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/*
* KENLM.h
*
* Created on: 4 Nov 2015
* Author: hieu
*/
#pragma once
#include <boost/shared_ptr.hpp>
#include "../FF/StatefulFeatureFunction.h"
#include "lm/model.hh"
#include "../legacy/Factor.h"
#include "../legacy/Util2.h"
#include "../Word.h"
namespace Moses2
{
class Word;
FeatureFunction *ConstructKenLM(size_t startInd, const std::string &lineOrig);
FeatureFunction *ConstructKenLM(size_t startInd, const std::string &line,
const std::string &file, FactorType factorType,
util::LoadMethod load_method);
template<class Model>
class KENLM: public StatefulFeatureFunction
{
public:
KENLM(size_t startInd, const std::string &line, const std::string &file,
FactorType factorType, util::LoadMethod load_method);
virtual ~KENLM();
virtual void Load(System &system);
virtual FFState* BlankState(MemPool &pool, const System &sys) const;
//! return the state associated with the empty hypothesis for a given sentence
virtual void EmptyHypothesisState(FFState &state, const ManagerBase &mgr,
const InputType &input, const Hypothesis &hypo) const;
virtual void
EvaluateInIsolation(MemPool &pool, const System &system, const Phrase<Moses2::Word> &source,
const TargetPhraseImpl &targetPhrase, Scores &scores,
SCORE &estimatedScore) const;
virtual void
EvaluateInIsolation(MemPool &pool, const System &system, const Phrase<SCFG::Word> &source,
const TargetPhrase<SCFG::Word> &targetPhrase, Scores &scores,
SCORE &estimatedScore) const;
virtual void EvaluateWhenApplied(const ManagerBase &mgr,
const Hypothesis &hypo, const FFState &prevState, Scores &scores,
FFState &state) const;
virtual void EvaluateWhenApplied(const SCFG::Manager &mgr,
const SCFG::Hypothesis &hypo, int featureID, Scores &scores,
FFState &state) const;
protected:
std::string m_path;
FactorType m_factorType;
util::LoadMethod m_load_method;
const Factor *m_bos;
const Factor *m_eos;
boost::shared_ptr<Model> m_ngram;
void CalcScore(const Phrase<Moses2::Word> &phrase, float &fullScore, float &ngramScore,
std::size_t &oovCount) const;
void CalcScore(const Phrase<SCFG::Word> &phrase, float &fullScore, float &ngramScore,
std::size_t &oovCount) const;
inline lm::WordIndex TranslateID(const Word &word) const
{
std::size_t factor = word[m_factorType]->GetId();
return (factor >= m_lmIdLookup.size() ? 0 : m_lmIdLookup[factor]);
}
// Convert last words of hypothesis into vocab ids, returning an end pointer.
lm::WordIndex *LastIDs(const Hypothesis &hypo, lm::WordIndex *indices) const;
std::vector<lm::WordIndex> m_lmIdLookup;
};
}
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