C++ InputType::GetWord方法代码示例

void PhraseDictionaryFuzzyMatch::InitializeForInput(InputType const& inputSentence)
{
  char dirName[] = "/tmp/moses.XXXXXX";
  char *temp = mkdtemp(dirName);
  UTIL_THROW_IF2(temp == NULL,
		  "Couldn't create temporary directory " << dirName);

  string dirNameStr(dirName);

  string inFileName(dirNameStr + "/in");

  ofstream inFile(inFileName.c_str());

  for (size_t i = 1; i < inputSentence.GetSize() - 1; ++i) {
    inFile << inputSentence.GetWord(i);
  }
  inFile << endl;
  inFile.close();

  long translationId = inputSentence.GetTranslationId();
  string ptFileName = m_FuzzyMatchWrapper->Extract(translationId, dirNameStr);

  // populate with rules for this sentence
  PhraseDictionaryNodeMemory &rootNode = m_collection[translationId];
  FormatType format = MosesFormat;

  // data from file
  InputFileStream inStream(ptFileName);

  // copied from class LoaderStandard
  PrintUserTime("Start loading fuzzy-match phrase model");

  const StaticData &staticData = StaticData::Instance();
  const std::string& factorDelimiter = staticData.GetFactorDelimiter();


  string lineOrig;
  size_t count = 0;

  while(getline(inStream, lineOrig)) {
    const string *line;
    if (format == HieroFormat) { // reformat line
      UTIL_THROW(util::Exception, "Cannot be Hiero format");
      //line = ReformatHieroRule(lineOrig);
    } else {
      // do nothing to format of line
      line = &lineOrig;
    }

    vector<string> tokens;
    vector<float> scoreVector;

    TokenizeMultiCharSeparator(tokens, *line , "|||" );

    if (tokens.size() != 4 && tokens.size() != 5) {
      stringstream strme;
      strme << "Syntax error at " << ptFileName << ":" << count;
      UserMessage::Add(strme.str());
      abort();
    }

    const string &sourcePhraseString = tokens[0]
                                       , &targetPhraseString = tokens[1]
                                           , &scoreString        = tokens[2]
                                               , &alignString        = tokens[3];

    bool isLHSEmpty = (sourcePhraseString.find_first_not_of(" \t", 0) == string::npos);
    if (isLHSEmpty && !staticData.IsWordDeletionEnabled()) {
      TRACE_ERR( ptFileName << ":" << count << ": pt entry contains empty target, skipping\n");
      continue;
    }

    Tokenize<float>(scoreVector, scoreString);
    const size_t numScoreComponents = GetNumScoreComponents();
    if (scoreVector.size() != numScoreComponents) {
      stringstream strme;
      strme << "Size of scoreVector != number (" << scoreVector.size() << "!="
            << numScoreComponents << ") of score components on line " << count;
      UserMessage::Add(strme.str());
      abort();
    }

    UTIL_THROW_IF2(scoreVector.size() != numScoreComponents,
    		"Number of scores incorrectly specified");

    // parse source & find pt node

    // constituent labels
    Word *sourceLHS;
    Word *targetLHS;

    // source
    Phrase sourcePhrase( 0);
    sourcePhrase.CreateFromString(Input, m_input, sourcePhraseString, factorDelimiter, &sourceLHS);

    // create target phrase obj
    TargetPhrase *targetPhrase = new TargetPhrase();
    targetPhrase->CreateFromString(Output, m_output, targetPhraseString, factorDelimiter, &targetLHS);

    // rest of target phrase
//.........这里部分代码省略.........

void WordTranslationFeature::EvaluateWithSourceContext(const InputType &input
    , const InputPath &inputPath
    , const TargetPhrase &targetPhrase
    , const StackVec *stackVec
    , ScoreComponentCollection &scoreBreakdown
    , ScoreComponentCollection *estimatedScores) const
{
  const Sentence& sentence = static_cast<const Sentence&>(input);
  const AlignmentInfo &alignment = targetPhrase.GetAlignTerm();

  // process aligned words
  for (AlignmentInfo::const_iterator alignmentPoint = alignment.begin(); alignmentPoint != alignment.end(); alignmentPoint++) {
    const Phrase& sourcePhrase = inputPath.GetPhrase();
    int sourceIndex = alignmentPoint->first;
    int targetIndex = alignmentPoint->second;
    Word ws = sourcePhrase.GetWord(sourceIndex);
    if (m_factorTypeSource == 0 && ws.IsNonTerminal()) continue;
    Word wt = targetPhrase.GetWord(targetIndex);
    if (m_factorTypeSource == 0 && wt.IsNonTerminal()) continue;
    StringPiece sourceWord = ws.GetFactor(m_factorTypeSource)->GetString();
    StringPiece targetWord = wt.GetFactor(m_factorTypeTarget)->GetString();
    if (m_ignorePunctuation) {
      // check if source or target are punctuation
      char firstChar = sourceWord[0];
      CharHash::const_iterator charIterator = m_punctuationHash.find( firstChar );
      if(charIterator != m_punctuationHash.end())
        continue;
      firstChar = targetWord[0];
      charIterator = m_punctuationHash.find( firstChar );
      if(charIterator != m_punctuationHash.end())
        continue;
    }

    if (!m_unrestricted) {
      if (FindStringPiece(m_vocabSource, sourceWord) == m_vocabSource.end())
        sourceWord = "OTHER";
      if (FindStringPiece(m_vocabTarget, targetWord) == m_vocabTarget.end())
        targetWord = "OTHER";
    }

    if (m_simple) {
      // construct feature name
      util::StringStream featureName;
      featureName << m_description << "_";
      featureName << sourceWord;
      featureName << "~";
      featureName << targetWord;
      scoreBreakdown.SparsePlusEquals(featureName.str(), 1);
    }
    if (m_domainTrigger && !m_sourceContext) {
      const bool use_topicid = sentence.GetUseTopicId();
      const bool use_topicid_prob = sentence.GetUseTopicIdAndProb();
      if (use_topicid || use_topicid_prob) {
        if(use_topicid) {
          // use topicid as trigger
          const long topicid = sentence.GetTopicId();
          util::StringStream feature;
          feature << m_description << "_";
          if (topicid == -1)
            feature << "unk";
          else
            feature << topicid;

          feature << "_";
          feature << sourceWord;
          feature << "~";
          feature << targetWord;
          scoreBreakdown.SparsePlusEquals(feature.str(), 1);
        } else {
          // use topic probabilities
          const vector<string> &topicid_prob = *(input.GetTopicIdAndProb());
          if (atol(topicid_prob[0].c_str()) == -1) {
            util::StringStream feature;
            feature << m_description << "_unk_";
            feature << sourceWord;
            feature << "~";
            feature << targetWord;
            scoreBreakdown.SparsePlusEquals(feature.str(), 1);
          } else {
            for (size_t i=0; i+1 < topicid_prob.size(); i+=2) {
              util::StringStream feature;
              feature << m_description << "_";
              feature << topicid_prob[i];
              feature << "_";
              feature << sourceWord;
              feature << "~";
              feature << targetWord;
              scoreBreakdown.SparsePlusEquals(feature.str(), atof((topicid_prob[i+1]).c_str()));
            }
          }
        }
      } else {
        // range over domain trigger words (keywords)
        const long docid = input.GetDocumentId();
        for (boost::unordered_set<std::string>::const_iterator p = m_vocabDomain[docid].begin(); p != m_vocabDomain[docid].end(); ++p) {
          string sourceTrigger = *p;
          util::StringStream feature;
          feature << m_description << "_";
          feature << sourceTrigger;
          feature << "_";
//.........这里部分代码省略.........