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Paddle/paddle/fluid/framework/data_set.h

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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. */
#pragma once
#include <ThreadPool.h>
#include <fstream>
#include <memory>
#include <mutex> // NOLINT
#include <set>
#include <string>
#include <thread> // NOLINT
#include <unordered_set>
#include <utility>
#include <vector>
#include "paddle/fluid/framework/data_feed.h"
namespace paddle {
namespace framework {
// Dataset is a abstract class, which defines user interfaces
// Example Usage:
// Dataset* dataset = DatasetFactory::CreateDataset("InMemoryDataset")
// dataset->SetFileList(std::vector<std::string>{"a.txt", "b.txt"})
// dataset->SetThreadNum(1)
// dataset->CreateReaders();
// dataset->SetDataFeedDesc(your_data_feed_desc);
// dataset->LoadIntoMemory();
// dataset->SetTrainerNum(2);
// dataset->GlobalShuffle();
class Dataset {
public:
Dataset() {}
virtual ~Dataset() {}
// set file list
virtual void SetFileList(const std::vector<std::string>& filelist) = 0;
// set readers' num
virtual void SetThreadNum(int thread_num) = 0;
// set workers' num
virtual void SetTrainerNum(int trainer_num) = 0;
// set fleet send batch size
virtual void SetFleetSendBatchSize(int64_t size) = 0;
// set fs name and ugi
virtual void SetHdfsConfig(const std::string& fs_name,
const std::string& fs_ugi) = 0;
// set customized download command, such as using afs api
virtual void SetDownloadCmd(const std::string& download_cmd) = 0;
// set data fedd desc, which contains:
// data feed name, batch size, slots
virtual void SetDataFeedDesc(const std::string& data_feed_desc_str) = 0;
// set channel num
virtual void SetChannelNum(int channel_num) = 0;
// set parse ins id
virtual void SetParseInsId(bool parse_ins_id) = 0;
virtual void SetParseContent(bool parse_content) = 0;
virtual void SetParseLogKey(bool parse_logkey) = 0;
virtual void SetEnablePvMerge(bool enable_pv_merge) = 0;
virtual bool EnablePvMerge() = 0;
virtual void SetMergeBySid(bool is_merge) = 0;
// set merge by ins id
virtual void SetMergeByInsId(int merge_size) = 0;
virtual void SetGenerateUniqueFeasign(bool gen_uni_feasigns) = 0;
// set fea eval mode
virtual void SetFeaEval(bool fea_eval, int record_candidate_size) = 0;
// get file list
virtual const std::vector<std::string>& GetFileList() = 0;
// get thread num
virtual int GetThreadNum() = 0;
// get worker num
virtual int GetTrainerNum() = 0;
// get fleet send batch size
virtual int64_t GetFleetSendBatchSize() = 0;
// get hdfs config
virtual std::pair<std::string, std::string> GetHdfsConfig() = 0;
// get download cmd
virtual std::string GetDownloadCmd() = 0;
// get data fedd desc
virtual const paddle::framework::DataFeedDesc& GetDataFeedDesc() = 0;
// get channel num
virtual int GetChannelNum() = 0;
// get readers, the reader num depend both on thread num
// and filelist size
virtual std::vector<paddle::framework::DataFeed*> GetReaders() = 0;
// create input channel and output channel
virtual void CreateChannel() = 0;
// register message handler between workers
virtual void RegisterClientToClientMsgHandler() = 0;
// load all data into memory
virtual void LoadIntoMemory() = 0;
// load all data into memory in async mode
virtual void PreLoadIntoMemory() = 0;
// wait async load done
virtual void WaitPreLoadDone() = 0;
// release all memory data
virtual void ReleaseMemory() = 0;
// local shuffle data
virtual void LocalShuffle() = 0;
// global shuffle data
virtual void GlobalShuffle(int thread_num = -1) = 0;
virtual void SlotsShuffle(const std::set<std::string>& slots_to_replace) = 0;
// create readers
virtual void CreateReaders() = 0;
// destroy readers
virtual void DestroyReaders() = 0;
// get memory data size
virtual int64_t GetMemoryDataSize() = 0;
// get memory data size in input_pv_channel_
virtual int64_t GetPvDataSize() = 0;
// get shuffle data size
virtual int64_t GetShuffleDataSize() = 0;
// merge by ins id
virtual void MergeByInsId() = 0;
// merge pv instance
virtual void PreprocessInstance() = 0;
// divide pv instance
virtual void PostprocessInstance() = 0;
// only for untest
virtual void SetCurrentPhase(int current_phase) = 0;
virtual void GenerateLocalTablesUnlock(int table_id, int feadim,
int read_thread_num,
int consume_thread_num,
int shard_num) = 0;
virtual void ClearLocalTables() = 0;
// create preload readers
virtual void CreatePreLoadReaders() = 0;
// destroy preload readers after prelaod done
virtual void DestroyPreLoadReaders() = 0;
// set preload thread num
virtual void SetPreLoadThreadNum(int thread_num) = 0;
// seperate train thread and dataset thread
virtual void DynamicAdjustChannelNum(int channel_num,
bool discard_remaining_ins = false) = 0;
virtual void DynamicAdjustReadersNum(int thread_num) = 0;
// set fleet send sleep seconds
virtual void SetFleetSendSleepSeconds(int seconds) = 0;
protected:
virtual int ReceiveFromClient(int msg_type, int client_id,
const std::string& msg) = 0;
};
// DatasetImpl is the implementation of Dataset,
// it holds memory data if user calls load_into_memory
template <typename T>
class DatasetImpl : public Dataset {
public:
DatasetImpl();
virtual ~DatasetImpl() {}
virtual void SetFileList(const std::vector<std::string>& filelist);
virtual void SetThreadNum(int thread_num);
virtual void SetTrainerNum(int trainer_num);
virtual void SetFleetSendBatchSize(int64_t size);
virtual void SetHdfsConfig(const std::string& fs_name,
const std::string& fs_ugi);
virtual void SetDownloadCmd(const std::string& download_cmd);
virtual void SetDataFeedDesc(const std::string& data_feed_desc_str);
virtual void SetChannelNum(int channel_num);
virtual void SetParseInsId(bool parse_ins_id);
virtual void SetParseContent(bool parse_content);
virtual void SetParseLogKey(bool parse_logkey);
virtual void SetEnablePvMerge(bool enable_pv_merge);
virtual void SetMergeBySid(bool is_merge);
virtual void SetMergeByInsId(int merge_size);
virtual void SetGenerateUniqueFeasign(bool gen_uni_feasigns);
virtual void SetFeaEval(bool fea_eval, int record_candidate_size);
virtual const std::vector<std::string>& GetFileList() { return filelist_; }
virtual int GetThreadNum() { return thread_num_; }
virtual int GetTrainerNum() { return trainer_num_; }
virtual Channel<T> GetInputChannel() { return input_channel_; }
virtual void SetInputChannel(const Channel<T>& input_channel) {
input_channel_ = input_channel;
}
virtual int64_t GetFleetSendBatchSize() { return fleet_send_batch_size_; }
virtual std::pair<std::string, std::string> GetHdfsConfig() {
return std::make_pair(fs_name_, fs_ugi_);
}
virtual std::string GetDownloadCmd();
virtual const paddle::framework::DataFeedDesc& GetDataFeedDesc() {
return data_feed_desc_;
}
virtual int GetChannelNum() { return channel_num_; }
virtual bool EnablePvMerge() { return enable_pv_merge_; }
virtual std::vector<paddle::framework::DataFeed*> GetReaders();
virtual void CreateChannel();
virtual void RegisterClientToClientMsgHandler();
virtual void LoadIntoMemory();
virtual void PreLoadIntoMemory();
virtual void WaitPreLoadDone();
virtual void ReleaseMemory();
virtual void LocalShuffle();
virtual void GlobalShuffle(int thread_num = -1);
virtual void SlotsShuffle(const std::set<std::string>& slots_to_replace) {}
virtual const std::vector<T>& GetSlotsOriginalData() {
return slots_shuffle_original_data_;
}
virtual void CreateReaders();
virtual void DestroyReaders();
virtual int64_t GetMemoryDataSize();
virtual int64_t GetPvDataSize();
virtual int64_t GetShuffleDataSize();
virtual void MergeByInsId() {}
virtual void PreprocessInstance() {}
virtual void PostprocessInstance() {}
virtual void SetCurrentPhase(int current_phase) {}
virtual void GenerateLocalTablesUnlock(int table_id, int feadim,
int read_thread_num,
int consume_thread_num,
int shard_num) {}
virtual void ClearLocalTables() {}
virtual void CreatePreLoadReaders();
virtual void DestroyPreLoadReaders();
virtual void SetPreLoadThreadNum(int thread_num);
virtual void DynamicAdjustChannelNum(int channel_num,
bool discard_remaining_ins = false);
virtual void DynamicAdjustReadersNum(int thread_num);
virtual void SetFleetSendSleepSeconds(int seconds);
protected:
virtual int ReceiveFromClient(int msg_type, int client_id,
const std::string& msg);
std::vector<std::shared_ptr<paddle::framework::DataFeed>> readers_;
std::vector<std::shared_ptr<paddle::framework::DataFeed>> preload_readers_;
paddle::framework::Channel<T> input_channel_;
paddle::framework::Channel<PvInstance> input_pv_channel_;
std::vector<paddle::framework::Channel<PvInstance>> multi_pv_output_;
std::vector<paddle::framework::Channel<PvInstance>> multi_pv_consume_;
int channel_num_;
std::vector<paddle::framework::Channel<T>> multi_output_channel_;
std::vector<paddle::framework::Channel<T>> multi_consume_channel_;
std::vector<std::unordered_set<uint64_t>> local_tables_;
// when read ins, we put ins from one channel to the other,
// and when finish reading, we set cur_channel = 1 - cur_channel,
// so if cur_channel=0, all data are in output_channel, else consume_channel
int cur_channel_;
std::vector<T> slots_shuffle_original_data_;
RecordCandidateList slots_shuffle_rclist_;
int thread_num_;
int pull_sparse_to_local_thread_num_;
paddle::framework::DataFeedDesc data_feed_desc_;
int trainer_num_;
std::vector<std::string> filelist_;
size_t file_idx_;
uint64_t total_fea_num_;
std::mutex mutex_for_pick_file_;
std::mutex mutex_for_fea_num_;
std::string fs_name_;
std::string fs_ugi_;
int64_t fleet_send_batch_size_;
int64_t fleet_send_sleep_seconds_;
std::vector<std::thread> preload_threads_;
bool merge_by_insid_;
bool parse_ins_id_;
bool parse_content_;
bool parse_logkey_;
bool merge_by_sid_;
bool enable_pv_merge_; // True means to merge pv
int current_phase_; // 1 join, 0 update
size_t merge_size_;
bool slots_shuffle_fea_eval_ = false;
bool gen_uni_feasigns_ = false;
int preload_thread_num_;
std::mutex global_index_mutex_;
int64_t global_index_ = 0;
std::vector<std::shared_ptr<ThreadPool>> consume_task_pool_;
std::vector<T> input_records_; // only for paddleboxdatafeed
};
// use std::vector<MultiSlotType> or Record as data type
class MultiSlotDataset : public DatasetImpl<Record> {
public:
MultiSlotDataset() {}
virtual void MergeByInsId();
virtual void PreprocessInstance();
virtual void PostprocessInstance();
virtual void SetCurrentPhase(int current_phase);
virtual void GenerateLocalTablesUnlock(int table_id, int feadim,
int read_thread_num,
int consume_thread_num, int shard_num);
virtual void ClearLocalTables() {
for (auto& t : local_tables_) {
t.clear();
std::unordered_set<uint64_t>().swap(t);
}
std::vector<std::unordered_set<uint64_t>>().swap(local_tables_);
}
virtual void PreprocessChannel(
const std::set<std::string>& slots_to_replace,
std::unordered_set<uint16_t>& index_slot); // NOLINT
virtual void SlotsShuffle(const std::set<std::string>& slots_to_replace);
virtual void GetRandomData(
const std::unordered_set<uint16_t>& slots_to_replace,
std::vector<Record>* result);
virtual ~MultiSlotDataset() {}
};
} // end namespace framework
} // end namespace paddle