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190 lines
6.0 KiB
190 lines
6.0 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <sys/time.h>
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#include <algorithm>
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#include <chrono> // NOLINT
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#include <cstdlib>
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#include <fstream>
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#include <iostream>
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#include <memory>
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#include <sstream>
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#include <string>
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#include <unordered_map>
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#include <vector>
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#include "paddle/fluid/framework/reader.h"
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#include "paddle/fluid/framework/threadpool.h"
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#include "paddle/fluid/operators/reader/lod_tensor_blocking_queue.h"
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namespace paddle {
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namespace operators {
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namespace reader {
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enum ReaderThreadStatus { Running, Stopped };
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struct DataDesc {
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DataDesc(int batch_size, const std::vector<std::string>& file_names,
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const std::string& file_type, const std::string& file_format,
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const std::vector<int>& dense_slot_index,
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const std::vector<int>& sparse_slot_index,
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const std::vector<std::string>& sparse_slot_ids)
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: batch_size_(batch_size),
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file_names_(file_names),
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file_type_(file_type),
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file_format_(file_format),
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dense_slot_index_(dense_slot_index),
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sparse_slot_index_(sparse_slot_index),
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sparse_slot_ids_(sparse_slot_ids) {}
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const int batch_size_;
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const std::vector<std::string> file_names_;
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const std::string file_type_; // gzip or plain
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const std::string file_format_; // csv or svm
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// used for csv data format
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const std::vector<int> dense_slot_index_;
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const std::vector<int> sparse_slot_index_;
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// used for svm data format
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const std::vector<std::string> sparse_slot_ids_;
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};
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inline std::ostream& operator<<(std::ostream& os, const DataDesc& data_desc) {
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os << "data_desc:\n";
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os << "\tbatch_size -> " << data_desc.batch_size_ << "\n";
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os << "\tfile_type -> " << data_desc.file_type_ << "\n";
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os << "\tfile_format -> " << data_desc.file_format_ << "\n";
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os << "\tfile_names -> {";
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for (auto& file_name : data_desc.file_names_) {
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os << file_name << ",";
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}
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os << "}\n";
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os << "\tdense_slot_index -> {";
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for (auto& slot : data_desc.dense_slot_index_) {
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os << slot << ",";
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}
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os << "}\n";
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os << "\tsparse_slot_index_ -> {";
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for (auto& slot : data_desc.sparse_slot_index_) {
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os << slot << ",";
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}
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os << "}\n";
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os << "\tsparse_slot_ids_ -> {";
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for (auto& slot : data_desc.sparse_slot_ids_) {
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os << slot << ",";
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}
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os << "}\n";
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return os;
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}
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void ReadThread(const std::vector<std::string>& file_list,
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const DataDesc& data_desc, int thread_id,
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std::vector<ReaderThreadStatus>* thread_status,
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std::shared_ptr<LoDTensorBlockingQueue> queue);
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// monitor all running thread, if they are all stopped,
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// then push an empty data into LoDTensorBlockingQueue
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void MonitorThread(std::vector<ReaderThreadStatus>* thread_status,
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std::shared_ptr<LoDTensorBlockingQueue> queue);
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class CTRReader : public framework::FileReader {
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public:
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CTRReader(const std::shared_ptr<LoDTensorBlockingQueue>& queue,
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int thread_num, const DataDesc& data_desc)
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: data_desc_(data_desc) {
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PADDLE_ENFORCE_GT(thread_num, 0, "thread num should be larger then 0!");
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PADDLE_ENFORCE(queue != nullptr, "LoDTensorBlockingQueue must not be null");
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PADDLE_ENFORCE_GT(data_desc_.file_names_.size(), 0,
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"file list should not be empty");
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thread_num_ = std::min<size_t>(data_desc_.file_names_.size(), thread_num);
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queue_ = queue;
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SplitFiles();
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for (size_t i = 0; i < thread_num_; ++i) {
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read_thread_status_.push_back(Stopped);
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}
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}
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~CTRReader() { Shutdown(); }
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void ReadNext(std::vector<framework::LoDTensor>* out) override {
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bool success;
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*out = queue_->Pop(&success);
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if (!success) out->clear();
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}
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void Shutdown() override {
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VLOG(3) << "Shutdown reader";
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if (status_ == ReaderStatus::kStopped) {
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return;
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}
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// shutdown should stop all the reader thread
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for (auto& read_thread : read_threads_) {
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read_thread->join();
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}
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if (monitor_thread_) {
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monitor_thread_->join();
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}
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read_threads_.clear();
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monitor_thread_.reset(nullptr);
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queue_->Close();
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status_ = ReaderStatus::kStopped;
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}
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void Start() override {
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VLOG(3) << "Start reader";
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PADDLE_ENFORCE_EQ(read_threads_.size(), 0, "read thread should be empty!");
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queue_->ReOpen();
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VLOG(3) << "reopen success";
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VLOG(3) << "thread_num " << thread_num_;
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for (size_t thread_id = 0; thread_id < thread_num_; thread_id++) {
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read_threads_.emplace_back(new std::thread(std::bind(
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&ReadThread, file_groups_[thread_id], data_desc_,
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static_cast<int>(thread_id), &read_thread_status_, queue_)));
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}
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monitor_thread_.reset(new std::thread(
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std::bind(&MonitorThread, &read_thread_status_, queue_)));
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status_ = ReaderStatus::kRunning;
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}
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private:
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void SplitFiles() {
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file_groups_.resize(thread_num_);
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for (size_t i = 0; i < data_desc_.file_names_.size(); ++i) {
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auto& file_name = data_desc_.file_names_[i];
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std::ifstream f(file_name.c_str());
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PADDLE_ENFORCE(f.good(), "file %s not exist!", file_name);
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file_groups_[i % thread_num_].push_back(file_name);
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}
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}
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private:
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size_t thread_num_;
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const DataDesc data_desc_;
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std::shared_ptr<LoDTensorBlockingQueue> queue_;
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std::vector<std::unique_ptr<std::thread>> read_threads_;
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std::unique_ptr<std::thread> monitor_thread_;
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std::vector<ReaderThreadStatus> read_thread_status_;
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std::vector<std::vector<std::string>> file_groups_;
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};
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} // namespace reader
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} // namespace operators
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} // namespace paddle
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