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https://github.com/moses-smt/mosesdecoder.git
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170 lines
6.2 KiB
C++
170 lines
6.2 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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#include "DecodeStepGeneration.h"
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#include "GenerationDictionary.h"
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#include "TranslationOption.h"
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#include "TranslationOptionCollection.h"
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#include "PartialTranslOptColl.h"
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#include "FactorCollection.h"
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namespace Moses
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{
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using namespace std;
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DecodeStepGeneration::DecodeStepGeneration(GenerationDictionary* dict,
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const DecodeStep* prev,
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const std::vector<FeatureFunction*> &features)
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: DecodeStep(dict, prev, features)
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{
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}
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// helpers
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typedef pair<Word, ScoreComponentCollection> WordPair;
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typedef list< WordPair > WordList;
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// 1st = word
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// 2nd = score
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typedef list< WordPair >::const_iterator WordListIterator;
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/** used in generation: increases iterators when looping through the exponential number of generation expansions */
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inline void IncrementIterators(vector< WordListIterator > &wordListIterVector
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, const vector< WordList > &wordListVector)
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{
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for (size_t currPos = 0 ; currPos < wordListVector.size() ; currPos++) {
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WordListIterator &iter = wordListIterVector[currPos];
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iter++;
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if (iter != wordListVector[currPos].end()) {
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// eg. 4 -> 5
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return;
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} else {
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// eg 9 -> 10
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iter = wordListVector[currPos].begin();
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}
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}
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}
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void DecodeStepGeneration::Process(const TranslationOption &inputPartialTranslOpt
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, const DecodeStep &decodeStep
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, PartialTranslOptColl &outputPartialTranslOptColl
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, TranslationOptionCollection * /* toc */
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, bool /*adhereTableLimit*/) const
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{
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if (inputPartialTranslOpt.GetTargetPhrase().GetSize() == 0) {
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// word deletion
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TranslationOption *newTransOpt = new TranslationOption(inputPartialTranslOpt);
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outputPartialTranslOptColl.Add(newTransOpt);
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return;
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}
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// normal generation step
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const GenerationDictionary* generationDictionary = decodeStep.GetGenerationDictionaryFeature();
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const Phrase &targetPhrase = inputPartialTranslOpt.GetTargetPhrase();
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const InputPath &inputPath = inputPartialTranslOpt.GetInputPath();
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size_t targetLength = targetPhrase.GetSize();
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// generation list for each word in phrase
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vector< WordList > wordListVector(targetLength);
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// create generation list
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int wordListVectorPos = 0;
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for (size_t currPos = 0 ; currPos < targetLength ; currPos++) { // going thorugh all words
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// generatable factors for this word to be put in wordList
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WordList &wordList = wordListVector[wordListVectorPos];
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const Word &word = targetPhrase.GetWord(currPos);
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// consult dictionary for possible generations for this word
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const OutputWordCollection *wordColl = generationDictionary->FindWord(word);
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if (wordColl == NULL) {
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// word not found in generation dictionary
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//toc->ProcessUnknownWord(sourceWordsRange.GetStartPos(), factorCollection);
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return; // can't be part of a phrase, special handling
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} else {
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// sort(*wordColl, CompareWordCollScore);
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OutputWordCollection::const_iterator iterWordColl;
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for (iterWordColl = wordColl->begin() ; iterWordColl != wordColl->end(); ++iterWordColl) {
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const Word &outputWord = (*iterWordColl).first;
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const ScoreComponentCollection& score = (*iterWordColl).second;
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// enter into word list generated factor(s) and its(their) score(s)
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wordList.push_back(WordPair(outputWord, score));
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}
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wordListVectorPos++; // done, next word
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}
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}
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// use generation list (wordList)
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// set up iterators (total number of expansions)
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size_t numIteration = 1;
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vector< WordListIterator > wordListIterVector(targetLength);
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vector< const Word* > mergeWords(targetLength);
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for (size_t currPos = 0 ; currPos < targetLength ; currPos++) {
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wordListIterVector[currPos] = wordListVector[currPos].begin();
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numIteration *= wordListVector[currPos].size();
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}
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// go thru each possible factor for each word & create hypothesis
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for (size_t currIter = 0 ; currIter < numIteration ; currIter++) {
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ScoreComponentCollection generationScore; // total score for this string of words
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// create vector of words with new factors for last phrase
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for (size_t currPos = 0 ; currPos < targetLength ; currPos++) {
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const WordPair &wordPair = *wordListIterVector[currPos];
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mergeWords[currPos] = &(wordPair.first);
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generationScore.PlusEquals(wordPair.second);
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}
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// merge with existing trans opt
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Phrase genPhrase( mergeWords);
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if (IsFilteringStep()) {
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if (!inputPartialTranslOpt.IsCompatible(genPhrase, m_conflictFactors))
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continue;
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}
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const TargetPhrase &inPhrase = inputPartialTranslOpt.GetTargetPhrase();
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TargetPhrase outPhrase(inPhrase);
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outPhrase.GetScoreBreakdown().PlusEquals(generationScore);
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outPhrase.MergeFactors(genPhrase, m_newOutputFactors);
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outPhrase.EvaluateInIsolation(inputPath.GetPhrase(), m_featuresToApply);
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const Range &sourceWordsRange = inputPartialTranslOpt.GetSourceWordsRange();
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TranslationOption *newTransOpt = new TranslationOption(sourceWordsRange, outPhrase);
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assert(newTransOpt);
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newTransOpt->SetInputPath(inputPath);
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outputPartialTranslOptColl.Add(newTransOpt);
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// increment iterators
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IncrementIterators(wordListIterVector, wordListVector);
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}
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}
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}
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