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fix future and total cost in multimodel(counts). (was broken since merge of branch weight-new in May)

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This commit is contained in:
Rico Sennrich 2013-07-31 13:32:53 +02:00
parent d0e2c43011
commit b32366ab8c
4 changed files with 40 additions and 16 deletions
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13
moses/ScoreComponentCollection.cpp
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@ -185,6 +185,19 @@ void ScoreComponentCollection::Assign(const FeatureFunction* sp, const string li
}
}
void ScoreComponentCollection::InvertDenseFeatures(const FeatureFunction* sp)
{
Scores old_scores = GetScoresForProducer(sp);
Scores new_scores(old_scores.size());
for (size_t i = 0; i != old_scores.size(); ++i) {
new_scores[i] = -old_scores[i];
}
Assign(sp, new_scores);
}
void ScoreComponentCollection::ZeroDenseFeatures(const FeatureFunction* sp)
{
size_t numScores = sp->GetNumScoreComponents();

1
moses/ScoreComponentCollection.h
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@ -335,6 +335,7 @@ public:
float GetWeightedScore() const;
void ZeroDenseFeatures(const FeatureFunction* sp);
void InvertDenseFeatures(const FeatureFunction* sp);
void L1Normalise();
float GetL1Norm() const;
float GetL2Norm() const;

23
moses/TranslationModel/PhraseDictionaryMultiModel.cpp
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@ -136,19 +136,19 @@ void PhraseDictionaryMultiModel::CollectSufficientStatistics(const Phrase& src,
multiModelStatistics * statistics = new multiModelStatistics;
statistics->targetPhrase = new TargetPhrase(*targetPhrase); //make a copy so that we don't overwrite the original phrase table info
// zero out scores from original phrase table
statistics->targetPhrase->GetScoreBreakdown().ZeroDenseFeatures(&pd);
Scores scoreVector(m_numScoreComponents);
statistics->p.resize(m_numScoreComponents);
for(size_t j = 0; j < m_numScoreComponents; ++j) {
statistics->p[j].resize(m_numModels);
scoreVector[j] = -raw_scores[j];
}
statistics->targetPhrase->GetScoreBreakdown().Assign(this, scoreVector); // set scores to 0
statistics->targetPhrase->Evaluate(src, GetFeaturesToApply());
//correct future cost estimates and total score
statistics->targetPhrase->GetScoreBreakdown().InvertDenseFeatures(&pd);
vector<FeatureFunction*> pd_feature;
pd_feature.push_back(m_pd[i]);
const vector<FeatureFunction*> pd_feature_const(pd_feature);
statistics->targetPhrase->Evaluate(src, pd_feature_const);
// zero out scores from original phrase table
statistics->targetPhrase->GetScoreBreakdown().ZeroDenseFeatures(&pd);
(*allStats)[targetString] = statistics;
@ -183,7 +183,12 @@ TargetPhraseCollection* PhraseDictionaryMultiModel::CreateTargetPhraseCollection
scoreVector[m_numScoreComponents-1] = 1.0;
statistics->targetPhrase->GetScoreBreakdown().Assign(this, scoreVector);
statistics->targetPhrase->Evaluate(src, GetFeaturesToApply());
//correct future cost estimates and total score
vector<FeatureFunction*> pd_feature;
pd_feature.push_back(const_cast<PhraseDictionaryMultiModel*>(this));
const vector<FeatureFunction*> pd_feature_const(pd_feature);
statistics->targetPhrase->Evaluate(src, pd_feature_const);
ret->Add(new TargetPhrase(*statistics->targetPhrase));
}

19
moses/TranslationModel/PhraseDictionaryMultiModelCounts.cpp
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@ -183,17 +183,17 @@ void PhraseDictionaryMultiModelCounts::CollectSufficientStatistics(const Phrase&
multiModelCountsStatistics * statistics = new multiModelCountsStatistics;
statistics->targetPhrase = new TargetPhrase(*targetPhrase); //make a copy so that we don't overwrite the original phrase table info
//correct future cost estimates and total score
statistics->targetPhrase->GetScoreBreakdown().InvertDenseFeatures(&pd);
vector<FeatureFunction*> pd_feature;
pd_feature.push_back(m_pd[i]);
const vector<FeatureFunction*> pd_feature_const(pd_feature);
statistics->targetPhrase->Evaluate(src, pd_feature_const);
// zero out scores from original phrase table
statistics->targetPhrase->GetScoreBreakdown().ZeroDenseFeatures(&pd);
statistics->fst.resize(m_numModels);
statistics->ft.resize(m_numModels);
Scores scoreVector(5);
scoreVector[0] = -raw_scores[0];
scoreVector[1] = -raw_scores[1];
scoreVector[2] = -raw_scores[2];
statistics->targetPhrase->GetScoreBreakdown().Assign(this, scoreVector); // set scores to 0
statistics->targetPhrase->Evaluate(src, GetFeaturesToApply());
(*allStats)[targetString] = statistics;
@ -246,7 +246,12 @@ TargetPhraseCollection* PhraseDictionaryMultiModelCounts::CreateTargetPhraseColl
scoreVector[4] = FloorScore(TransformScore(2.718));
statistics->targetPhrase->GetScoreBreakdown().Assign(this, scoreVector);
statistics->targetPhrase->Evaluate(src, GetFeaturesToApply());
//correct future cost estimates and total score
vector<FeatureFunction*> pd_feature;
pd_feature.push_back(const_cast<PhraseDictionaryMultiModelCounts*>(this));
const vector<FeatureFunction*> pd_feature_const(pd_feature);
statistics->targetPhrase->Evaluate(src, pd_feature_const);
} catch (AlignmentException& e) {
continue;
}