextMap *nccl_ctxs_;
ReduceOpHandle(ir::Node *node, const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
......
......@@ -35,7 +35,7 @@ struct TestReduceOpHandle {
std::vector<p::Place> gpu_list_;
std::vector<std::unique_ptr<p::DeviceContext>> ctxs_;
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
std::unique_ptr<platform::NCCLContextMap> nccl_ctxs_;
#endif
......@@ -43,7 +43,7 @@ struct TestReduceOpHandle {
for (size_t j = 0; j < ctxs_.size(); ++j) {
ctxs_[j]->Wait();
}
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
if (nccl_ctxs_) {
nccl_ctxs_->WaitAll();
}
......@@ -53,7 +53,7 @@ struct TestReduceOpHandle {
void InitCtxOnGpu(bool use_gpu) {
use_gpu_ = use_gpu;
if (use_gpu) {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
int count = p::GetCUDADeviceCount();
if (count <= 1) {
LOG(WARNING) << "Cannot test multi-gpu Broadcast, because the CUDA "
......@@ -77,7 +77,7 @@ struct TestReduceOpHandle {
gpu_list_.push_back(p);
ctxs_.emplace_back(new p::CPUDeviceContext(p));
}
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
nccl_ctxs_.reset(nullptr);
#endif
}
......@@ -99,14 +99,14 @@ struct TestReduceOpHandle {
nodes.emplace_back(new ir::Node("node"));
if (use_gpu_) {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
op_handle_.reset(new ReduceOpHandle(nodes.back().get(), local_scopes_,
gpu_list_, nccl_ctxs_.get()));
#else
PADDLE_THROW("CUDA is not support.");
#endif
} else {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
op_handle_.reset(new ReduceOpHandle(nodes.back().get(), local_scopes_,
gpu_list_, nccl_ctxs_.get()));
#else
......
......@@ -15,7 +15,10 @@
#include "paddle/fluid/framework/ir/is_test_pass.h"
#include <gtest/gtest.h>
#ifdef _WIN32
#undef FALSE
#undef TRUE
#endif
namespace paddle {
namespace framework {
namespace ir {
......
......@@ -26,10 +26,8 @@ limitations under the License. */
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/memory/memory.h"
#if !defined(_WIN32)
#include "paddle/fluid/recordio/scanner.h"
#include "paddle/fluid/recordio/writer.h"
#endif // _WIN32
namespace paddle {
namespace framework {
......@@ -305,7 +303,6 @@ void DeserializeFromStream(std::istream &is, LoDTensor *tensor,
TensorFromStream(is, static_cast<Tensor *>(tensor), dev_ctx);
}
#if !defined(_WIN32)
void WriteToRecordIO(recordio::Writer *writer,
const std::vector<LoDTensor> &tensor,
const platform::DeviceContext &dev_ctx) {
......@@ -335,19 +332,7 @@ bool ReadFromRecordIO(recordio::Scanner *scanner,
return true;
}
#else
class Writer {};
class Scanner {};
void WriteToRecordIO(recordio::Writer *writer,
const std::vector<LoDTensor> &tensor,
const platform::DeviceContext &dev_ctx) {}
bool ReadFromRecordIO(recordio::Scanner *scanner,
const platform::DeviceContext &dev_ctx,
std::vector<LoDTensor> *result_ptr) {
PADDLE_ENFORCE("windows didn't supported recordio!.");
return true;
}
#endif // _WIN32
std::vector<LoDTensor> LoDTensor::SplitLoDTensor(
const std::vector<platform::Place> places) const {
check_memory_size();
......
......@@ -274,7 +274,6 @@ TEST(LoD, ConvertToOffsetBasedLoD) {
EXPECT_EQ(offset_lod, expected);
}
#if !defined(_WIN32)
template <typename T>
static void TestRecordIO() {
LoDTensor tensor;
......@@ -321,7 +320,6 @@ TEST(LoDTensor, RecordIO) {
TestRecordIO<float>();
TestRecordIO<double>();
}
#endif // !defined(_WIN32)
} // namespace framework
} // namespace paddle
......@@ -149,17 +149,14 @@ void OperatorBase::Run(const Scope& scope, const platform::Place& place) {
#endif
}
// The profile has a process-wide mutex, results in serious performance issue
// in concurrency scenerio. Here use an `if` to fix this issue.
// Please not remove the `if`, ask @Superjomn if there are any concern.
#ifndef _WIN32
// The profile has a process-wide mutex, results in serious performance issue
// in concurrency scenerio. Here use an `if` to fix this issue.
// Please not remove the `if`, ask @Superjomn if there are any concern.
if (platform::IsProfileEnabled()) {
platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
platform::RecordEvent record_event(Type(), pool.Get(place));
RunImpl(scope, place);
} else // NOLINT
#endif
{
} else {
RunImpl(scope, place);
}
VLOG(3) << place << " " << DebugStringEx(&scope);
......
......@@ -19,6 +19,7 @@
#include "paddle/fluid/inference/analysis/ut_helper.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_inference_pass.h"
#include "paddle/fluid/platform/port.h"
namespace paddle {
namespace inference {
......@@ -75,7 +76,7 @@ void TestWord2vecPrediction(const std::string& model_path) {
0.000932706};
const size_t num_elements = outputs.front().data.length() / sizeof(float);
// The outputs' buffers are in CPU memory.
for (size_t i = 0; i < std::min(5UL, num_elements); i++) {
for (size_t i = 0; i < std::min((size_t)5UL, num_elements); i++) {
LOG(INFO) << "data: "
<< static_cast<float*>(outputs.front().data.data())[i];
PADDLE_ENFORCE(static_cast<float*>(outputs.front().data.data())[i],
......
......@@ -56,7 +56,6 @@ bool AnalysisPredictor::Init(
const std::shared_ptr<framework::Scope> &parent_scope,
const std::shared_ptr<framework::ProgramDesc> &program) {
VLOG(3) << "Predictor::init()";
#if !defined(_WIN32)
if (FLAGS_profile) {
LOG(WARNING) << "Profiler is actived, might affect the performance";
LOG(INFO) << "You can turn off by set gflags '-profile false'";
......@@ -64,7 +63,6 @@ bool AnalysisPredictor::Init(
: platform::ProfilerState::kCPU;
platform::EnableProfiler(tracking_device);
}
#endif
// no matter with or without MKLDNN
paddle::platform::SetNumThreads(config_.cpu_math_library_num_threads());
......@@ -520,12 +518,10 @@ bool AnalysisPredictor::LoadParameters() {
}
AnalysisPredictor::~AnalysisPredictor() {
#if !defined(_WIN32)
if (FLAGS_profile) {
platform::DisableProfiler(platform::EventSortingKey::kTotal,
"./profile.log");
}
#endif
if (sub_scope_) {
scope_->DeleteScope(sub_scope_);
}
......
......@@ -64,7 +64,6 @@ void NativePaddlePredictor::PrepareFeedFetch() {
bool NativePaddlePredictor::Init(
std::shared_ptr<framework::Scope> parent_scope) {
VLOG(3) << "Predictor::init()";
#if !defined(_WIN32)
if (FLAGS_profile) {
LOG(WARNING) << "Profiler is actived, might affect the performance";
LOG(INFO) << "You can turn off by set gflags '-profile false'";
......@@ -73,7 +72,6 @@ bool NativePaddlePredictor::Init(
: platform::ProfilerState::kCPU;
platform::EnableProfiler(tracking_device);
}
#endif
// no matter with or without MKLDNN
paddle::platform::SetNumThreads(config_.cpu_math_library_num_threads());
......@@ -121,12 +119,10 @@ bool NativePaddlePredictor::Init(
}
NativePaddlePredictor::~NativePaddlePredictor() {
#if !defined(_WIN32)
if (FLAGS_profile) {
platform::DisableProfiler(platform::EventSortingKey::kTotal,
"./profile.log");
}
#endif
if (sub_scope_) {
scope_->DeleteScope(sub_scope_);
}
......
......@@ -15,10 +15,6 @@
#pragma once
#include <glog/logging.h>
#if !defined(_WIN32)
#include <sys/time.h>
#else
#endif
#include <algorithm>
#include <chrono> // NOLINT
......@@ -28,6 +24,7 @@
#include <string>
#include <vector>
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/string/printf.h"
namespace paddle {
......
......@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include <gflags/gflags.h>
#include <sys/time.h>
#include <time.h>
#include <algorithm>
#include <fstream>
......
......@@ -178,11 +178,9 @@ void TestOneThreadPrediction(
warmup_timer.tic();
predictor->Run(inputs[0], outputs, batch_size);
PrintTime(batch_size, 1, 1, 0, warmup_timer.toc(), 1);
#if !defined(_WIN32)
if (FLAGS_profile) {
paddle::platform::ResetProfiler();
}
#endif
}
LOG(INFO) << "Run " << num_times << " times...";
......@@ -232,11 +230,9 @@ void TestMultiThreadPrediction(
warmup_timer.tic();
predictor->Run(inputs[0], outputs, batch_size);
PrintTime(batch_size, 1, num_threads, tid, warmup_timer.toc(), 1);
#if !defined(_WIN32)
if (FLAGS_profile) {
paddle::platform::ResetProfiler();
}
#endif
}
LOG(INFO) << "Thread " << tid << " run " << num_times << " times...";
......
......@@ -12,7 +12,6 @@ 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 <sys/time.h>
#include <time.h>
#include <fstream>
#include <thread> // NOLINT
......
......@@ -20,6 +20,7 @@ limitations under the License. */
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/inference/io.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/platform/profiler.h"
DECLARE_bool(use_mkldnn);
......
......@@ -46,7 +46,7 @@ void CreateInput(LoDTensor* ids, LoDTensor* scores) {
auto* scores_data = scores->mutable_data<float>(place);
vector<int64_t> _ids({4, 2, 5, 2, 1, 3, 3, 5, 2, 8, 2, 1});
vector<float> _scores(
{0.5, 0.3, 0.2, 0.6, 0.3, 0.1, 0.9, 0.5, 0.1, 0.7, 0.5, 0.1});
{0.5f, 0.3f, 0.2f, 0.6f, 0.3f, 0.1f, 0.9f, 0.5f, 0.1f, 0.7f, 0.5f, 0.1f});
for (int i = 0; i < 12; i++) {
ids_data[i] = _ids[i];
......@@ -80,7 +80,7 @@ TEST(DISABLED_beam_search_op, run) {
ASSERT_EQ(sids.lod(), sscores.lod());
vector<int> tids({4, 2, 3, 8});
vector<float> tscores({0.5, 0.6, 0.9, 0.7});
vector<float> tscores({0.5f, 0.6f, 0.9f, 0.7f});
for (int i = 0; i < 4; i++) {
ASSERT_EQ(tids[i], sids.data<int64_t>()[i]);
......
......@@ -12,7 +12,6 @@ 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 <sys/time.h>
#include <limits>
#include "glog/logging.h" // For VLOG
......@@ -20,6 +19,7 @@ limitations under the License. */
#include "paddle/fluid/operators/distributed/grpc_client.h"
#include "paddle/fluid/operators/distributed/grpc_serde.h"
#include "paddle/fluid/operators/distributed/request_handler.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/platform/profiler.h"
DECLARE_bool(rpc_disable_reuse_port);
......
......@@ -15,7 +15,6 @@ limitations under the License. */
#ifdef PADDLE_WITH_CUDA
#include <nccl.h>
#endif
#include <sys/time.h>
#include <thread> // NOLINT
#include "google/protobuf/io/coded_stream.h"
......@@ -26,6 +25,7 @@ limitations under the License. */
#include "paddle/fluid/operators/distributed/grpc_variable_response.h"
#include "paddle/fluid/operators/distributed/proto_encoder_helper.h"
#include "paddle/fluid/operators/distributed/sendrecvop_utils.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/platform/profiler.h"
namespace paddle {
......
......@@ -13,7 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <sys/time.h>
#include <iostream>
#include <string>
#include <vector>
......@@ -25,6 +25,7 @@ limitations under the License. */
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/framework/var_type.h"
#include "paddle/fluid/operators/distributed/sendrecvop_utils.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/operators/distributed/send_recv.grpc.pb.h"
#include "paddle/fluid/operators/distributed/send_recv.pb.h"
......
......@@ -15,12 +15,12 @@ limitations under the License. */
#ifdef PADDLE_WITH_CUDA
#include <nccl.h>
#endif
#include <sys/time.h>
#include <thread> // NOLINT
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/operators/distributed/sendrecvop_utils.h"
#include "paddle/fluid/operators/distributed/variable_response.h"
#include "paddle/fluid/platform/port.h"
DEFINE_bool(rpc_disable_reuse_port, false, "Disable SO_REUSEPORT or not.");
......
......@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <sys/time.h>
#include <iostream>
#include <string>
#include <vector>
......@@ -24,6 +23,7 @@ limitations under the License. */
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/framework/var_type.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/operators/distributed/send_recv.pb.h"
......
......@@ -12,7 +12,6 @@ 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 <sys/time.h>
#include <cmath>
#include <cstring>
#include <random>
......@@ -22,6 +21,7 @@ limitations under the License. */
#include "gtest/gtest.h"
#include "paddle/fluid/operators/math/cpu_vec.h"
#include "paddle/fluid/platform/port.h"
inline double GetCurrentUS() {
struct timeval time;
......
......@@ -14,9 +14,9 @@ limitations under the License. */
#include "paddle/fluid/operators/math/im2col.h"
#include <gtest/gtest.h>
#include <sys/time.h>
#include <vector>
#include "paddle/fluid/operators/math/im2col_cfo_cpu.h"
#include "paddle/fluid/platform/port.h"
template <typename DeviceContext, typename Place>
void testIm2col() {
......
......@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/math/jit_kernel.h"
#include <sys/time.h>
#include <cmath> // for exp
#include <cstring> // for memcpy
#include <random>
......@@ -22,6 +21,7 @@ limitations under the License. */
#include "gflags/gflags.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
#include "paddle/fluid/platform/port.h"
#ifdef PADDLE_WITH_MKLML
#include "paddle/fluid/platform/dynload/mklml.h"
......
......@@ -62,7 +62,7 @@ inline const char* cudnnGetErrorString(cudnnStatus_t status) {
#define CUDNN_ENFORCE(condition) \
do { \
cudnnStatus_t status = condition; \
auto status = condition; \
if (UNLIKELY(status != CUDNN_STATUS_SUCCESS)) { \
PADDLE_THROW(::paddle::platform::cudnnGetErrorString(status)); \
} \
......
......@@ -48,13 +48,13 @@ extern void EnforceCUDNNLoaded(const char* fn_name);
#else
#define DECLARE_DYNAMIC_LOAD_CUDNN_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
inline cudnnStatus_t operator()(Args... args) { \
return ::__name(args...); \
} \
}; \
#define DECLARE_DYNAMIC_LOAD_CUDNN_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
inline auto operator()(Args... args) { \
return ::__name(args...); \
} \
}; \
extern DynLoad__##__name __name
#endif
......
......@@ -19,7 +19,16 @@ limitations under the License. */
#include "gflags/gflags.h"
#include "paddle/fluid/platform/enforce.h"
DEFINE_double(fraction_of_gpu_memory_to_use, 0.92,
#ifndef _WIN32
const float fraction_of_gpu_memory_to_use = 0.92f;
#else
// fraction_of_gpu_memory_to_use cannot be too high on windows,
// since the win32 graphic sub-system can occupy some GPU memory
// which may lead to insufficient memory left for paddle
const float fraction_of_gpu_memory_to_use = 0.5f;
#endif
DEFINE_double(fraction_of_gpu_memory_to_use, fraction_of_gpu_memory_to_use,
"Allocate a trunk of gpu memory that is this fraction of the "
"total gpu memory size. Future memory usage will be allocated "
"from the trunk. If the trunk doesn't have enough gpu memory, "
......
......@@ -14,11 +14,11 @@
#pragma once
#include <ThreadPool.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <functional>
#include <memory>
#include "ThreadPool.h"
#include "paddle/fluid/platform/enforce.h"
namespace paddle {
......
......@@ -30,11 +30,12 @@ namespace pybind11 {
namespace detail {
// Can be replaced by a generic lambda in C++14
struct variant_caster_visitor : public boost::static_visitor<handle> {
struct __attribute__((visibility("hidden"))) paddle_variant_caster_visitor
: public boost::static_visitor<handle> {
return_value_policy policy;
handle parent;
variant_caster_visitor(return_value_policy policy, handle parent)
paddle_variant_caster_visitor(return_value_policy policy, handle parent)
: policy(policy), parent(parent) {}
template <class T>
......@@ -44,10 +45,10 @@ struct variant_caster_visitor : public boost::static_visitor<handle> {
};
template <class Variant>
struct variant_caster;
struct paddle_variant_caster;
template <template <class...> class V, class... Ts>
struct variant_caster<V<Ts...>> {
struct paddle_variant_caster<V<Ts...>> {
using Type = V<Ts...>;
template <typename T>
......@@ -90,7 +91,7 @@ struct variant_caster<V<Ts...>> {
static handle cast(Type const &src, return_value_policy policy,
handle parent) {
variant_caster_visitor visitor(policy, parent);
paddle_variant_caster_visitor visitor(policy, parent);
return boost::apply_visitor(visitor, src);
}
......@@ -101,7 +102,7 @@ struct variant_caster<V<Ts...>> {
// Add specialization for concrete variant type
template <class... Args>
struct type_caster<boost::variant<Args...>>
: variant_caster<boost::variant<Args...>> {};
: paddle_variant_caster<boost::variant<Args...>> {};
} // namespace detail
} // namespace pybind11
......
......@@ -86,12 +86,12 @@ bool IsCompiledWithDIST() {
#endif
}
PYBIND11_PLUGIN(core) {
PYBIND11_MODULE(core, m) {
// Not used, just make sure cpu_info.cc is linked.
paddle::platform::CpuTotalPhysicalMemory();
paddle::memory::allocation::UseAllocatorStrategyGFlag();
py::module m("core", "C++ core of PaddlePaddle");
m.doc() = "C++ core of PaddlePaddle";
// using framework in this function. Since it is inside a function, it will
// not cause namespace pollution.
......@@ -907,7 +907,6 @@ All parameter, weight, gradient are variables in Paddle.
});
BindRecordIOWriter(&m);
return m.ptr();
}
} // namespace pybind
} // namespace paddle
......@@ -21,7 +21,6 @@ limitations under the License. */
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/float16.h"
#include "pybind11/common.h"
#include "pybind11/numpy.h"
#include "pybind11/pybind11.h"
......
......@@ -12,9 +12,9 @@ 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. */
#ifndef _WIN32
#ifndef HL_WARPCTC_WRAP_H_
#define HL_WARPCTC_WRAP_H_
#include "ctc.h"
#include "hl_base.h"
......@@ -91,3 +91,4 @@ extern void hl_warpctc_get_workspace_size(const int* cpuLabelLengths,
size_t* bytes);
#endif // HL_WARPCTC_WRAP_H_
#endif
......@@ -132,11 +132,15 @@ inline pid_t gettid() {
uint64_t tid;
pthread_threadid_np(NULL, &tid);
#else
#ifndef _WIN32
#ifndef __NR_gettid
#define __NR_gettid 224
#endif
pid_t tid = syscall(__NR_gettid);
#endif
#else // _WIN32
pid_t tid = _getpid();
#endif // _WIN32
CHECK_NE((int)tid, -1);
return tid;
}
......
......@@ -14,10 +14,12 @@ limitations under the License. */
#pragma once
#ifndef _WIN32
#include <pthread.h>
#include <sys/syscall.h>
#include <sys/types.h>
#include <unistd.h>
#endif
#include <sys/types.h>
#include <map>
#include <mutex>
#include <random>
......
......@@ -14,7 +14,9 @@ limitations under the License. */
#pragma once
#ifndef _WIN32
#include <sys/syscall.h> // for syscall()
#endif
#include <sys/types.h>
#include <algorithm>
#include <cmath>
......@@ -40,6 +42,31 @@ inline int rand_r(unsigned int* seedp) {
}
#endif
#ifdef _WIN32
#define NOMINMAX // msvc max/min macro conflict with std::min/max
#include <windows.h>
template <typename T>
inline int __builtin_clz(const T& value) {
DWORD leadning_zero = 0;
if (_BitScanReverse(&leadning_zero, value)) {
return static_cast<int>(sizeof(T) * 8 - leadning_zero);
} else {
return static_cast<int>(0);
}
}
inline int __builtin_clzl(const unsigned long& value) {
return __builtin_clz(value);
}
inline int __builtin_clzll(const unsigned long long& value) {
return __builtin_clz(value);
}
#define pid_t int
#endif
/**
* Loop over the elements in a container
* TODO(yuyang18): It's this foreach useful? Why not use C++ 11 foreach,
......
......@@ -149,7 +149,7 @@ function cmake_gen() {
elif [ "$1" == "cp37-cp37m" ]; then
export LD_LIBRARY_PATH=/opt/_internal/cpython-3.7.0/lib/:${LD_LIBRARY_PATH}
export PATH=/opt/_internal/cpython-3.7.0/bin/:${PATH}
export PYTHON_FLAGS="-DPYTHON_EXECUTABLE:FILEPATH=/opt/_internal/cpython-3.7.0/bin/python3
export PYTHON_FLAGS="-DPYTHON_EXECUTABLE:FILEPATH=/opt/_internal/cpython-3.7.0/bin/python3.7
-DPYTHON_INCLUDE_DIR:PATH=/opt/_internal/cpython-3.7.0/include/python3.7m
-DPYTHON_LIBRARIES:FILEPATH=/opt/_internal/cpython-3.7.0/lib/libpython3.so"
fi
......
......@@ -3,8 +3,10 @@
if(WITH_TESTING)
add_library(paddle_test_main STATIC TestMain.cpp)
add_dependencies(paddle_test_main paddle_proto ${external_project_dependencies})
add_library(paddle_test_util STATIC TestUtil.cpp)
add_dependencies(paddle_test_util paddle_proto ${external_project_dependencies})
if(NOT WIN32)
add_library(paddle_test_util STATIC TestUtil.cpp)
add_dependencies(paddle_test_util paddle_proto ${external_project_dependencies})
endif(NOT WIN32)
if(NOT MOBILE_INFERENCE)
cc_library(paddle_gtest_main SRCS paddle_gtest_main.cc DEPS device_context memory gtest gflags)
endif()
......
......@@ -46,8 +46,8 @@ def _is_numpy_(var):
def _is_number_(var):
return isinstance(var, int) or isinstance(var, float) or (isinstance(
var, np.ndarray) and var.shape == (1, ))
return isinstance(var, int) or isinstance(var, np.int64) or isinstance(
var, float) or (isinstance(var, np.ndarray) and var.shape == (1, ))
def _is_number_or_matrix_(var):
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册