pull_dense_worker.cc 4.2 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
/* 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 <time.h>
#include "paddle/fluid/framework/device_worker.h"

namespace paddle {
namespace framework {

std::shared_ptr<PullDenseWorker> PullDenseWorker::s_instance_ = NULL;
D
dongdaxiang 已提交
21 22 23 24 25 26
std::mutex PullDenseWorker::mutex_for_version_;
std::map<uint64_t, uint64_t> PullDenseWorker::last_versions_;
std::map<uint64_t, uint64_t> PullDenseWorker::current_version_;
std::map<uint64_t, std::vector<uint64_t>> PullDenseWorker::training_versions_;
std::map<uint64_t, std::vector<std::string>>
    PullDenseWorker::dense_value_names_;
27 28 29 30

void PullDenseWorker::Initialize(const TrainerDesc& param) {
  running_ = false;
  param_ = param.pull_dense_param();
H
heqiaozhi 已提交
31
  dwp_param_ = param.downpour_param();
32 33 34
  threshold_ = param_.threshold();
  thread_num_ = param_.device_num();
  sleep_time_ms_ = param_.sleep_time_ms();
H
heqiaozhi 已提交
35 36 37 38 39 40 41 42 43 44 45
  for (size_t i = 0;
       i < dwp_param_.program_config(0).pull_dense_table_id_size(); ++i) {
    uint64_t tid = static_cast<uint64_t>(
        dwp_param_.program_config(0).pull_dense_table_id(i));
    TableParameter table;
    for (auto i : param_.dense_table()) {
      if (i.table_id() == tid) {
        table = i;
        break;
      }
    }
46
    // setup dense variables for each table
H
heqiaozhi 已提交
47
    int var_num = table.dense_value_name_size();
48 49
    dense_value_names_[tid].resize(var_num);
    for (int j = 0; j < var_num; ++j) {
H
heqiaozhi 已提交
50
        dense_value_names_[tid][j] = table.dense_value_name(j);
51 52 53 54 55 56
    }
    // setup training version for each table
    training_versions_[tid].resize(thread_num_, 0);
    last_versions_[tid] = 0;
    current_version_[tid] = 0;
  }
57
  fleet_ptr_ = FleetWrapper::GetInstance();
58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75
}

void PullDenseWorker::Wait(std::vector<::std::future<int32_t>>* status_vec) {
  for (auto& t : *status_vec) {
    t.wait();
    auto status = t.get();
    if (status != 0) {
      LOG(WARNING) << "Current Pull Dense Thread Failed Times"
                   << ++pull_dense_fail_times_;
    }
  }

  int MAX_FAIL_NUM = 20;
  if (pull_dense_fail_times_ > MAX_FAIL_NUM) {
    LOG(FATAL) << "Pull Dense Failed Times More Than " << MAX_FAIL_NUM
               << " Times";
    exit(-1);
  }
76
  status_vec->resize(0);
77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
}

void PullDenseWorker::Stop() {
  if (running_) {
    running_ = false;
    t_.join();
  }
}

int PullDenseWorker::Start() {
  running_ = true;
  t_ = std::thread(&PullDenseWorker::Run, this);
  return 0;
}

void PullDenseWorker::Run() {
  while (running_) {
    pull_dense_status_.resize(0);
H
heqiaozhi 已提交
95 96 97 98
    for (size_t i = 0;
         i < dwp_param_.program_config(0).pull_dense_table_id_size(); ++i) {
      uint64_t tid = static_cast<uint64_t>(
          dwp_param_.program_config(0).pull_dense_table_id(i));
99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134
      if (CheckUpdateParam(tid)) {
        fleet_ptr_->PullDenseVarsAsync(
            *root_scope_, tid, dense_value_names_[tid], &pull_dense_status_);
        ResetThreadVersion(tid);
      }
    }
    if (pull_dense_status_.size() != 0) {
      Wait(&pull_dense_status_);
    }
    usleep(sleep_time_ms_ * 1000);
  }
}

void PullDenseWorker::IncreaseThreadVersion(int thread_id, uint64_t table_id) {
  std::lock_guard<std::mutex> lock(mutex_for_version_);
  training_versions_[table_id][thread_id]++;
}

bool PullDenseWorker::CheckUpdateParam(uint64_t table_id) {
  std::lock_guard<std::mutex> lock(mutex_for_version_);
  auto& version = training_versions_[table_id];
  current_version_[table_id] =
      *(std::min_element(version.begin(), version.end()));
  if (current_version_[table_id] - last_versions_[table_id] < threshold_) {
    return false;
  }
  return true;
}

void PullDenseWorker::ResetThreadVersion(uint64_t table_id) {
  std::lock_guard<std::mutex> lock(mutex_for_version_);
  last_versions_[table_id] = current_version_[table_id];
}

}  // namespace framework
}  // namespace paddle