parallel_do_op.cc 5.4 KB
Newer Older
Y
Yang Yang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

   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 <vector>
#include "paddle/framework/executor.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"

namespace paddle {
namespace operators {

constexpr char kInputs[] = "inputs";
constexpr char kParameters[] = "parameters";
constexpr char kPlaces[] = "places";
constexpr char kParallelBlock[] = "parallel_block";
constexpr char kOutputs[] = "outputs";
constexpr char kParallelScopes[] = "parallel_scopes";
// #define GRAD_SUFFIX "@GRAD"
// constexpr char kInputGrads[] = "inputs" GRAD_SUFFIX;
// constexpr char kOutputGrads[] = "outputs" GRAD_SUFFIX;
// constexpr char kParamGrads[] = "parameters" GRAD_SUFFIX;

using ParallelScopeVar = std::vector<framework::Scope *>;
using OperatorBase = framework::OperatorBase;

class ParallelDoOp : public OperatorBase {
 public:
  ParallelDoOp(const std::string &type,
               const framework::VariableNameMap &inputs,
               const framework::VariableNameMap &outputs,
               const framework::AttributeMap &attrs)
      : OperatorBase(type, inputs, outputs, attrs) {}

  void Run(const framework::Scope &scope,
           const platform::DeviceContext &dev_ctx) const override {
    // create scope
    // copy parameters
  }
};

class ParallelDoGradOp : public OperatorBase {
 public:
  ParallelDoGradOp(const std::string &type,
                   const framework::VariableNameMap &inputs,
                   const framework::VariableNameMap &outputs,
                   const framework::AttributeMap &attrs)
      : OperatorBase(type, inputs, outputs, attrs) {}

  void Run(const framework::Scope &scope,
           const platform::DeviceContext &dev_ctx) const override {}
};

class ParallelDoOpProtoMaker : public framework::OpProtoAndCheckerMaker {
 public:
  ParallelDoOpProtoMaker(framework::OpProto *proto,
                         framework::OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput(kInputs, "").AsDuplicable();
    AddInput(kParameters, "").AsDuplicable();
    AddInput(kPlaces, "");
    AddOutput(kOutputs, "").AsDuplicable();
    AddOutput(kParallelScopes, "");
    AddAttr<framework::BlockDescBind *>(kParallelBlock, "");
    AddComment(R"DOC(
ParallelDo Operator.
)DOC");
  }
};

class ParallelDoGradOpDescMaker : public framework::SingleGradOpDescMaker {
 public:
  using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;

 protected:
  virtual std::unique_ptr<framework::OpDescBind> Apply() const {
    PADDLE_THROW("Not Implemented");
    auto *grad = new framework::OpDescBind();
    grad->SetType("recurrent_grad");
    for (auto &input_param : this->InputNames()) {
      grad->SetInput(input_param, this->Input(input_param));
      grad->SetOutput(framework::GradVarName(input_param),
                      this->InputGrad(input_param));
    }

    for (auto &output_param : this->OutputNames()) {
      if (output_param == kParallelScopes) {
        grad->SetInput(output_param, this->Output(output_param));
        grad->SetInput(framework::GradVarName(output_param),
                       this->Output(output_param));
      } else {
        grad->SetInput(output_param, this->Output(output_param));
        grad->SetInput(framework::GradVarName(output_param),
                       this->OutputGrad(output_param));
      }
    }
    grad->SetAttrMap(this->Attrs());
    grad->SetBlockAttr(kParallelBlock, *grad_block_[0]);

    return std::unique_ptr<framework::OpDescBind>(grad);
  }
};

class ParallelDoGradOpShapeInference : public framework::InferShapeBase {
 public:
  void operator()(framework::InferShapeContext *ctx) const override {
    PADDLE_THROW("Not Implemented");
    // std::vector<std::string> input{kInputs};
    // std::vector<std::string> output{kOutputs};
    // for (auto &s : input) {
    //   PADDLE_ENFORCE(ctx->HasInputs(s));
    //   PADDLE_ENFORCE(ctx->HasOutputs(framework::GradVarName(s)),
    //                  "Cannot find the gradient variable %s",
    //                  framework::GradVarName(s));
    // }
    // for (auto &s : output) {
    //   PADDLE_ENFORCE(ctx->HasInputs(s));
    // }
    // for (auto &s : input) {
    //   ctx->SetOutputsDim(framework::GradVarName(s), ctx->GetInputsDim(s));
    // }
    // if (ctx->HasInputs(kParameters)) {
    //   PADDLE_ENFORCE(ctx->HasOutputs(framework::GradVarName(kParameters)));
    //   ctx->SetOutputsDim(framework::GradVarName(kParameters),
    //                      ctx->GetInputsDim(kParameters));
    // }
  }
};

}  // namespace operators
}  // namespace paddle

REGISTER_OPERATOR(parallel_do, paddle::operators::ParallelDoOp,
                  paddle::operators::ParallelDoOpProtoMaker,
                  paddle::operators::ParallelDoGradOpDescMaker);
REGISTER_OPERATOR(parallel_do_grad, paddle::operators::ParallelDoGradOp,
                  paddle::operators::ParallelDoGradOpShapeInference);