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Paddle/paddle/fluid/operators/reader/buffered_reader.cc

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// 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/operators/reader/buffered_reader.h"
#include <memory>
#include <utility>
#include <vector>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/platform/profiler.h"
namespace paddle {
namespace operators {
namespace reader {
BufferedReader::~BufferedReader() {
VLOG(1) << "~BufferedReader";
reader_->Shutdown();
while (!position_.empty()) {
position_.front().wait();
position_.pop();
}
#ifdef PADDLE_WITH_CUDA
if (platform::is_gpu_place(place_)) {
platform::SetDeviceId(boost::get<platform::CUDAPlace>(place_).device);
PADDLE_ENFORCE(cudaStreamDestroy(stream_));
for (auto &event : events_) {
PADDLE_ENFORCE(cudaEventDestroy(event));
}
}
#endif
}
BufferedReader::BufferedReader(
const std::shared_ptr<framework::ReaderBase> &reader,
const platform::Place &place, size_t buffer_size)
: framework::DecoratedReader(reader),
thread_pool_(1),
place_(place),
buffer_size_(buffer_size) {
VLOG(1) << "BufferedReader";
#ifdef PADDLE_WITH_CUDA
if (platform::is_gpu_place(place_)) {
platform::SetDeviceId(boost::get<platform::CUDAPlace>(place_).device);
compute_stream_ =
((platform::CUDADeviceContext *)(platform::DeviceContextPool::Instance()
.Get(place_)))
->stream();
events_.resize(buffer_size);
for (auto &event : events_) {
PADDLE_ENFORCE(cudaEventCreateWithFlags(&event, cudaEventDisableTiming));
}
PADDLE_ENFORCE(cudaStreamCreateWithFlags(&stream_, cudaStreamNonBlocking));
}
#endif
cpu_buffer_.resize(buffer_size);
gpu_buffer_.resize(buffer_size);
ReadTillBufferFullAsync();
}
void BufferedReader::ReadTillBufferFullAsync() {
PADDLE_ENFORCE_EQ(position_.size(), 0U);
for (size_t i = 0; i < buffer_size_; ++i) {
ReadAsync(i);
}
}
void BufferedReader::ReadAsync(size_t i) {
position_.emplace(thread_pool_.enqueue([this, i]() -> size_t {
TensorVec &cpu = cpu_buffer_[i];
reader_->ReadNext(&cpu);
if (cpu.empty()) {
return -1UL;
}
#ifdef PADDLE_WITH_CUDA
// NOTE(liangdun): using async copy instead of TensorCopySync
// TensorCopySync would block other stream, because TensorCopySync
// issues the copying command to the default stream, it will make two
// commands from different streams cannot run concurrently.
if (platform::is_gpu_place(place_)) {
TensorVec &gpu = gpu_buffer_[i];
if (gpu.empty()) {
gpu.resize(cpu.size());
} else {
PADDLE_ENFORCE_EQ(gpu.size(), cpu.size(),
"Input tensor number not matched");
}
std::vector<void *> gpu_ptrs;
gpu_ptrs.reserve(cpu.size());
for (size_t i = 0; i < cpu.size(); ++i) {
gpu[i].Resize(cpu[i].dims());
gpu[i].set_layout(cpu[i].layout());
gpu_ptrs.emplace_back(gpu[i].mutable_data(place_, cpu[i].type()));
}
// NOTE(zjl): cudaStreamWaitEvent() must be called after all
// gpu[i].mutable_data() is called, since some ops release
// gpu memory immediately without waiting gpu kernel ends
platform::SetDeviceId(boost::get<platform::CUDAPlace>(place_).device);
PADDLE_ENFORCE(cudaEventRecord(events_[i], compute_stream_));
PADDLE_ENFORCE(cudaStreamWaitEvent(stream_, events_[i], 0));
platform::RecordEvent record_event("BufferedReader:MemoryCopy");
for (size_t i = 0; i < cpu.size(); ++i) {
auto cpu_place = cpu[i].place();
auto cpu_ptr = cpu[i].data<void>();
auto gpu_ptr = gpu_ptrs[i];
auto size =
cpu[i].numel() * paddle::framework::SizeOfType(cpu[i].type());
if (platform::is_cuda_pinned_place(cpu_place)) {
memory::Copy(boost::get<platform::CUDAPlace>(place_), gpu_ptr,
boost::get<platform::CUDAPinnedPlace>(cpu_place),
cpu_ptr, size, stream_);
} else if ((platform::is_gpu_place(cpu_place))) {
memory::Copy(boost::get<platform::CUDAPlace>(place_), gpu_ptr,
boost::get<platform::CUDAPlace>(cpu_place), cpu_ptr,
size, stream_);
} else {
memory::Copy(boost::get<platform::CUDAPlace>(place_), gpu_ptr,
boost::get<platform::CPUPlace>(cpu_place), cpu_ptr, size,
stream_);
}
gpu[i].set_lod(cpu[i].lod());
}
PADDLE_ENFORCE(cudaStreamSynchronize(stream_));
}
#endif
return i;
}));
}
void BufferedReader::ShutdownImpl() {
VLOG(1) << "ShutdownImpl";
reader_->Shutdown();
while (!position_.empty()) {
position_.pop();
}
prev_pos_ = -1UL;
}
void BufferedReader::StartImpl() {
reader_->Start();
ReadTillBufferFullAsync();
}
void BufferedReader::ReadNextImpl(std::vector<framework::LoDTensor> *out) {
if (position_.empty()) {
out->clear();
return;
}
size_t i = position_.front().get();
position_.pop();
if (i == -1UL) {
ReadNextImpl(out);
return;
}
*out = std::move(platform::is_gpu_place(place_) ? gpu_buffer_[i]
: cpu_buffer_[i]);
// Do not push current position into ReadAsync. Push the previous position
// Since all computation in fluid are async, change the data of
// current position may cause data error.
if (prev_pos_ != -1Ul) {
ReadAsync(prev_pos_);
}
prev_pos_ = i;
}
} // namespace reader
} // namespace operators
} // namespace paddle