| #include <fstream> |
| #include "DsgModel.h" |
| #include "dsgHyp.h" |
| #include "moses/Util.h" |
| #include "util/exception.hh" |
|
|
| using namespace std; |
| using namespace lm::ngram; |
|
|
| namespace Moses |
| { |
|
|
| DesegModel::DesegModel(const std::string &line) |
| :StatefulFeatureFunction(5, line ) |
| { |
| tFactor = 0; |
| order=5; |
| numFeatures = 5; |
| optimistic = 1; |
| ReadParameters(); |
| } |
|
|
| DesegModel::~DesegModel() |
| { |
| delete DSGM; |
| } |
|
|
| void DesegModel :: readLanguageModel(const char *lmFile) |
| { |
| DSGM = ConstructDsgLM(m_lmPath.c_str()); |
| State startState = DSGM->NullContextState(); |
| desegT=new Desegmenter(m_desegPath,m_simple); |
| } |
|
|
|
|
| void DesegModel::Load(AllOptions::ptr const& opts) |
| { |
| m_options = opts; |
| readLanguageModel(m_lmPath.c_str()); |
| } |
|
|
|
|
|
|
| void DesegModel:: EvaluateInIsolation(const Phrase &source |
| , const TargetPhrase &targetPhrase |
| , ScoreComponentCollection &scoreBreakdown |
| , ScoreComponentCollection &estimatedScores) const |
| { |
|
|
| dsgHypothesis obj; |
| vector <string> myTargetPhrase; |
| vector<float> scores; |
| vector<string> targ_phrase; |
| const AlignmentInfo &align = targetPhrase.GetAlignTerm(); |
|
|
| for (int i = 0; i < targetPhrase.GetSize(); i++) { |
| targ_phrase.push_back(targetPhrase.GetWord(i).GetFactor(tFactor)->GetString().as_string()); |
| } |
|
|
| obj.setState(DSGM->NullContextState()); |
| obj.setPhrases(targ_phrase); |
| obj.calculateDsgProbinIsol(*DSGM,*desegT,align); |
| obj.populateScores(scores,numFeatures); |
| estimatedScores.PlusEquals(this, scores); |
| } |
|
|
|
|
| FFState* DesegModel::EvaluateWhenApplied( |
| const Hypothesis& cur_hypo, |
| const FFState* prev_state, |
| ScoreComponentCollection* accumulator) const |
| { |
| const TargetPhrase &target = cur_hypo.GetCurrTargetPhrase(); |
| const Range &src_rng =cur_hypo.GetCurrSourceWordsRange(); |
| const AlignmentInfo &align = cur_hypo.GetCurrTargetPhrase().GetAlignTerm(); |
| size_t sourceOffset = src_rng.GetStartPos(); |
|
|
| dsgHypothesis obj; |
| vector<float> scores; |
| vector<string> targ_phrase; |
| bool isCompleted; |
|
|
| isCompleted=cur_hypo.IsSourceCompleted(); |
| for (int i = 0; i < cur_hypo.GetCurrTargetLength(); i++) { |
| targ_phrase.push_back(target.GetWord(i).GetFactor(tFactor)->GetString().as_string()); |
| } |
|
|
| obj.setState(prev_state); |
| obj.setPhrases( targ_phrase ); |
| obj.calculateDsgProb(*DSGM,*desegT,isCompleted,align, sourceOffset, optimistic); |
| obj.populateScores(scores,numFeatures); |
| accumulator->PlusEquals(this, scores); |
| return obj.saveState(); |
|
|
| } |
|
|
| FFState* DesegModel::EvaluateWhenApplied( |
| const ChartHypothesis& , |
| int , |
| ScoreComponentCollection* accumulator) const |
| { |
| UTIL_THROW2("Chart decoding not support by UTIL_THROW2"); |
| } |
|
|
| const FFState* DesegModel::EmptyHypothesisState(const InputType &input) const |
| { |
| VERBOSE(3,"DesegModel::EmptyHypothesisState()" << endl); |
| State startState = DSGM->BeginSentenceState(); |
| dsgState ss= dsgState(startState); |
| return new dsgState(ss); |
| } |
|
|
| std::string DesegModel::GetScoreProducerWeightShortName(unsigned idx) const |
| { |
| return "dsg"; |
| } |
|
|
|
|
| void DesegModel::SetParameter(const std::string& key, const std::string& value) |
| { |
|
|
| if (key == "path") { |
| m_lmPath = value; |
| } else if (key == "contiguity-features") { |
| if(value == "no") |
| numFeatures = 1; |
| else |
| numFeatures = 5; |
| } else if (key == "output-factor") { |
| tFactor = Scan<int>(value); |
| } else if (key == "optimistic") { |
| if (value == "n") |
| optimistic = 0; |
| else |
| optimistic = 1; |
| } else if (key == "deseg-path") { |
| m_desegPath = Scan<int>(value); |
| } else if (key == "deseg-scheme") { |
| if(value == "s") |
| m_simple = 1; |
| else |
| m_simple = 0; |
| } else if (key == "order") { |
| order = Scan<int>(value); |
| } else { |
| StatefulFeatureFunction::SetParameter(key, value); |
| } |
| } |
|
|
| bool DesegModel::IsUseable(const FactorMask &mask) const |
| { |
| bool ret = mask[0]; |
| return ret; |
| } |
|
|
| } |
|
|
