// -*- mode: c++; indent-tabs-mode: nil; tab-width:2 -*- // $Id$ /*********************************************************************** Moses - factored phrase-based language decoder Copyright (C) 2006 University of Edinburgh This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA ***********************************************************************/ #ifndef moses_LanguageModel_h #define moses_LanguageModel_h #include #include #include "moses/FF/StatefulFeatureFunction.h" namespace Moses { namespace Incremental { class Manager; } class FactorCollection; class Factor; class Phrase; //! Abstract base class which represent a language model on a contiguous phrase class LanguageModel : public StatefulFeatureFunction { protected: LanguageModel(const std::string &line); bool m_enableOOVFeature; public: static const LanguageModel &GetFirstLM(); virtual ~LanguageModel(); bool OOVFeatureEnabled() const { return m_enableOOVFeature; } virtual void SetParameter(const std::string& key, const std::string& value); virtual const FFState* EmptyHypothesisState(const InputType &input) const = 0; /* calc total unweighted LM score of this phrase and return score via arguments. * Return scores should always be in natural log, regardless of representation with LM implementation. * Uses GetValue() of inherited class. * \param fullScore scores of all unigram, bigram... of contiguous n-gram of the phrase * \param ngramScore score of only n-gram of order m_nGramOrder * \param oovCount number of LM OOVs */ virtual void CalcScore(const Phrase &phrase, float &fullScore, float &ngramScore, std::size_t &oovCount) const = 0; virtual void CalcScoreFromCache(const Phrase &phrase, float &fullScore, float &ngramScore, std::size_t &oovCount) const { } virtual void IssueRequestsFor(Hypothesis& hypo, const FFState* input_state) { } virtual void sync() { } virtual void SetFFStateIdx(int state_idx) { } // KenLM only (others throw an exception): call incremental search with the model and mapping. virtual void IncrementalCallback(Incremental::Manager &manager) const; virtual void ReportHistoryOrder(std::ostream &out,const Phrase &phrase) const; virtual void EvaluateInIsolation(const Phrase &source , const TargetPhrase &targetPhrase , ScoreComponentCollection &scoreBreakdown , ScoreComponentCollection &estimatedScores) const; }; } #endif