// 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 #include #include #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()) { auto &front = position_.front(); if (front.valid()) { front.wait(); } position_.pop(); } } BufferedReader::BufferedReader( const std::shared_ptr &reader, const platform::Place &place, size_t buffer_size) : framework::DecoratedReader(reader), thread_pool_(1), place_(place), buffer_size_(buffer_size) { VLOG(1) << "BufferedReader"; is_same_place_ = false; cpu_buffer_.resize(buffer_size); cuda_pinned_buffer_.resize(buffer_size); ReadTillBufferFullAsync(); } void BufferedReader::ReadTillBufferFullAsync() { 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 if (platform::is_gpu_place(place_)) { // NOTE: [Copy processing of different input devices] // We may accept input tensor in three different devices: // - CPUPlace // - CUDAPinnedPlace // - CUDAPlace // CUDA Stream Synchronizing is slow, in order to avoid Synchronizing // in BufferedReader thread, we do data copy as follows: // - If src Tensor on CPU memory, we copy it to CUDAPinned memory // - IF src Tensor on CUDAPinned memory, we use it directly // - IF src Tensor on CUDA memory, we use it directly platform::CUDAPinnedPlace cuda_pinned_place; TensorVec &cuda_pinned = cuda_pinned_buffer_[i]; if (cuda_pinned.empty()) { cuda_pinned.resize(cpu.size()); } else { PADDLE_ENFORCE_EQ( cuda_pinned.size(), cpu.size(), platform::errors::InvalidArgument( "Input tensor number on GPU and CPU devices are not matched.")); } std::vector cuda_pinned_ptrs; cuda_pinned_ptrs.reserve(cpu.size()); platform::RecordEvent record_event("BufferedReader:MemoryCopy"); for (size_t i = 0; i < cpu.size(); ++i) { if (platform::is_cpu_place(cpu[i].place())) { cuda_pinned[i].Resize(cpu[i].dims()); cuda_pinned[i].set_layout(cpu[i].layout()); cuda_pinned_ptrs.emplace_back( cuda_pinned[i].mutable_data(cuda_pinned_place, cpu[i].type())); auto size = cpu[i].numel() * paddle::framework::SizeOfType(cpu[i].type()); memory::Copy(cuda_pinned_place, cuda_pinned_ptrs[i], BOOST_GET_CONST(platform::CPUPlace, cpu[i].place()), cpu[i].data(), size); cuda_pinned[i].set_lod(cpu[i].lod()); } else { // we set same place flag & use cpu[i] directly is_same_place_ = true; } } } #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 *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_) && !is_same_place_) ? cuda_pinned_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