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119 lines
4.2 KiB
C++
119 lines
4.2 KiB
C++
// -*- mode: c++; indent-tabs-mode: nil; tab-width:2 -*-
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/***********************************************************************
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Moses - factored phrase-based language decoder
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Copyright (C) 2006 University of Edinburgh
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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***********************************************************************/
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#ifndef moses_LanguageModelImplementation_h
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#define moses_LanguageModelImplementation_h
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#include <string>
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#include <vector>
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#include "moses/Factor.h"
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#include "moses/TypeDef.h"
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#include "moses/Util.h"
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#include "moses/Word.h"
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#include "Base.h"
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#include <boost/shared_ptr.hpp>
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namespace Moses
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{
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class FactorCollection;
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class Factor;
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class Phrase;
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//! to be returned from LM functions
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struct LMResult {
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// log probability
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float score;
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// Is the word unknown?
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bool unknown;
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};
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//! Abstract base class which represent a language model on a contiguous phrase
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class LanguageModelImplementation : public LanguageModel
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{
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// default constructor is ok
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void ShiftOrPush(std::vector<const Word*> &contextFactor, const Word &word) const;
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protected:
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std::string m_filePath;
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size_t m_nGramOrder; //! max n-gram length contained in this LM
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Word m_sentenceStartWord, m_sentenceEndWord; //! Contains factors which represents the beging and end words for this LM.
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//! Usually <s> and </s>
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LanguageModelImplementation(const std::string &line);
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public:
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virtual ~LanguageModelImplementation() {}
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void SetParameter(const std::string& key, const std::string& value);
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/* get score of n-gram. n-gram should not be bigger than m_nGramOrder
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* Specific implementation can return State and len data to be used in hypothesis pruning
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* \param contextFactor n-gram to be scored
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* \param state LM state. Input and output. state must be initialized. If state isn't initialized, you want GetValueWithoutState.
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*/
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virtual LMResult GetValueGivenState(const std::vector<const Word*> &contextFactor, FFState &state) const;
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// Like GetValueGivenState but state may not be initialized (however it is non-NULL).
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// For example, state just came from NewState(NULL).
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virtual LMResult GetValueForgotState(const std::vector<const Word*> &contextFactor, FFState &outState) const = 0;
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//! get State for a particular n-gram. We don't care what the score is.
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// This is here so models can implement a shortcut to GetValueAndState.
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virtual void GetState(const std::vector<const Word*> &contextFactor, FFState &outState) const;
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virtual const FFState *GetNullContextState() const = 0;
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virtual const FFState *GetBeginSentenceState() const = 0;
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virtual FFState *NewState(const FFState *from = NULL) const = 0;
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virtual void CalcScore(const Phrase &phrase, float &fullScore, float &ngramScore, size_t &oovCount) const;
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FFState *EvaluateWhenApplied(const Hypothesis &hypo, const FFState *ps, ScoreComponentCollection *out) const;
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FFState* EvaluateWhenApplied(const ChartHypothesis& cur_hypo, int featureID, ScoreComponentCollection* accumulator) const;
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void updateChartScore(float *prefixScore, float *finalScore, float score, size_t wordPos) const;
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//! max n-gram order of LM
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size_t GetNGramOrder() const {
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return m_nGramOrder;
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}
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//! Contains factors which represents the beging and end words for this LM. Usually <s> and </s>
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const Word &GetSentenceStartWord() const {
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return m_sentenceStartWord;
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}
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const Word &GetSentenceEndWord() const {
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return m_sentenceEndWord;
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}
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const FFState* EmptyHypothesisState(const InputType &/*input*/) const {
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return NewState(GetBeginSentenceState());
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}
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};
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}
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#endif
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