mirror of
https://github.com/moses-smt/mosesdecoder.git
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201 lines
6.4 KiB
C++
201 lines
6.4 KiB
C++
// -*- c++ -*-
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#ifndef moses_FeatureFunction_h
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#define moses_FeatureFunction_h
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#include <vector>
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#include <set>
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#include <string>
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#include "moses/FeatureVector.h"
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#include "moses/TypeDef.h"
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#include "moses/parameters/AllOptions.h"
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#include <boost/shared_ptr.hpp>
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namespace Moses
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{
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class AllOptions;
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class Phrase;
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class TargetPhrase;
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class TranslationOptionList;
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class TranslationOption;
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class Hypothesis;
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class ChartHypothesis;
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class InputType;
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class ScoreComponentCollection;
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class Bitmap;
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class Range;
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class FactorMask;
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class InputPath;
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class StackVec;
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class DistortionScoreProducer;
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class TranslationTask;
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/** base class for all feature functions.
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*/
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class FeatureFunction
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{
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protected:
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/**< all the score producers in this run */
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static std::vector<FeatureFunction*> s_staticColl;
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std::string m_description, m_argLine;
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std::vector<std::vector<std::string> > m_args;
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bool m_tuneable;
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bool m_requireSortingAfterSourceContext;
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size_t m_verbosity;
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size_t m_numScoreComponents;
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size_t m_index; // index into vector covering ALL feature function values
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std::vector<bool> m_tuneableComponents;
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size_t m_numTuneableComponents;
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AllOptions::ptr m_options;
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//In case there's multiple producers with the same description
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static std::multiset<std::string> description_counts;
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public:
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static void Register(FeatureFunction* ff);
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private:
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// void Initialize(const std::string &line);
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void ParseLine(const std::string &line);
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public:
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static const std::vector<FeatureFunction*>& GetFeatureFunctions() {
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return s_staticColl;
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}
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static FeatureFunction &FindFeatureFunction(const std::string& name);
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static void Destroy();
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FeatureFunction(const std::string &line, bool registerNow);
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FeatureFunction(size_t numScoreComponents, const std::string &line, bool registerNow = true);
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virtual bool IsStateless() const = 0;
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virtual ~FeatureFunction();
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//! override to load model files
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virtual void Load(AllOptions::ptr const& opts) {
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m_options = opts;
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}
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AllOptions::ptr const&
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options() const {
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return m_options;
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}
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static void ResetDescriptionCounts() {
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description_counts.clear();
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}
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//! returns the number of scores that a subclass produces.
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//! For example, a language model conventionally produces 1, a translation table some arbitrary number, etc
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size_t GetNumScoreComponents() const {
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return m_numScoreComponents;
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}
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//! returns a string description of this producer
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const std::string& GetScoreProducerDescription() const {
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return m_description;
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}
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FName GetFeatureName(const std::string& name) const {
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return FName(GetScoreProducerDescription(), name);
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}
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//! if false, then this feature is not displayed in the n-best list.
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// use with care
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virtual bool IsTuneable() const {
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return m_tuneable;
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}
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virtual bool HasTuneableComponents() const {
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return m_numTuneableComponents;
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}
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virtual bool IsTuneableComponent(size_t i) const {
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if (m_numTuneableComponents == m_numScoreComponents) {
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return true;
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}
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return m_tuneableComponents[i];
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}
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virtual bool RequireSortingAfterSourceContext() const {
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return m_requireSortingAfterSourceContext;
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}
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virtual std::vector<float> DefaultWeights() const;
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size_t GetIndex() const;
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size_t SetIndex(size_t const idx);
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protected:
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virtual void
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CleanUpAfterSentenceProcessing(InputType const& source) { }
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public:
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//! Called before search and collecting of translation options
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virtual void
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InitializeForInput(ttasksptr const& ttask) { };
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// clean up temporary memory, called after processing each sentence
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virtual void
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CleanUpAfterSentenceProcessing(ttasksptr const& ttask);
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const std::string &
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GetArgLine() const {
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return m_argLine;
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}
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// given a target phrase containing only factors specified in mask
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// return true if the feature function can be evaluated
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virtual bool IsUseable(const FactorMask &mask) const = 0;
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// used by stateless ff and stateful ff. Calculate initial score
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// estimate during loading of phrase table
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//
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// source phrase is the substring that the phrase table uses to look
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// up the target phrase,
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//
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// may have more factors than actually need, but not guaranteed.
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// For SCFG decoding, the source contains non-terminals, NOT the raw
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// source from the input sentence
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virtual void
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EvaluateInIsolation(const Phrase &source, const TargetPhrase &targetPhrase,
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ScoreComponentCollection& scoreBreakdown,
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ScoreComponentCollection& estimatedScores) const = 0;
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// for context-dependent processing
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static void SetupAll(TranslationTask const& task);
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virtual void Setup(TranslationTask const& task) const { };
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// This method is called once all the translation options are retrieved from the phrase table, and
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// just before search.
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// 'inputPath' is guaranteed to be the raw substring from the input. No factors were added or taken away
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// 'stackVec' is a vector of chart cells that the RHS non-terms cover.
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// It is guaranteed to be in the same order as the non-terms in the source phrase.
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// For pb models, stackvec is NULL.
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// No FF should set estimatedScores in both overloads!
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virtual void EvaluateWithSourceContext(const InputType &input
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, const InputPath &inputPath
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, const TargetPhrase &targetPhrase
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, const StackVec *stackVec
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, ScoreComponentCollection &scoreBreakdown
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, ScoreComponentCollection *estimatedScores = NULL) const = 0;
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// This method is called once all the translation options are retrieved from the phrase table, and
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// just before search.
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// 'inputPath' is guaranteed to be the raw substring from the input. No factors were added or taken away
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// 'stackVec' is a vector of chart cells that the RHS non-terms cover.
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// It is guaranteed to be in the same order as the non-terms in the source phrase.
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// For pb models, stackvec is NULL.
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// No FF should set estimatedScores in both overloads!
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virtual void EvaluateTranslationOptionListWithSourceContext(const InputType &input
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, const TranslationOptionList &translationOptionList) const = 0;
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virtual void SetParameter(const std::string& key, const std::string& value);
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virtual void ReadParameters();
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virtual void SetTuneableComponents(const std::string& value);
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};
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}
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#endif
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