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// $Id$
/***********************************************************************
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_LanguageModelJoint_h
#define moses_LanguageModelJoint_h
#include <vector>
#include <string>
#include <sstream>
#include "LM/SingleFactor.h"
#include "LM/MultiFactor.h"
#include "Word.h"
#include "FactorTypeSet.h"
#include "FactorCollection.h"
namespace Moses
{
class Phrase;
class FactorCollection;
/** LM of multiple factors. A simple extension of single factor LM - factors backoff together.
* Rather slow as this uses string concatenation/split
*/
class LanguageModelJoint : public LanguageModelMultiFactor
{
protected:
LanguageModelSingleFactor *m_lmImpl;
std::vector<FactorType> m_factorTypesOrdered;
size_t m_implFactor;
public:
LanguageModelJoint(LanguageModelSingleFactor *lmImpl) {
m_lmImpl = lmImpl;
}
~LanguageModelJoint() {
delete m_lmImpl;
}
bool Load(const std::string &filePath
, const std::vector<FactorType> &factorTypes
, size_t nGramOrder) {
m_factorTypes = FactorMask(factorTypes);
m_filePath = filePath;
m_nGramOrder = nGramOrder;
m_factorTypesOrdered= factorTypes;
m_implFactor = 0;
FactorCollection &factorCollection = FactorCollection::Instance();
// sentence markers
for (size_t index = 0 ; index < factorTypes.size() ; ++index) {
FactorType factorType = factorTypes[index];
m_sentenceStartArray[factorType] = factorCollection.AddFactor(Output, factorType, BOS_);
m_sentenceEndArray[factorType] = factorCollection.AddFactor(Output, factorType, EOS_);
}
return m_lmImpl->Load(filePath, m_implFactor, nGramOrder);
}
LMResult GetValueForgotState(const std::vector<const Word*> &contextFactor, FFState &outState) const {
if (contextFactor.size() == 0) {
LMResult ret;
ret.score = 0.0;
ret.unknown = false;
return ret;
}
// joint context for internal LM
std::vector<const Word*> jointContext;
for (size_t currPos = 0 ; currPos < m_nGramOrder ; ++currPos ) {
const Word &word = *contextFactor[currPos];
// add word to chunked context
std::stringstream stream("");
const Factor *factor = word[ m_factorTypesOrdered[0] ];
stream << factor->GetString();
for (size_t index = 1 ; index < m_factorTypesOrdered.size() ; ++index) {
FactorType factorType = m_factorTypesOrdered[index];
const Factor *factor = word[factorType];
stream << "|" << factor->GetString();
}
factor = FactorCollection::Instance().AddFactor(Output, m_implFactor, stream.str());
Word* jointWord = new Word;
jointWord->SetFactor(m_implFactor, factor);
jointContext.push_back(jointWord);
}
// calc score on chunked phrase
LMResult ret = m_lmImpl->GetValueForgotState(jointContext, outState);
RemoveAllInColl(jointContext);
return ret;
}
const FFState *GetNullContextState() const {
return m_lmImpl->GetNullContextState();
}
const FFState *GetBeginSentenceState() const {
return m_lmImpl->GetBeginSentenceState();
}
FFState *NewState(const FFState *from) const {
return m_lmImpl->NewState(from);
}
};
}
#endif
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