mirror of
https://github.com/moses-smt/mosesdecoder.git
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213 lines
5.4 KiB
C++
213 lines
5.4 KiB
C++
// $Id$
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#include <vector>
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#include "ScoreComponentCollection.h"
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#include "StaticData.h"
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using namespace std;
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namespace Moses
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{
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ScoreComponentCollection::ScoreIndexMap ScoreComponentCollection::s_scoreIndexes;
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size_t ScoreComponentCollection::s_denseVectorSize = 0;
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ScoreComponentCollection::ScoreComponentCollection() : m_scores(s_denseVectorSize)
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{}
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void ScoreComponentCollection::RegisterScoreProducer
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(const FeatureFunction* scoreProducer)
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{
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size_t start = s_denseVectorSize;
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size_t end = start + scoreProducer->GetNumScoreComponents();
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VERBOSE(1, "FeatureFunction: " << scoreProducer->GetScoreProducerDescription() << " start: " << start << " end: " << (end-1) << endl);
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s_scoreIndexes[scoreProducer] = pair<size_t,size_t>(start,end);
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s_denseVectorSize = end;
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}
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float ScoreComponentCollection::GetWeightedScore() const
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{
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return m_scores.inner_product(StaticData::Instance().GetAllWeights().m_scores);
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}
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void ScoreComponentCollection::MultiplyEquals(float scalar)
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{
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m_scores *= scalar;
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}
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// Multiply all weights of this sparse producer by a given scalar
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void ScoreComponentCollection::MultiplyEquals(const FeatureFunction* sp, float scalar)
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{
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std::string prefix = sp->GetScoreProducerDescription() + FName::SEP;
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for(FVector::FNVmap::const_iterator i = m_scores.cbegin(); i != m_scores.cend(); i++) {
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std::stringstream name;
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name << i->first;
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if (name.str().substr( 0, prefix.length() ).compare( prefix ) == 0)
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m_scores[i->first] = i->second * scalar;
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}
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}
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// Count weights belonging to this sparse producer
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size_t ScoreComponentCollection::GetNumberWeights(const FeatureFunction* sp)
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{
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std::string prefix = sp->GetScoreProducerDescription() + FName::SEP;
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size_t weights = 0;
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for(FVector::FNVmap::const_iterator i = m_scores.cbegin(); i != m_scores.cend(); i++) {
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std::stringstream name;
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name << i->first;
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if (name.str().substr( 0, prefix.length() ).compare( prefix ) == 0)
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weights++;
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}
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return weights;
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}
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void ScoreComponentCollection::DivideEquals(float scalar)
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{
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m_scores /= scalar;
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}
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void ScoreComponentCollection::CoreDivideEquals(float scalar)
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{
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m_scores.coreDivideEquals(scalar);
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}
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void ScoreComponentCollection::DivideEquals(const ScoreComponentCollection& rhs)
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{
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m_scores.divideEquals(rhs.m_scores);
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}
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void ScoreComponentCollection::MultiplyEquals(const ScoreComponentCollection& rhs)
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{
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m_scores *= rhs.m_scores;
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}
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void ScoreComponentCollection::MultiplyEqualsBackoff(const ScoreComponentCollection& rhs, float backoff)
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{
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m_scores.multiplyEqualsBackoff(rhs.m_scores, backoff);
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}
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void ScoreComponentCollection::MultiplyEquals(float core_r0, float sparse_r0)
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{
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m_scores.multiplyEquals(core_r0, sparse_r0);
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}
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std::ostream& operator<<(std::ostream& os, const ScoreComponentCollection& rhs)
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{
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os << rhs.m_scores;
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return os;
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}
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void ScoreComponentCollection::L1Normalise()
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{
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m_scores /= m_scores.l1norm_coreFeatures();
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}
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float ScoreComponentCollection::GetL1Norm() const
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{
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return m_scores.l1norm();
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}
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float ScoreComponentCollection::GetL2Norm() const
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{
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return m_scores.l2norm();
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}
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float ScoreComponentCollection::GetLInfNorm() const
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{
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return m_scores.linfnorm();
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}
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size_t ScoreComponentCollection::L1Regularize(float lambda)
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{
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return m_scores.l1regularize(lambda);
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}
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void ScoreComponentCollection::L2Regularize(float lambda)
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{
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m_scores.l2regularize(lambda);
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}
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size_t ScoreComponentCollection::SparseL1Regularize(float lambda)
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{
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return m_scores.sparseL1regularize(lambda);
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}
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void ScoreComponentCollection::SparseL2Regularize(float lambda)
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{
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m_scores.sparseL2regularize(lambda);
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}
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void ScoreComponentCollection::Save(ostream& out) const
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{
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ScoreIndexMap::const_iterator iter = s_scoreIndexes.begin();
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for (; iter != s_scoreIndexes.end(); ++iter ) {
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string name = iter->first->GetScoreProducerDescription();
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IndexPair ip = iter->second; // feature indices
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if (ip.second-ip.first == 1) {
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out << name << " " << m_scores[ip.first] << endl;
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} else {
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for (size_t i=ip.first; i < ip.second; ++i) {
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ostringstream fullname;
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fullname << name << "_" << (i + 1 - ip.first);
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out << fullname.str() << " " << m_scores[i] << endl;
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}
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}
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}
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// write sparse features
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m_scores.write(out);
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}
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void ScoreComponentCollection::Save(const string& filename) const
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{
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ofstream out(filename.c_str());
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if (!out) {
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ostringstream msg;
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msg << "Unable to open " << filename;
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throw runtime_error(msg.str());
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}
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Save(out);
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out.close();
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}
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void ScoreComponentCollection::Assign(const FeatureFunction* sp, const string line)
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{
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istringstream istr(line);
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while(istr) {
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string namestring;
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FValue value;
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istr >> namestring;
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if (!istr) break;
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istr >> value;
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FName fname(sp->GetScoreProducerDescription(), namestring);
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m_scores[fname] = value;
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}
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}
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void ScoreComponentCollection::ZeroDenseFeatures(const FeatureFunction* sp)
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{
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size_t numScores = sp->GetNumScoreComponents();
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Scores vec(numScores, 0);
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Assign(sp, vec);
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}
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//! get subset of scores that belong to a certain sparse ScoreProducer
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FVector ScoreComponentCollection::GetVectorForProducer(const FeatureFunction* sp) const
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{
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FVector fv(s_denseVectorSize);
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std::string prefix = sp->GetScoreProducerDescription() + FName::SEP;
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for(FVector::FNVmap::const_iterator i = m_scores.cbegin(); i != m_scores.cend(); i++) {
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std::stringstream name;
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name << i->first;
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if (name.str().substr( 0, prefix.length() ).compare( prefix ) == 0)
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fv[i->first] = i->second;
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}
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return fv;
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}
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}
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