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https://github.com/moses-smt/mosesdecoder.git
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167 lines
5.8 KiB
C++
167 lines
5.8 KiB
C++
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// $Id$
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// vim:tabstop=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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#include "TranslationOption.h"
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#include "WordsBitmap.h"
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#include "PhraseDictionaryMemory.h"
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#include "GenerationDictionary.h"
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#include "LMList.h"
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#include "StaticData.h"
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#include "InputType.h"
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using namespace std;
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//TODO this should be a factory function!
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TranslationOption::TranslationOption(const WordsRange &wordsRange
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, const TargetPhrase &targetPhrase
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, const InputType &inputType)
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: m_targetPhrase(targetPhrase)
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, m_sourceWordsRange(wordsRange)
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{
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// set score
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m_scoreBreakdown.PlusEquals(targetPhrase.GetScoreBreakdown());
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if (inputType.GetType() == SentenceInput)
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{
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Phrase phrase = inputType.GetSubString(wordsRange);
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m_sourcePhrase = new Phrase(phrase);
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}
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else
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{ // TODO lex reordering with confusion network
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m_sourcePhrase = new Phrase(*targetPhrase.GetSourcePhrase());
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}
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}
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//TODO this should be a factory function!
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TranslationOption::TranslationOption(const WordsRange &wordsRange
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, const TargetPhrase &targetPhrase
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, const InputType &inputType
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, int /*whatever*/)
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: m_targetPhrase(targetPhrase)
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, m_sourceWordsRange (wordsRange)
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, m_futureScore(0)
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{
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const UnknownWordPenaltyProducer *up = StaticData::Instance().GetUnknownWordPenaltyProducer();
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if (up) {
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const ScoreProducer *scoreProducer = (const ScoreProducer *)up; // not sure why none of the c++ cast works
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vector<float> score(1);
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score[0] = FloorScore(-numeric_limits<float>::infinity());
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m_scoreBreakdown.Assign(scoreProducer, score);
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}
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if (inputType.GetType() == SentenceInput)
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{
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Phrase phrase = inputType.GetSubString(wordsRange);
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m_sourcePhrase = new Phrase(phrase);
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}
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else
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{ // TODO lex reordering with confusion network
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m_sourcePhrase = new Phrase(*targetPhrase.GetSourcePhrase());
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}
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}
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TranslationOption::TranslationOption(const TranslationOption ©)
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: m_targetPhrase(copy.m_targetPhrase)
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//, m_sourcePhrase(new Phrase(*copy.m_sourcePhrase)) // TODO use when confusion network trans opt for confusion net properly implemented
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, m_sourcePhrase( (copy.m_sourcePhrase == NULL) ? new Phrase(Input) : new Phrase(*copy.m_sourcePhrase))
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, m_sourceWordsRange(copy.m_sourceWordsRange)
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, m_futureScore(copy.m_futureScore)
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, m_scoreBreakdown(copy.m_scoreBreakdown)
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, m_reordering(copy.m_reordering)
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{}
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TranslationOption::TranslationOption(const TranslationOption ©, const WordsRange &sourceWordsRange)
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: m_targetPhrase(copy.m_targetPhrase)
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//, m_sourcePhrase(new Phrase(*copy.m_sourcePhrase)) // TODO use when confusion network trans opt for confusion net properly implemented
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, m_sourcePhrase( (copy.m_sourcePhrase == NULL) ? new Phrase(Input) : new Phrase(*copy.m_sourcePhrase))
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, m_sourceWordsRange(sourceWordsRange)
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, m_futureScore(copy.m_futureScore)
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, m_scoreBreakdown(copy.m_scoreBreakdown)
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, m_reordering(copy.m_reordering)
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{}
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void TranslationOption::MergeNewFeatures(const Phrase& phrase, const ScoreComponentCollection& score, const std::vector<FactorType>& featuresToAdd)
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{
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assert(phrase.GetSize() == m_targetPhrase.GetSize());
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if (featuresToAdd.size() == 1) {
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m_targetPhrase.MergeFactors(phrase, featuresToAdd[0]);
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} else if (featuresToAdd.empty()) {
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/* features already there, just update score */
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} else {
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m_targetPhrase.MergeFactors(phrase, featuresToAdd);
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}
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m_scoreBreakdown.PlusEquals(score);
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}
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bool TranslationOption::IsCompatible(const Phrase& phrase, const std::vector<FactorType>& featuresToCheck) const
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{
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if (featuresToCheck.size() == 1) {
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return m_targetPhrase.IsCompatible(phrase, featuresToCheck[0]);
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} else if (featuresToCheck.empty()) {
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return true;
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/* features already there, just update score */
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} else {
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return m_targetPhrase.IsCompatible(phrase, featuresToCheck);
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}
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}
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bool TranslationOption::Overlap(const Hypothesis &hypothesis) const
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{
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const WordsBitmap &bitmap = hypothesis.GetWordsBitmap();
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return bitmap.Overlap(GetSourceWordsRange());
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}
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void TranslationOption::CalcScore()
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{
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// LM scores
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float ngramScore = 0;
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float retFullScore = 0;
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const LMList &allLM = StaticData::Instance().GetAllLM();
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allLM.CalcScore(GetTargetPhrase(), retFullScore, ngramScore, &m_scoreBreakdown);
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size_t phraseSize = GetTargetPhrase().GetSize();
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// future score
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m_futureScore = retFullScore - ngramScore
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+ m_scoreBreakdown.InnerProduct(StaticData::Instance().GetAllWeights()) - phraseSize * StaticData::Instance().GetWeightWordPenalty();
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}
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TO_STRING_BODY(TranslationOption);
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// friend
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ostream& operator<<(ostream& out, const TranslationOption& possibleTranslation)
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{
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out << possibleTranslation.GetTargetPhrase()
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<< "c=" << possibleTranslation.GetFutureScore()
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<< " [" << possibleTranslation.GetSourceWordsRange() << "]"
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<< possibleTranslation.GetScoreBreakdown();
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return out;
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}
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void TranslationOption::CacheReorderingProb(const LexicalReordering &lexreordering
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, const Score &score)
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{
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m_reordering.Assign(&lexreordering, score);
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}
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