SequenceGenerator.cpp 7.5 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Z
zhangjinchao01 已提交
2 3 4 5 6 7 8 9 10 11 12 13 14

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. */

Y
Yu Yang 已提交
15 16 17 18
#include <algorithm>
#include <iterator>
#include <sstream>
#include <vector>
Z
zhangjinchao01 已提交
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
#include "PaddleAPI.h"
#include "paddle/gserver/gradientmachines/GradientMachine.h"
#include "paddle/parameter/Argument.h"
#include "paddle/utils/Flags.h"

// used to represent partial sequence
struct Path {
  std::vector<int> ids;
  float logProb;
  paddle::MachineState machineState;

  Path() { logProb = 0; }

  Path(std::vector<int>& ids, float logProb, paddle::MachineState& machineState)
      : ids(ids), logProb(logProb), machineState(machineState) {}

  bool operator<(const Path& other) const { return (logProb > other.logProb); }
};

// Return top k (k == beam_size) optimal paths using beam search. The last
// element of inArgs is the Argument of feedback. gradMachine has MaxIdLayer
// as output and outArgs thus stores top k labels and their probabilities per
// position
static void findNBest(paddle::GradientMachine* gradMachine,
                      std::vector<paddle::Argument>& inArgs,
44 45 46 47
                      std::vector<Path>& finalPaths,
                      size_t bos_id,
                      size_t eos_id,
                      size_t max_length) {
Z
zhangjinchao01 已提交
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169
  std::vector<Path> paths;
  Path emptyPath;
  paths.push_back(emptyPath);
  finalPaths.clear();
  gradMachine->resetState();
  paddle::Argument feedback = inArgs.back();
  feedback.ids->setElement(0, (int)(bos_id));
  float minFinalPathLogProb = 0;
  size_t beam = 0;
  int id;
  std::vector<paddle::Argument> outArgs;
  while (true) {  // iterate over each generated word
    std::vector<Path> newPaths;
    paddle::MachineState machineState;
    for (size_t j = 0; j < paths.size(); j++) {
      Path& path = paths[j];
      if (path.machineState.size() > 0) {
        gradMachine->setState(path.machineState);
        feedback.ids->setElement(0, path.ids.back());
      }
      gradMachine->forward(inArgs, &outArgs, paddle::PASS_TEST);
      gradMachine->getState(machineState);
      beam = outArgs[0].ids->getSize();
      for (size_t k = 0; k < beam; k++) {
        id = outArgs[0].ids->getElement(k);
        float prob = outArgs[0].in->getElement(0, k);
        std::vector<int> nids(path.ids);
        nids.push_back(id);
        float newLogProb = path.logProb + log(prob);
        Path newPath(nids, newLogProb, machineState);
        if (id == (int)eos_id || nids.size() >= max_length) {
          finalPaths.push_back(newPath);
          if (minFinalPathLogProb > newPath.logProb) {
            minFinalPathLogProb = newPath.logProb;
          }
        } else {
          newPaths.push_back(newPath);
        }
      }
    }

    if (newPaths.size() == 0) {
      break;
    }
    std::nth_element(newPaths.begin(),
                     newPaths.begin() + std::min(beam, newPaths.size()),
                     newPaths.end());
    if (newPaths.size() > beam) {
      newPaths.resize(beam);
    }
    // pathA < pathB means pathA.logProb > pathB.logProb
    float maxPathLogProb =
        std::min_element(newPaths.begin(), newPaths.end())->logProb;
    if (finalPaths.size() >= beam && minFinalPathLogProb >= maxPathLogProb) {
      break;
    }
    paths = newPaths;
  }  // end while

  std::partial_sort(finalPaths.begin(),
                    finalPaths.begin() + std::min(beam, finalPaths.size()),
                    finalPaths.end());
  if (finalPaths.size() > beam) {
    finalPaths.resize(beam);
  }
}

struct SequenceGeneratorPrivate {
  std::shared_ptr<paddle::GradientMachine> machine;
  std::shared_ptr<std::vector<std::string>> dict;
  size_t beginPos;
  size_t endPos;
  size_t maxLength;

  paddle::Argument feedback;

  template <typename T>
  inline T& cast(void* ptr) {
    return *(T*)(ptr);
  }

  inline void findNBest(std::vector<paddle::Argument>& inArgs,
                        std::vector<Path>& path) {
    ::findNBest(machine.get(), inArgs, path, beginPos, endPos, maxLength);
  }

  SequenceGeneratorPrivate()
      : dict(std::make_shared<std::vector<std::string>>()),
        beginPos(0UL),
        endPos(0UL),
        maxLength(0UL),
        feedback(__create_feedback__()) {}

private:
  static paddle::Argument __create_feedback__() {
    paddle::Argument feedback;
    feedback.ids = paddle::IVector::create(/* size= */ 1, FLAGS_use_gpu);

    feedback.sequenceStartPositions =
        paddle::ICpuGpuVector::create(/* size= */ 2, /* useGpu= */ false);
    feedback.sequenceStartPositions->getMutableData(false)[0] = 0;
    feedback.sequenceStartPositions->getMutableData(false)[1] = 1;
    return feedback;
  }
};

SequenceGenerator::SequenceGenerator() : m(new SequenceGeneratorPrivate()) {}

SequenceGenerator::~SequenceGenerator() { delete m; }

class PathSequenceResults : public ISequenceResults {
  // ISequenceResults interface
public:
  PathSequenceResults(const std::shared_ptr<std::vector<Path>>& path,
                      const std::shared_ptr<std::vector<std::string>>& dict)
      : path_(path), dict_(dict) {}

  size_t getSize() const { return path_->size(); }
  std::string getSentence(size_t id, bool split) const throw(RangeError) {
    if (id < getSize()) {
      Path& p = (*path_)[id];
      std::ostringstream sout;
170 171
      std::transform(p.ids.begin(),
                     p.ids.end(),
Z
zhangjinchao01 已提交
172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242
                     std::ostream_iterator<std::string>(sout, split ? " " : ""),
                     [&](int id) { return (*dict_)[id]; });
      return sout.str();
    } else {
      RangeError e;
      throw e;
    }
  }
  std::vector<int> getSequence(size_t id) const throw(RangeError) {
    if (id < getSize()) {
      Path& p = (*path_)[id];
      return p.ids;
    } else {
      RangeError e;
      throw e;
    }
  }
  float getScore(size_t id) const throw(RangeError) {
    if (id < getSize()) {
      Path& p = (*path_)[id];
      return p.logProb;
    } else {
      RangeError e;
      throw e;
    }
  }

private:
  std::shared_ptr<std::vector<Path>> path_;
  std::shared_ptr<std::vector<std::string>> dict_;
};

ISequenceResults* SequenceGenerator::generateSequence(
    const Arguments& inArgs) const {
  auto& in_args =
      m->cast<std::vector<paddle::Argument>>(inArgs.getInternalArgumentsPtr());
  for (auto& arg : in_args) {
    arg.sequenceStartPositions = m->feedback.sequenceStartPositions;
  }
  in_args.push_back(m->feedback);
  auto path = std::make_shared<std::vector<Path>>();
  m->findNBest(in_args, *path);
  return new PathSequenceResults(path, m->dict);
}

SequenceGenerator* SequenceGenerator::createByGradientMachineSharedPtr(
    void* ptr) {
  SequenceGenerator* r = new SequenceGenerator();
  r->m->machine = r->m->cast<std::shared_ptr<paddle::GradientMachine>>(ptr);
  return r;
}

void SequenceGenerator::setDict(const std::vector<std::string>& dict) {
  *m->dict = dict;
}

void SequenceGenerator::setBos(size_t bos) { m->beginPos = bos; }

void SequenceGenerator::setEos(size_t eos) { m->endPos = eos; }

void SequenceGenerator::setMaxLength(size_t maxLength) {
  m->maxLength = maxLength;
}

void SequenceGenerator::setBeamSize(size_t beamSize) {
  if (beamSize != -1UL) {
    FLAGS_beam_size = beamSize;
  }
}

ISequenceResults::~ISequenceResults() {}