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93 lines
3.0 KiB
C++
93 lines
3.0 KiB
C++
// $Id$
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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_LanguageModel_h
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#define moses_LanguageModel_h
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#include <string>
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#include <cstddef>
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#include "moses/FeatureFunction.h"
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namespace Moses
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{
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namespace Incremental { class Manager; }
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class FactorCollection;
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class Factor;
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class Phrase;
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//! Abstract base class which represent a language model on a contiguous phrase
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class LanguageModel : public StatefulFeatureFunction {
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protected:
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LanguageModel(const std::string& description, const std::string &line);
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// This can't be in the constructor for virual function dispatch reasons
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bool m_enableOOVFeature;
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public:
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virtual ~LanguageModel();
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bool OOVFeatureEnabled() const {
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return m_enableOOVFeature;
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}
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float GetWeight() const;
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float GetOOVWeight() const;
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virtual const FFState* EmptyHypothesisState(const InputType &input) const = 0;
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/* whether this LM can be used on a particular phrase.
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* Should return false if phrase size = 0 or factor types required don't exists
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*/
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virtual bool Useable(const Phrase &phrase) const = 0;
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/* calc total unweighted LM score of this phrase and return score via arguments.
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* Return scores should always be in natural log, regardless of representation with LM implementation.
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* Uses GetValue() of inherited class.
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* Useable() should be called beforehand on the phrase
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* \param fullScore scores of all unigram, bigram... of contiguous n-gram of the phrase
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* \param ngramScore score of only n-gram of order m_nGramOrder
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* \param oovCount number of LM OOVs
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*/
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virtual void CalcScore(const Phrase &phrase, float &fullScore, float &ngramScore, std::size_t &oovCount) const = 0;
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virtual void CalcScoreFromCache(const Phrase &phrase, float &fullScore, float &ngramScore, std::size_t &oovCount) const {
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}
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virtual void IssueRequestsFor(Hypothesis& hypo,
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const FFState* input_state) {
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}
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virtual void sync() {
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}
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virtual void SetFFStateIdx(int state_idx) {
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}
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// KenLM only (others throw an exception): call incremental search with the model and mapping.
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virtual void IncrementalCallback(Incremental::Manager &manager) const;
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};
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}
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#endif
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