/* 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 "google/protobuf/io/zero_copy_stream_impl.h" #include "google/protobuf/message.h" #include "google/protobuf/text_format.h" #include "paddle/fluid/framework/data_set.h" #include "paddle/fluid/framework/data_feed_factory.h" namespace paddle { namespace framework { Dataset::Dataset() { thread_num_ = 1; } void Dataset::SetFileList(const std::vector& filelist) { filelist_ = filelist; int file_cnt = filelist_.size(); if (thread_num_ > file_cnt) { VLOG(1) << "DataSet thread num = " << thread_num_ << ", file num = " << file_cnt << ". Changing DataSet thread num = " << file_cnt; thread_num_ = file_cnt; } } void Dataset::SetThreadNum(int thread_num) { int file_cnt = filelist_.size(); if (file_cnt != 0 && thread_num > file_cnt) { VLOG(1) << "DataSet thread num = " << thread_num << ", file num = " << file_cnt << ". Changing DataSet thread num = " << file_cnt; thread_num = file_cnt; } thread_num_ = thread_num; } void Dataset::SetTrainerNum(int trainer_num) { trainer_num_ = trainer_num; } void Dataset::SetDataFeedDesc(const std::string& data_feed_desc_str) { google::protobuf::TextFormat::ParseFromString( data_feed_desc_str, &data_feed_desc_); } std::vector> Dataset::GetReaders() { return readers_; } void Dataset::LoadIntoMemory() { if (readers_.size() == 0) { CreateReaders(); } std::vector load_threads; for (int64_t i = 0; i < thread_num_; ++i) { load_threads.push_back(std::thread( &paddle::framework::DataFeed::LoadIntoMemory, readers_[i].get())); } for (std::thread& t : load_threads) { t.join(); } } void Dataset::LocalShuffle() { if (readers_.size() == 0) { CreateReaders(); } std::vector local_shuffle_threads; for (int64_t i = 0; i < thread_num_; ++i) { local_shuffle_threads.push_back(std::thread( &paddle::framework::DataFeed::LocalShuffle, readers_[i].get())); } for (std::thread& t : local_shuffle_threads) { t.join(); } } // todo global shuffle void Dataset::GlobalShuffle() { /* auto fleet_ptr = FleetWrapper::GetInstance(); fleet_ptr->registe_client2client_msg_handler(0, [this](int msg_type, int client_id, const std::string& msg) -> int { return this->ReceiveFromClient(msg_type, client_id, msg); }); if (readers_.size() == 0) { CreateReaders(); } std::vector global_shuffle_threads; for (int64_t i = 0; i < thread_num_; ++i) { global_shuffle_threads.push_back(std::thread(&paddle::framework::DataFeed::GlobalShuffle, readers_[i].get(), trainer_num_)); } for (std::thread& t : global_shuffle_threads) { t.join(); }*/ } void Dataset::CreateReaders() { CHECK(thread_num_ > 0) << "thread_num should > 0"; if (readers_.size() != 0) { return; } for (int64_t i = 0; i < thread_num_; ++i) { readers_.push_back(DataFeedFactory::CreateDataFeed(data_feed_desc_.name())); readers_.back()->Init(data_feed_desc_); } readers_[0]->SetFileList(filelist_); } int Dataset::ReceiveFromClient(int msg_type, int client_id, const std::string& msg) { // can also use hash // int64_t index = paddle::ps::local_random_engine()() % thread_num_; int64_t index = 0; readers_[index]->PutInsToChannel(msg); return 0; } } // end namespace framework } // end namespace paddle