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79 lines
2.4 KiB
79 lines
2.4 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/data_feed_factory.h"
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#include "paddle/fluid/framework/data_set.h"
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#include "paddle/fluid/framework/device_worker_factory.h"
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#include "paddle/fluid/framework/trainer.h"
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namespace paddle {
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namespace framework {
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void DistMultiTrainer::Initialize(const TrainerDesc& trainer_desc,
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Dataset* dataset) {
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thread_num_ = trainer_desc.thread_num();
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SetDataset(dataset);
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const std::vector<paddle::framework::DataFeed*> readers =
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dataset->GetReaders();
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thread_num_ = readers.size();
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workers_.resize(thread_num_);
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for (int i = 0; i < thread_num_; ++i) {
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workers_[i] = DeviceWorkerFactory::CreateDeviceWorker(
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trainer_desc.device_worker_name());
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workers_[i]->SetDeviceIndex(i);
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workers_[i]->SetDataFeed(readers[i]);
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workers_[i]->Initialize(trainer_desc);
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}
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VLOG(3) << "going to initialize pull dense worker";
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pull_dense_worker_ = PullDenseWorker::GetInstance();
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pull_dense_worker_->Initialize(trainer_desc);
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VLOG(3) << "initialize pull dense worker";
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SetDebug(trainer_desc.debug());
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}
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void DistMultiTrainer::InitOtherEnv(const ProgramDesc& main_program) {
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pull_dense_worker_->SetRootScope(root_scope_);
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pull_dense_worker_->Start();
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VLOG(3) << "init other env done.";
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}
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void DistMultiTrainer::Run() {
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for (int thidx = 0; thidx < thread_num_; ++thidx) {
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if (!debug_) {
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threads_.push_back(
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std::thread(&DeviceWorker::TrainFiles, workers_[thidx].get()));
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} else {
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threads_.push_back(std::thread(&DeviceWorker::TrainFilesWithProfiler,
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workers_[thidx].get()));
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}
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}
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}
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void DistMultiTrainer::Finalize() {
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for (auto& th : threads_) {
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th.join();
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}
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pull_dense_worker_->Stop();
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root_scope_->DropKids();
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}
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} // end namespace framework
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} // end namespace paddle
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