fleet_wrapper.cc 13.5 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14
// Copyright (c) 2019 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.

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
/* 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 "paddle/fluid/framework/fleet/fleet_wrapper.h"
X
xujiaqi01 已提交
30
#include <utility>
31
#include "paddle/fluid/framework/data_feed.h"
32
#include "paddle/fluid/framework/scope.h"
33 34 35 36 37 38

namespace paddle {
namespace framework {

const uint32_t MAX_FEASIGN_NUM = 1024 * 100 * 100;
std::shared_ptr<FleetWrapper> FleetWrapper::s_instance_ = NULL;
39 40
bool FleetWrapper::is_initialized_ = false;

41
#ifdef PADDLE_WITH_PSLIB
D
dongdaxiang 已提交
42 43 44
template <class AR>
paddle::ps::Archive<AR>& operator<<(paddle::ps::Archive<AR>& ar,
                                    const MultiSlotType& ins) {
45 46 47 48
  ar << ins.GetType();
  ar << ins.GetOffset();
  ar << ins.GetFloatData();
  ar << ins.GetUint64Data();
X
xujiaqi01 已提交
49
  return ar;
50 51
}

D
dongdaxiang 已提交
52 53 54
template <class AR>
paddle::ps::Archive<AR>& operator>>(paddle::ps::Archive<AR>& ar,
                                    MultiSlotType& ins) {
55 56 57 58
  ar >> ins.MutableType();
  ar >> ins.MutableOffset();
  ar >> ins.MutableFloatData();
  ar >> ins.MutableUint64Data();
X
xujiaqi01 已提交
59
  return ar;
60 61 62
}
#endif

63 64 65
#ifdef PADDLE_WITH_PSLIB
std::shared_ptr<paddle::distributed::PSlib> FleetWrapper::pslib_ptr_ = NULL;
#endif
66 67 68 69

void FleetWrapper::InitServer(const std::string& dist_desc, int index) {
#ifdef PADDLE_WITH_PSLIB
  if (!is_initialized_) {
D
dongdaxiang 已提交
70
    VLOG(3) << "Going to init server";
71 72 73 74 75
    pslib_ptr_ = std::shared_ptr<paddle::distributed::PSlib>(
        new paddle::distributed::PSlib());
    pslib_ptr_->init_server(dist_desc, index);
    is_initialized_ = true;
  } else {
D
dongdaxiang 已提交
76
    VLOG(3) << "Server can be initialized only once";
77 78 79 80 81 82 83 84 85
  }
#endif
}

void FleetWrapper::InitWorker(const std::string& dist_desc,
                              const std::vector<uint64_t>& host_sign_list,
                              int node_num, int index) {
#ifdef PADDLE_WITH_PSLIB
  if (!is_initialized_) {
D
dongdaxiang 已提交
86
    VLOG(3) << "Going to init worker";
87 88 89 90 91 92 93
    pslib_ptr_ = std::shared_ptr<paddle::distributed::PSlib>(
        new paddle::distributed::PSlib());
    pslib_ptr_->init_worker(dist_desc,
                            const_cast<uint64_t*>(host_sign_list.data()),
                            node_num, index);
    is_initialized_ = true;
  } else {
D
dongdaxiang 已提交
94
    VLOG(3) << "Worker can be initialized only once";
95 96 97 98 99 100
  }
#endif
}

void FleetWrapper::StopServer() {
#ifdef PADDLE_WITH_PSLIB
D
dongdaxiang 已提交
101
  VLOG(3) << "Going to stop server";
102 103 104 105 106 107
  pslib_ptr_->stop_server();
#endif
}

uint64_t FleetWrapper::RunServer() {
#ifdef PADDLE_WITH_PSLIB
D
dongdaxiang 已提交
108
  VLOG(3) << "Going to run server";
109 110 111 112 113 114 115 116 117
  return pslib_ptr_->run_server();
#else
  return 0;
#endif
}

void FleetWrapper::GatherServers(const std::vector<uint64_t>& host_sign_list,
                                 int node_num) {
#ifdef PADDLE_WITH_PSLIB
D
dongdaxiang 已提交
118
  VLOG(3) << "Going to gather server ips";
119 120 121 122 123
  pslib_ptr_->gather_servers(const_cast<uint64_t*>(host_sign_list.data()),
                             node_num);
#endif
}

D
dongdaxiang 已提交
124
void FleetWrapper::GatherClients(const std::vector<uint64_t>& host_sign_list) {
X
xjqbest 已提交
125 126 127
#ifdef PADDLE_WITH_PSLIB
  VLOG(3) << "Going to gather client ips";
  size_t len = host_sign_list.size();
D
dongdaxiang 已提交
128
  pslib_ptr_->gather_clients(const_cast<uint64_t*>(host_sign_list.data()), len);
X
xjqbest 已提交
129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146
#endif
}

std::vector<uint64_t> FleetWrapper::GetClientsInfo() {
#ifdef PADDLE_WITH_PSLIB
  VLOG(3) << "Going to get client info";
  return pslib_ptr_->get_client_info();
#endif
  return std::vector<uint64_t>();
}

void FleetWrapper::CreateClient2ClientConnection() {
#ifdef PADDLE_WITH_PSLIB
  VLOG(3) << "Going to create client2client connection";
  pslib_ptr_->create_client2client_connection();
#endif
}

147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168
void FleetWrapper::PullSparseVarsSync(
    const Scope& scope, const uint64_t table_id,
    const std::vector<std::string>& var_names, std::vector<uint64_t>* fea_keys,
    std::vector<std::vector<float>>* fea_values, int fea_value_dim) {
#ifdef PADDLE_WITH_PSLIB
  std::vector<::std::future<int32_t>> pull_sparse_status;
  pull_sparse_status.resize(0);
  fea_keys->clear();
  fea_keys->resize(0);
  fea_keys->reserve(MAX_FEASIGN_NUM);
  for (auto name : var_names) {
    Variable* var = scope.FindVar(name);
    LoDTensor* tensor = var->GetMutable<LoDTensor>();
    int64_t* ids = tensor->data<int64_t>();
    int len = tensor->numel();
    for (auto i = 0u; i < len; ++i) {
      if (ids[i] == 0u) {
        continue;
      }
      fea_keys->push_back(static_cast<uint64_t>(ids[i]));
    }
  }
D
dongdaxiang 已提交
169 170 171 172 173 174 175 176 177 178 179
  fea_values->resize(fea_keys->size() + 1);
  for (auto& t : *fea_values) {
    t.resize(fea_value_dim);
  }
  std::vector<float*> pull_result_ptr;
  for (auto& t : *fea_values) {
    pull_result_ptr.push_back(t.data());
  }
  auto status = pslib_ptr_->_worker_ptr->pull_sparse(
      pull_result_ptr.data(), table_id, fea_keys->data(), fea_keys->size());
  pull_sparse_status.push_back(std::move(status));
180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195
  for (auto& t : pull_sparse_status) {
    t.wait();
    auto status = t.get();
    if (status != 0) {
      LOG(ERROR) << "fleet pull sparse failed, status[" << status << "]";
      exit(-1);
    }
  }
#endif
}

void FleetWrapper::PullDenseVarsAsync(
    const Scope& scope, const uint64_t tid,
    const std::vector<std::string>& var_names,
    std::vector<::std::future<int32_t>>* pull_dense_status) {
#ifdef PADDLE_WITH_PSLIB
X
xujiaqi01 已提交
196 197
  auto& regions = _regions[tid];
  regions.clear();
198 199 200
  regions.resize(var_names.size());
  for (auto i = 0u; i < var_names.size(); ++i) {
    Variable* var = scope.FindVar(var_names[i]);
201 202 203
    LoDTensor* tensor = var->GetMutable<LoDTensor>();
    float* w = tensor->data<float>();
    paddle::ps::Region reg(w, tensor->numel());
204
    regions[i] = std::move(reg);
205 206 207 208 209 210 211 212 213 214 215
  }
  auto status =
      pslib_ptr_->_worker_ptr->pull_dense(regions.data(), regions.size(), tid);
  pull_dense_status->push_back(std::move(status));
#endif
}

void FleetWrapper::PullDenseVarsSync(
    const Scope& scope, const uint64_t tid,
    const std::vector<std::string>& var_names) {
#ifdef PADDLE_WITH_PSLIB
X
xujiaqi01 已提交
216 217
  auto& regions = _regions[tid];
  regions.clear();
218 219 220 221 222 223 224 225 226 227 228 229 230 231
  regions.reserve(var_names.size());
  for (auto& t : var_names) {
    Variable* var = scope.FindVar(t);
    LoDTensor* tensor = var->GetMutable<LoDTensor>();
    float* w = tensor->data<float>();
    paddle::ps::Region reg(w, tensor->numel());
    regions.emplace_back(std::move(reg));
  }
  auto status =
      pslib_ptr_->_worker_ptr->pull_dense(regions.data(), regions.size(), tid);
  status.wait();
#endif
}

232
void FleetWrapper::PushDenseParamSync(
D
dongdaxiang 已提交
233
    const Scope& scope, const uint64_t table_id,
234 235 236 237 238 239
    const std::vector<std::string>& var_names) {
#ifdef PADDLE_WITH_PSLIB
  auto place = platform::CPUPlace();
  std::vector<paddle::ps::Region> regions;
  for (auto& t : var_names) {
    Variable* var = scope.FindVar(t);
240
    CHECK(var != nullptr) << "var[" << t << "] not found";
241
    LoDTensor* tensor = var->GetMutable<LoDTensor>();
242
    float* g = tensor->mutable_data<float>(place);
243 244 245
    paddle::ps::Region reg(g, tensor->numel());
    regions.emplace_back(std::move(reg));
  }
246 247 248 249 250
  auto push_status = pslib_ptr_->_worker_ptr->push_dense_param(
      regions.data(), regions.size(), table_id);
  push_status.wait();
  auto status = push_status.get();
  CHECK(status == 0) << "push dense param failed, status[" << status << "]";
251 252 253
#endif
}

D
dongdaxiang 已提交
254 255 256 257
void FleetWrapper::PushDenseVarsSync(
    Scope* scope, const uint64_t table_id,
    const std::vector<std::string>& var_names) {}

258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288
void FleetWrapper::PushDenseVarsAsync(
    const Scope& scope, const uint64_t table_id,
    const std::vector<std::string>& var_names,
    std::vector<::std::future<int32_t>>* push_sparse_status) {
#ifdef PADDLE_WITH_PSLIB
  std::vector<paddle::ps::Region> regions;
  for (auto& t : var_names) {
    Variable* var = scope.FindVar(t);
    LoDTensor* tensor = var->GetMutable<LoDTensor>();
    int count = tensor->numel();
    float* g = tensor->data<float>();
    paddle::ps::Region reg(g, count);
    regions.emplace_back(std::move(reg));
  }
  auto status = pslib_ptr_->_worker_ptr->push_dense(regions.data(),
                                                    regions.size(), table_id);
  push_sparse_status->push_back(std::move(status));
#endif
}

void FleetWrapper::PushSparseVarsWithLabelAsync(
    const Scope& scope, const uint64_t table_id,
    const std::vector<uint64_t>& fea_keys, const std::vector<float>& fea_labels,
    const std::vector<std::string>& sparse_key_names,
    const std::vector<std::string>& sparse_grad_names, const int emb_dim,
    std::vector<std::vector<float>>* push_values,
    std::vector<::std::future<int32_t>>* push_sparse_status) {
#ifdef PADDLE_WITH_PSLIB
  int offset = 2;
  uint64_t fea_idx = 0u;
  for (size_t i = 0; i < sparse_key_names.size(); ++i) {
289 290
    Variable* g_var = scope.FindVar(sparse_grad_names[i]);
    CHECK(g_var != nullptr) << "var[" << sparse_grad_names[i] << "] not found";
291 292 293 294 295 296 297 298 299 300 301 302 303 304 305
    LoDTensor* g_tensor = g_var->GetMutable<LoDTensor>();
    if (g_tensor == NULL) {
      LOG(ERROR) << "var[" << sparse_key_names[i] << "] not found";
      exit(-1);
    }
    float* g = g_tensor->data<float>();
    Variable* var = scope.FindVar(sparse_key_names[i]);
    CHECK(var != nullptr) << "var[" << sparse_key_names[i] << "] not found";
    LoDTensor* tensor = var->GetMutable<LoDTensor>();
    if (tensor == NULL) {
      LOG(ERROR) << "var[" << sparse_key_names[i] << "] not found";
      exit(-1);
    }
    int len = tensor->numel();
    int64_t* ids = tensor->data<int64_t>();
306 307 308 309 310
    push_values->resize(fea_keys.size() + 1);
    for (auto& t : *push_values) {
      t.resize(emb_dim + offset);
    }

311 312 313 314 315
    for (auto id_idx = 0u; id_idx < len; ++id_idx) {
      if (ids[id_idx] == 0) {
        g += emb_dim;
        continue;
      }
316 317
      CHECK(fea_idx < (*push_values).size());
      CHECK(fea_idx < fea_labels.size());
318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339
      memcpy((*push_values)[fea_idx].data() + offset, g,
             sizeof(float) * emb_dim);
      (*push_values)[fea_idx][0] = 1.0f;
      (*push_values)[fea_idx][1] = static_cast<float>(fea_labels[fea_idx]);
      g += emb_dim;
      fea_idx++;
    }
  }
  CHECK(fea_idx == fea_keys.size()) << "fea_idx: " << fea_idx
                                    << "features size: " << fea_keys.size();
  std::vector<float*> push_g_vec;
  for (auto i = 0u; i < fea_keys.size(); ++i) {
    push_g_vec.push_back((*push_values)[i].data());
  }
  auto status = pslib_ptr_->_worker_ptr->push_sparse(
      table_id, fea_keys.data(), (const float**)push_g_vec.data(),
      fea_keys.size());
  push_sparse_status->push_back(std::move(status));

#endif
}

340 341
int FleetWrapper::RegisterClientToClientMsgHandler(int msg_type,
                                                   MsgHandlerFunc handler) {
342
#ifdef PADDLE_WITH_PSLIB
X
xujiaqi01 已提交
343 344 345
  VLOG(3) << "calling FleetWrapper::RegisterClientToClientMsgHandler";
  VLOG(3) << "pslib_ptr_=" << pslib_ptr_;
  VLOG(3) << "_worker_ptr=" << pslib_ptr_->_worker_ptr;
346 347
  return pslib_ptr_->_worker_ptr->registe_client2client_msg_handler(msg_type,
                                                                    handler);
348 349 350 351
#else
  VLOG(0) << "FleetWrapper::RegisterClientToClientMsgHandler"
          << " does nothing when no pslib";
#endif
X
xujiaqi01 已提交
352
  return 0;
353 354
}

355 356
std::future<int32_t> FleetWrapper::SendClientToClientMsg(
    int msg_type, int to_client_id, const std::string& msg) {
357
#ifdef PADDLE_WITH_PSLIB
358 359
  return pslib_ptr_->_worker_ptr->send_client2client_msg(msg_type, to_client_id,
                                                         msg);
360 361 362 363
#else
  VLOG(0) << "FleetWrapper::SendClientToClientMsg"
          << " does nothing when no pslib";
#endif
364
  return std::future<int32_t>();
X
xujiaqi01 已提交
365 366
}

D
dongdaxiang 已提交
367
template <typename T>
368
void FleetWrapper::Serialize(const std::vector<T*>& t, std::string* str) {
369 370
#ifdef PADDLE_WITH_PSLIB
  paddle::ps::BinaryArchive ar;
371 372 373
  for (size_t i = 0; i < t.size(); ++i) {
    ar << *(t[i]);
  }
X
xujiaqi01 已提交
374
  *str = std::string(ar.buffer(), ar.length());
375
#else
376
  VLOG(0) << "FleetWrapper::Serialize does nothing when no pslib";
377 378 379
#endif
}

D
dongdaxiang 已提交
380
template <typename T>
381
void FleetWrapper::Deserialize(std::vector<T>* t, const std::string& str) {
382
#ifdef PADDLE_WITH_PSLIB
383 384 385
  if (str.length() == 0) {
    return;
  }
386 387
  paddle::ps::BinaryArchive ar;
  ar.set_read_buffer(const_cast<char*>(str.c_str()), str.length(), nullptr);
388 389 390 391 392 393 394 395
  if (ar.cursor() == ar.finish()) {
    return;
  }
  while (ar.cursor() < ar.finish()) {
    t->push_back(ar.get<T>());
  }
  CHECK(ar.cursor() == ar.finish());
  VLOG(3) << "Deserialize size " << t->size();
396
#else
397
  VLOG(0) << "FleetWrapper::Deserialize does nothing when no pslib";
398 399 400 401
#endif
}

template void FleetWrapper::Serialize<std::vector<MultiSlotType>>(
402 403 404
    const std::vector<std::vector<MultiSlotType>*>&, std::string*);
template void FleetWrapper::Deserialize<std::vector<MultiSlotType>>(
    std::vector<std::vector<MultiSlotType>>*, const std::string&);
405

406 407
}  // end namespace framework
}  // end namespace paddle