ps_client.h 12.5 KB
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// Copyright (c) 2020 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 <future>
#include <map>
#include <memory>
#include <string>
#include <unordered_map>
#include <vector>
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#include "paddle/fluid/distributed/common/cost_timer.h"
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#include "paddle/fluid/distributed/ps.pb.h"
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#include "paddle/fluid/distributed/ps/service/env.h"
#include "paddle/fluid/distributed/ps/service/sendrecv.pb.h"
#include "paddle/fluid/distributed/ps/table/accessor.h"
#include "paddle/fluid/distributed/ps/table/graph/graph_node.h"
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#include "paddle/fluid/distributed/ps/table/table.h"
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#include "paddle/fluid/platform/timer.h"
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namespace paddle {
namespace distributed {

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using paddle::distributed::PsRequestMessage;
using paddle::distributed::PsResponseMessage;

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typedef std::function<void(void *)> PSClientCallBack;
class PSClientClosure : public google::protobuf::Closure {
 public:
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  explicit PSClientClosure(PSClientCallBack callback) : _callback(callback) {}
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  virtual ~PSClientClosure() {}
  virtual void set_promise_value(int value) {
    for (auto &promise : _promises) {
      promise->set_value(value);
    }
  }

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  void add_promise(std::shared_ptr<std::promise<int32_t>> &promise) {  // NOLINT
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    _promises.push_back(promise);
  }

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  void add_timer(std::shared_ptr<CostTimer> &timer) {  // NOLINT
    _timers.push_back(timer);
  }

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 protected:
  PSClientCallBack _callback;
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  std::vector<std::shared_ptr<CostTimer>> _timers;
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  std::vector<std::shared_ptr<std::promise<int32_t>>> _promises;
};

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struct LoadSaveContext {
  int table_id;
  std::string epoch;
  std::string mode;
};

enum TrainingMode { Async = 0, Sync = 1, Geo = 3 };

enum TrainingPhase { Init = 0, Train = 1, Save = 2 };

// enum ValueType {
//   Sparse = 0,
//   Dense = 1
// };

struct PushContext {
  const uint64_t *keys;
  const float **push_values;
  const Region *push_dense_values;
};

struct RequestContext {
  int table;
  TrainingMode training_mode;    // 1 for async, 2 for geo, 3 for sync
  TrainingPhase training_phase;  // 1 for init, 2 for train
  ValueType value_type;          // 1 for sparse, 2 for dense
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  uint64_t *keys;
  float **sparse_values;  // for sparse values
  Region *dense_values;   // for dense values
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  PushContext push_context;
  size_t num;
  bool is_training;
  void *callback;
};

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class PSClient {
 public:
  PSClient() {}
  virtual ~PSClient() {}
  PSClient(PSClient &&) = delete;
  PSClient(const PSClient &) = delete;

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  virtual int32_t configure(  // NOLINT
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      const PSParameter &config,
      const std::map<uint64_t, std::vector<paddle::distributed::Region>>
          &regions,
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      PSEnvironment &_env, size_t client_id) final;  // NOLINT
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  virtual int32_t create_client2client_connection(
      int pserver_timeout_ms, int pserver_connect_timeout_ms,
      int max_retry) = 0;

  // 触发table数据退场
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  virtual std::future<int32_t> shrink(uint32_t table_id,
                                      const std::string threshold) = 0;
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  // 全量table进行数据load
  virtual std::future<int32_t> load(const std::string &epoch,
                                    const std::string &mode) = 0;
  // 指定table数据load
  virtual std::future<int32_t> load(uint32_t table_id, const std::string &epoch,
                                    const std::string &mode) = 0;
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  // context配置load选项
  virtual std::future<int32_t> Load(const LoadSaveContext &load_context) = 0;

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  // 全量table数据save  value_accessor根据mode,可能有不同的save条件
  virtual std::future<int32_t> save(const std::string &epoch,
                                    const std::string &mode) = 0;
  // 指定table数据save  value_accessor根据mode,可能有不同的save条件
  virtual std::future<int32_t> save(uint32_t table_id, const std::string &epoch,
                                    const std::string &mode) = 0;

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  virtual std::future<int32_t> Save(const LoadSaveContext &save_context) = 0;

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  // 清空table数据
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  virtual std::future<int32_t> clear() = 0;
  virtual std::future<int32_t> clear(uint32_t table_id) = 0;

  // pull dense的参数部分,并分块填充到本地网络参数中
  // start和num用于拉取部分参数
  // future结束前keys和values缓冲区不能再次使用
  // client将values按照区块拆包后送交多个sender
  // sender聚集同一区块的请求,累计多个填充buffer
  // server将参数区块中配置的某一维提取返回
  // 返回数据解包后填充到累计的多个buffer中
  virtual std::future<int32_t> pull_dense(Region *regions, size_t region_num,
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                                          size_t table_id) = 0;  // 保留
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  virtual std::future<int32_t> Push(RequestContext &push_context) = 0;

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  // firstly push dense param for parameter server
  // this is neccessary because dense weight initialized in trainer on cold
  // start
  virtual std::future<int32_t> push_dense_param(const Region *regions,
                                                size_t region_num,
                                                size_t table_id) = 0;

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  virtual std::future<int32_t> push_dense(const Region *regions,
                                          size_t region_num,
                                          size_t table_id) = 0;
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  virtual std::future<int32_t> Pull(RequestContext &pull_context) = 0;

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  // 使用keys进行pull请求,结果填充values
  // keys和values的个数均为num个,每个value占用select_size空间
  // future结束前keys和values缓冲区不能再次使用
  // 整合多个线程请求的keys,聚集并分散发送到server
  // 返回结果后,遍历buffer并对values赋值
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  // is_training 用于区分请求是训练/预测,server端对于特征和准入会有不同的处理.
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  virtual std::future<int32_t> pull_sparse(float **select_values,
                                           size_t table_id,
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                                           const uint64_t *keys, size_t num,
                                           bool is_training) = 0;
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  virtual std::future<int32_t> pull_sparse_param(float **select_values,
                                                 size_t table_id,
                                                 const uint64_t *keys,
                                                 size_t num, bool is_training) {
    VLOG(0) << "Did not implement";
    std::promise<int32_t> promise;
    std::future<int> fut = promise.get_future();
    promise.set_value(-1);
    return fut;
  }

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  virtual ::std::future<int32_t> pull_sparse_ptr(char **select_values,
                                                 size_t table_id,
                                                 const uint64_t *keys,
                                                 size_t num) {
    VLOG(0) << "Did not implement";
    std::promise<int32_t> promise;
    std::future<int> fut = promise.get_future();
    promise.set_value(-1);
    return fut;
  }

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  virtual std::future<int32_t> print_table_stat(uint32_t table_id) = 0;

  // 确保所有积攒中的请求都发起发送
  virtual std::future<int32_t> flush() = 0;
  // server优雅退出
  virtual std::future<int32_t> stop_server() = 0;

  // server profilera
  virtual std::future<int32_t> start_profiler() = 0;
  virtual std::future<int32_t> stop_profiler() = 0;

  virtual std::future<int32_t> barrier(size_t table_id,
                                       uint32_t barrier_type) = 0;

  virtual std::future<int32_t> pull_geo_param(size_t table_id,
                                              std::vector<float> *values,
                                              std::vector<uint64_t> *keys,
                                              int pserver_idx) = 0;

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  virtual std::future<int32_t> push_global_step(int table_id,
                                                int64_t *total_send_data,
                                                void *done) = 0;
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  // recv table from server and save it in LodTensor
  virtual int32_t recv_and_save_table(const uint64_t table_id,
                                      const std::string &path) = 0;

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  virtual void finalize_worker() = 0;
  // client to client, 消息发送
  virtual std::future<int32_t> send_client2client_msg(int msg_type,
                                                      int to_client_id,
                                                      const std::string &msg) {
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    VLOG(0) << "Did not implement";
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    std::promise<int32_t> promise;
    std::future<int> fut = promise.get_future();
    promise.set_value(-1);
    return fut;
  }
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  // client2client消息处理,std::function<int32_t (int, int, const std::string&)
  // -> ret (msg_type, from_client_id, msg)
  typedef std::function<int32_t(int, int, const std::string &)> MsgHandlerFunc;
  virtual int registe_client2client_msg_handler(int msg_type,
                                                MsgHandlerFunc handler) {
    _msg_handler_map[msg_type] = handler;
    return 0;
  }
  virtual int handle_client2client_msg(int msg_type, int from_client_id,
                                       const std::string &msg) {
    auto itr = _msg_handler_map.find(msg_type);
    if (itr == _msg_handler_map.end()) {
      LOG(WARNING) << "unknown client2client_msg type:" << msg_type;
      return -1;
    }
    return itr->second(msg_type, from_client_id, msg);
  }

  virtual ValueAccessor *table_accessor(size_t table_id) {
    auto itr = _table_accessors.find(table_id);
    if (itr == _table_accessors.end()) {
      return NULL;
    }
    return itr->second.get();
  }

  virtual size_t get_server_nums() = 0;

  virtual std::future<int32_t> push_dense_raw_gradient(
      int table_id, float *total_send_data, size_t total_send_data_size,
      void *done) = 0;

  virtual std::future<int32_t> push_sparse_raw_gradient(
      size_t table_id, const uint64_t *keys, const float **update_values,
      size_t num, void *done) = 0;

  virtual std::future<int32_t> push_sparse_raw_gradient_partial(
      size_t table_id, const uint64_t *keys, const float **update_values,
      uint32_t num, void *done, int pserver_idx) = 0;

  virtual std::future<int32_t> push_sparse_param(size_t table_id,
                                                 const uint64_t *keys,
                                                 const float **update_values,
                                                 size_t num, void *done) = 0;
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  virtual std::future<int32_t> push_sparse(size_t table_id,
                                           const uint64_t *keys,
                                           const float **update_values,
                                           size_t num) = 0;
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 protected:
  virtual int32_t initialize() = 0;
  size_t _client_id;
  PSParameter _config;
  std::map<uint64_t, std::vector<paddle::distributed::Region>>
      _dense_pull_regions;
  PSEnvironment *_env;
  std::unordered_map<uint32_t, std::shared_ptr<ValueAccessor>> _table_accessors;
  std::unordered_map<int32_t, MsgHandlerFunc>
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      _msg_handler_map;  // 处理client2client消息
};

template <class T>
class AsyncRequestTask {
 public:
  AsyncRequestTask() : _promise(std::make_shared<std::promise<int32_t>>()) {}
  AsyncRequestTask(T &data, size_t table_id, std::shared_ptr<CostTimer> &timer)
      : _table_id(table_id),
        _timer(timer),
        _promise(std::make_shared<std::promise<int32_t>>()) {
    _data = std::move(data);
  }

  AsyncRequestTask(AsyncRequestTask &data)  // NOLINT
      : _table_id(data.table_id()),
        _timer(data.timer()),
        _promise(data.promise()) {
    _data = std::move(data.data());
  }

  ~AsyncRequestTask() {}

  inline T &data() { return _data; }
  inline size_t table_id() { return _table_id; }
  inline std::shared_ptr<CostTimer> &timer() { return _timer; }
  inline std::future<int32_t> get_future() { return _promise->get_future(); }
  inline std::shared_ptr<std::promise<int32_t>> &promise() { return _promise; }

 private:
  T _data;
  size_t _table_id;
  std::shared_ptr<CostTimer> _timer;
  std::shared_ptr<std::promise<int32_t>> _promise;
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};
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REGISTER_PSCORE_REGISTERER(PSClient);
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class PSClientFactory {
 public:
  static PSClient *create(const PSParameter &config);
};
}  // namespace distributed
}  // namespace paddle