recv_op.cc 4.8 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
武毅 已提交
2

L
Luo Tao 已提交
3 4 5
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
武毅 已提交
6

L
Luo Tao 已提交
7
    http://www.apache.org/licenses/LICENSE-2.0
武毅 已提交
8

L
Luo Tao 已提交
9 10 11 12 13
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. */
武毅 已提交
14

15
#include <future>  // NOLINT
武毅 已提交
16 17
#include <ostream>

Y
Yi Wang 已提交
18 19 20 21
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
W
Wu Yi 已提交
22
#include "paddle/fluid/operators/distributed/distributed.h"
Y
Yancey1989 已提交
23
#include "paddle/fluid/platform/profiler.h"
T
typhoonzero 已提交
24

武毅 已提交
25 26 27 28 29
namespace paddle {
namespace operators {

class RecvOp : public framework::OperatorBase {
 public:
30 31 32
  RecvOp(const std::string &type, const framework::VariableNameMap &inputs,
         const framework::VariableNameMap &outputs,
         const framework::AttributeMap &attrs)
T
typhoonzero 已提交
33 34
      : OperatorBase(type, inputs, outputs, attrs) {}

35 36
  void RunImpl(const framework::Scope &scope,
               const platform::Place &place) const override {
T
typhoonzero 已提交
37
    std::vector<std::string> epmap = Attr<std::vector<std::string>>("epmap");
38 39
    std::vector<std::string> varnames =
        Attr<std::vector<std::string>>("varnames");
Y
Yancey1989 已提交
40
    int sync_mode = Attr<int>("sync_mode");
41 42
    auto outs = Outputs("Out");
    bool with_barrier = Attr<bool>("with_barrier");
Y
Yancey1989 已提交
43

44 45
    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
    auto &ctx = *pool.Get(place);
Y
Yancey1989 已提交
46

47
    distributed::RPCClient *rpc_client =
W
Wu Yi 已提交
48 49
        distributed::RPCClient::GetInstance<RPCCLIENT_T>(
            Attr<int>("trainer_id"));
T
typhoonzero 已提交
50

51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
    if (with_barrier) {
      std::vector<distributed::VarHandlePtr> rets;
      for (size_t i = 0; i < outs.size(); i++) {
        std::string varname = varnames.size() == 0 ? outs[i] : varnames[i];
        VLOG(4) << "recv " << outs[i] << " from " << epmap[i] << " with "
                << varname << " and with AsyncGetVar";
        rets.push_back(
            rpc_client->AsyncGetVar(epmap[i], ctx, scope, varname, outs[i]));
      }
      if (sync_mode) {
        for (size_t i = 0; i < rets.size(); i++) {
          PADDLE_ENFORCE(rets[i]->Wait(), "internal error in RPCClient");
        }
      }
    } else {
      std::vector<distributed::VarHandlePtr> rets;
      for (size_t i = 0; i < outs.size(); i++) {
        std::string varname = varnames.size() == 0 ? outs[i] : varnames[i];
        VLOG(4) << "recv " << outs[i] << " from " << epmap[i] << " with "
                << varname << " and with AsyncGetVarNoBarrier";
        rets.push_back(rpc_client->AsyncGetVarNoBarrier(epmap[i], ctx, scope,
                                                        varname, outs[i]));
      }
74 75 76
      for (size_t i = 0; i < rets.size(); i++) {
        PADDLE_ENFORCE(rets[i]->Wait(), "internal error in RPCClient");
      }
Y
Yancey1989 已提交
77
    }
武毅 已提交
78 79 80 81 82
  }
};

class RecvOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
Y
Yu Yang 已提交
83
  void Make() {
84 85
    AddInput("X", "(Any) Dummy inputs, used for control dependency")
        .AsDuplicable();
T
typhoonzero 已提交
86
    AddOutput("Out", "(Tensor) Variables to get from server.").AsDuplicable();
武毅 已提交
87 88 89
    AddComment(R"DOC(
Recv operator

90
This operator can get variables from server side.
武毅 已提交
91
)DOC");
T
typhoonzero 已提交
92 93 94 95
    AddAttr<std::vector<std::string>>("epmap",
                                      "(string vector, default 127.0.0.1:6164)"
                                      "Server endpoints in the order of input "
                                      "variables for mapping")
Y
Yancey1989 已提交
96
        .SetDefault({});
W
Wu Yi 已提交
97
    AddAttr<int>("trainer_id", "trainer id from 0 ~ worker_num.").SetDefault(0);
Y
Yancey1989 已提交
98
    AddAttr<int>("sync_mode",
Y
Yancey1989 已提交
99 100 101
                 "(int, default 0)"
                 "sync recv or async recv.")
        .SetDefault(0);
102 103 104 105 106 107 108 109 110 111 112
    AddAttr<bool>("with_barrier",
                  "(bool, default True) if with_barrier=False, will use "
                  "AsyncGetVarNoBarrier get variable from pserver immediately")
        .SetDefault(true);
    AddAttr<std::vector<std::string>>(
        "varnames",
        "(string vector, default {}) "
        "sometimes we need to put received var in another name "
        "for example: we need var named 'moment_1@127.0.0.1:1001', "
        "and it real name on parameter server is 'moment_1'. ")
        .SetDefault({});
武毅 已提交
113 114 115
  }
};

116 117
class RecvOpShapeInference : public framework::InferShapeBase {
 public:
118
  void operator()(framework::InferShapeContext *ctx) const override {}
119 120
};

武毅 已提交
121 122 123 124 125
}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;

126 127
REGISTER_OPERATOR(recv, ops::RecvOp, paddle::framework::EmptyGradOpMaker,
                  ops::RecvOpMaker, ops::RecvOpShapeInference);