void ScoreComponentCollection::ZeroAllLM(const LMList& lmList)
{
for (size_t ind = lmList.GetMinIndex(); ind <= lmList.GetMaxIndex(); ++ind)
{
m_scores[ind] = 0;
}
}
void ScoreComponentCollection::PlusEqualsAllLM(const LMList& lmList, const ScoreComponentCollection& rhs)
{
for (size_t ind = lmList.GetMinIndex(); ind <= lmList.GetMaxIndex(); ++ind)
{
m_scores[ind] += rhs.m_scores[ind];
}
}
void TargetPhrase::SetScoreChart(const ScoreProducer* translationScoreProducer,
const Scores &scoreVector
,const vector<float> &weightT
,const LMList &languageModels
,const WordPenaltyProducer* wpProducer)
{
assert(weightT.size() == scoreVector.size());
// calc average score if non-best
m_transScore = std::inner_product(scoreVector.begin(), scoreVector.end(), weightT.begin(), 0.0f);
m_scoreBreakdown.PlusEquals(translationScoreProducer, scoreVector);
// Replicated from TranslationOptions.cpp
float totalNgramScore = 0;
float totalFullScore = 0;
float totalOOVScore = 0;
LMList::const_iterator lmIter;
for (lmIter = languageModels.begin(); lmIter != languageModels.end(); ++lmIter) {
const LanguageModel &lm = **lmIter;
if (lm.Useable(*this)) {
// contains factors used by this LM
const float weightLM = lm.GetWeight();
const float oovWeightLM = lm.GetOOVWeight();
float fullScore, nGramScore;
size_t oovCount;
lm.CalcScore(*this, fullScore, nGramScore, oovCount);
fullScore = UntransformLMScore(fullScore);
nGramScore = UntransformLMScore(nGramScore);
if (StaticData::Instance().GetLMEnableOOVFeature()) {
vector<float> scores(2);
scores[0] = nGramScore;
scores[1] = oovCount;
m_scoreBreakdown.Assign(&lm, scores);
totalOOVScore += oovCount * oovWeightLM;
} else {
m_scoreBreakdown.Assign(&lm, nGramScore);
}
// total LM score so far
totalNgramScore += nGramScore * weightLM;
totalFullScore += fullScore * weightLM;
}
}
// word penalty
size_t wordCount = GetNumTerminals();
m_scoreBreakdown.Assign(wpProducer, - (float) wordCount * 0.434294482); // TODO log -> ln ??
m_fullScore = m_scoreBreakdown.GetWeightedScore() - totalNgramScore + totalFullScore + totalOOVScore;
}
void TargetPhrase::SetScore(const ScoreProducer* translationScoreProducer,
const Scores &scoreVector,
const ScoreComponentCollection &sparseScoreVector,
const vector<float> &weightT,
float weightWP, const LMList &languageModels)
{
CHECK(weightT.size() == scoreVector.size());
// calc average score if non-best
float transScore = std::inner_product(scoreVector.begin(), scoreVector.end(), weightT.begin(), 0.0f);
m_scoreBreakdown.PlusEquals(translationScoreProducer, scoreVector);
m_scoreBreakdown.PlusEquals(sparseScoreVector);
// Replicated from TranslationOptions.cpp
float totalNgramScore = 0;
float totalFullScore = 0;
float totalOOVScore = 0;
LMList::const_iterator lmIter;
for (lmIter = languageModels.begin(); lmIter != languageModels.end(); ++lmIter) {
const LanguageModel &lm = **lmIter;
if (lm.Useable(*this)) {
// contains factors used by this LM
const float weightLM = lm.GetWeight();
const float oovWeightLM = lm.GetOOVWeight();
float fullScore, nGramScore;
size_t oovCount;
lm.CalcScore(*this, fullScore, nGramScore, oovCount);
if (StaticData::Instance().GetLMEnableOOVFeature()) {
vector<float> scores(2);
scores[0] = nGramScore;
scores[1] = oovCount;
m_scoreBreakdown.Assign(&lm, scores);
totalOOVScore += oovCount * oovWeightLM;
} else {
m_scoreBreakdown.Assign(&lm, nGramScore);
}
// total LM score so far
totalNgramScore += nGramScore * weightLM;
totalFullScore += fullScore * weightLM;
}
}
m_fullScore = transScore + totalFullScore + totalOOVScore
- (this->GetSize() * weightWP); // word penalty
}
void TargetPhrase::SetScore(const ScoreProducer* translationScoreProducer,
const Scores &scoreVector,
const vector<float> &weightT,
float weightWP, const LMList &languageModels)
{
assert(weightT.size() == scoreVector.size());
// calc average score if non-best
m_transScore = std::inner_product(scoreVector.begin(), scoreVector.end(), weightT.begin(), 0.0f);
m_scoreBreakdown.PlusEquals(translationScoreProducer, scoreVector);
// Replicated from TranslationOptions.cpp
float totalFutureScore = 0;
float totalNgramScore = 0;
float totalFullScore = 0;
LMList::const_iterator lmIter;
for (lmIter = languageModels.begin(); lmIter != languageModels.end(); ++lmIter)
{
const LanguageModel &lm = **lmIter;
if (lm.Useable(*this))
{ // contains factors used by this LM
const float weightLM = lm.GetWeight();
float fullScore, nGramScore;
lm.CalcScore(*this, fullScore, nGramScore);
m_scoreBreakdown.Assign(&lm, nGramScore);
// total LM score so far
totalNgramScore += nGramScore * weightLM;
totalFullScore += fullScore * weightLM;
}
}
m_ngramScore = totalNgramScore;
m_fullScore = m_transScore + totalFutureScore + totalFullScore
- (this->GetSize() * weightWP); // word penalty
}
