mirror of
https://github.com/moses-smt/mosesdecoder.git
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147 lines
3.7 KiB
C++
147 lines
3.7 KiB
C++
#ifndef GLOBALLEXICALMODELUNLIMITED_H_
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#define GLOBALLEXICALMODELUNLIMITED_H_
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#include <string>
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#include <vector>
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#include "Factor.h"
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#include "Phrase.h"
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#include "TypeDef.h"
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#include "Util.h"
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#include "WordsRange.h"
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#include "ScoreProducer.h"
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#include "FeatureFunction.h"
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#include "FactorTypeSet.h"
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#include "Sentence.h"
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#include "FFState.h"
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#ifdef WITH_THREADS
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#include <boost/thread/tss.hpp>
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#endif
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namespace Moses
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{
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class Factor;
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class Phrase;
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class Hypothesis;
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class InputType;
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/** Discriminatively trained global lexicon model
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* This is a implementation of Mauser et al., 2009's model that predicts
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* each output word from _all_ the input words. The intuition behind this
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* feature is that it uses context words for disambiguation
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*/
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class GlobalLexicalModelUnlimited : public StatelessFeatureFunction
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{
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typedef std::map< char, short > CharHash;
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typedef std::map< std::string, short > StringHash;
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struct ThreadLocalStorage
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{
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const Sentence *input;
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};
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private:
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#ifdef WITH_THREADS
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boost::thread_specific_ptr<ThreadLocalStorage> m_local;
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#else
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std::auto_ptr<ThreadLocalStorage> m_local;
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#endif
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CharHash m_punctuationHash;
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std::vector< FactorType > m_inputFactors;
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std::vector< FactorType > m_outputFactors;
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bool m_unrestricted;
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bool m_sourceContext;
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bool m_biphrase;
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bool m_bitrigger;
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bool m_biasFeature;
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float m_sparseProducerWeight;
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bool m_ignorePunctuation;
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std::set<std::string> m_vocabSource;
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std::set<std::string> m_vocabTarget;
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public:
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GlobalLexicalModelUnlimited(const std::vector< FactorType >& inFactors, const std::vector< FactorType >& outFactors,
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bool biasFeature, bool ignorePunctuation, size_t context):
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StatelessFeatureFunction("glm",ScoreProducer::unlimited),
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m_inputFactors(inFactors),
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m_outputFactors(outFactors),
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m_unrestricted(true),
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m_sourceContext(false),
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m_biphrase(false),
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m_bitrigger(false),
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m_biasFeature(biasFeature),
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m_sparseProducerWeight(1),
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m_ignorePunctuation(ignorePunctuation)
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{
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std::cerr << "Creating global lexical model unlimited.. ";
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switch(context) {
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case 1:
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m_sourceContext = true;
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std::cerr << "using source context.. ";
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break;
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case 2:
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m_biphrase = true;
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std::cerr << "using biphrases.. ";
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break;
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case 3:
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std::cerr << "using bitriggers.. ";
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m_bitrigger = true;
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break;
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}
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// compile a list of punctuation characters
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if (m_ignorePunctuation) {
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std::cerr << "ignoring punctuation.. ";
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char punctuation[] = "\"'!?¿·()#_,.:;•&@‑/\\0123456789~=";
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for (size_t i=0; i < sizeof(punctuation)-1; ++i)
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m_punctuationHash[punctuation[i]] = 1;
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}
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std::cerr << "done." << std::endl;
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}
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std::string GetScoreProducerWeightShortName(unsigned) const {
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return "glm";
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};
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bool Load(const std::string &filePathSource, const std::string &filePathTarget);
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void InitializeForInput( Sentence const& in );
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const FFState* EmptyHypothesisState(const InputType &) const {
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return new DummyState();
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}
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//TODO: This implements the old interface, but cannot be updated because
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//it appears to be stateful
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void Evaluate(const Hypothesis& cur_hypo,
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ScoreComponentCollection* accumulator) const;
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void EvaluateChart(const ChartHypothesis& /* cur_hypo */,
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int /* featureID */,
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ScoreComponentCollection* ) const {
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/* Not implemented */
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assert(0);
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}
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void SetSparseProducerWeight(float weight) { m_sparseProducerWeight = weight; }
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float GetSparseProducerWeight() const { return m_sparseProducerWeight; }
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void AddFeature(ScoreComponentCollection* accumulator, StringHash alreadyScored,
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std::string sourceTrigger, std::string sourceWord, std::string targetTrigger,
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std::string targetWord) const;
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};
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}
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#endif /* GLOBALLEXICALMODELUNLIMITED_H_ */
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