beam_search_decode_op.cc 4.4 KB
Newer Older
Q
Qiao Longfei 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
/* 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 "paddle/operators/beam_search_decode_op.h"

namespace paddle {
namespace operators {

class BeamSearchDecodeOp : public framework::OperatorBase {
 public:
  BeamSearchDecodeOp(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 {
    framework::ExecutionContext ctx(*this, scope, dev_ctx);
30

Q
Qiao Longfei 已提交
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
    const LoDTensorArray* ids = ctx.Input<LoDTensorArray>("Ids");
    const LoDTensorArray* scores = ctx.Input<LoDTensorArray>("Scores");
    const size_t step_num = ids->size();
    PADDLE_ENFORCE_GT(step_num, 0UL,
                      "beam search steps should be larger than 0");
    const size_t source_num = ids->at(0).lod().at(0).size() - 1;
    PADDLE_ENFORCE_GT(source_num, 0UL, "source num should be larger than 0");

    for (size_t i = 0; i < step_num; ++i) {
      PADDLE_ENFORCE_EQ(ids->at(i).lod().size(), 2UL,
                        "Level of LodTensor should be 2");
    }

    // prepare output
    LoDTensor* sentenceIds = ctx.Output<LoDTensor>("SentenceIds");
    LoDTensor* sentenceScores = ctx.Output<LoDTensor>("SentenceScores");

    BeamSearchDecoder<float> beam_search_decoder;
    beam_search_decoder.PackAllSteps(*ids, *scores, sentenceIds,
                                     sentenceScores);
  }
};

class BeamSearchDecodeOpProtoMaker : public framework::OpProtoAndCheckerMaker {
 public:
  BeamSearchDecodeOpProtoMaker(framework::OpProto* proto,
                               framework::OpAttrChecker* op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("Ids",
             "(LodTensorArray)"
             "score of the candidate words in each step");
    AddInput("Scores",
             "(LodTensorArray)"
             "score of the candidate words in each step");
    AddOutput("SentenceIds",
              "(LodTensor)"
              "All possible result sentences of word ids");
    AddOutput("SentenceScores",
              "(LodTensor)"
              "All possible result sentences of word scores");
    AddComment(R"DOC(
Pack the result of Beam search op into SentenceIds and SentenceScores.
)DOC");
  }
};

class BeamSearchDecodeInferShape : public framework::InferShapeBase {
 public:
  void operator()(framework::InferShapeContext* context) const override {
    PADDLE_ENFORCE(context->HasInput("Ids"),
                   "BeamSearchDecodeOp must has input Ids");
    PADDLE_ENFORCE(context->HasInput("Scores"),
                   "BeamSearchDecodeOp must has input Scores");
    PADDLE_ENFORCE(context->HasOutput("SentenceIds"),
                   "BeamSearchDecodeOp must has output SentenceIds");
    PADDLE_ENFORCE(context->HasOutput("SentenceScores"),
                   "BeamSearchDecodeOp must has output SentenceScores");
  }
};

class BeamSearchDecodeInferVarType : public framework::VarTypeInference {
 public:
  void operator()(const framework::OpDescBind& op_desc,
                  framework::BlockDescBind* block) const override {
    for (auto& o : op_desc.Output("SentenceIds")) {
      block->Var(o)->SetType(framework::VarDesc::LOD_TENSOR);
    }
    for (auto& o : op_desc.Output("SentenceScores")) {
      block->Var(o)->SetType(framework::VarDesc::LOD_TENSOR);
    }
  }
};

}  // namespace operators
}  // namespace paddle

REGISTER_OPERATOR(beam_search_decode, paddle::operators::BeamSearchDecodeOp,
                  paddle::operators::BeamSearchDecodeOpProtoMaker,
                  paddle::operators::BeamSearchDecodeInferShape,
                  paddle::operators::BeamSearchDecodeInferVarType,
                  paddle::framework::EmptyGradOpMaker);