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123 lines
3.3 KiB
C++
123 lines
3.3 KiB
C++
#ifndef MERT_OPTIMIZER_H_
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#define MERT_OPTIMIZER_H_
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#include <vector>
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#include <string>
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#include "Data.h"
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#include "FeatureData.h"
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#include "Scorer.h"
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#include "Types.h"
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static const float kMaxFloat = std::numeric_limits<float>::max();
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namespace MosesTuning
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{
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class Point;
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/**
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* Abstract optimizer class.
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*/
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class Optimizer
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{
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protected:
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Scorer *m_scorer; // no accessor for them only child can use them
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FeatureDataHandle m_feature_data; // no accessor for them only child can use them
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unsigned int m_num_random_directions;
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const std::vector<bool>& m_positive;
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public:
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Optimizer(unsigned Pd, const std::vector<unsigned>& i2O, const std::vector<bool>& positive, const std::vector<parameter_t>& start, unsigned int nrandom);
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void SetScorer(Scorer *scorer) {
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m_scorer = scorer;
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}
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void SetFeatureData(FeatureDataHandle feature_data) {
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m_feature_data = feature_data;
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}
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virtual ~Optimizer();
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unsigned size() const {
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return m_feature_data ? m_feature_data->size() : 0;
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}
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/**
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* Generic wrapper around TrueRun to check a few things. Non virtual.
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*/
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statscore_t Run(Point&) const;
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/**
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* Main function that performs an optimization.
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*/
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virtual statscore_t TrueRun(Point&) const = 0;
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/**
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* Given a set of lambdas, get the nbest for each sentence.
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*/
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void Get1bests(const Point& param,std::vector<unsigned>& bests) const;
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/**
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* Given a set of nbests, get the Statistical score.
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*/
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statscore_t GetStatScore(const std::vector<unsigned>& nbests) const {
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return m_scorer->score(nbests);
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}
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statscore_t GetStatScore(const Point& param) const;
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std::vector<statscore_t> GetIncStatScore(const std::vector<unsigned>& ref, const std::vector<std::vector<std::pair<unsigned,unsigned> > >& diffs) const;
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/**
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* Get the optimal Lambda and the best score in a particular direction from a given Point.
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*/
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statscore_t LineOptimize(const Point& start, const Point& direction, Point& best) const;
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};
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/**
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* Default basic optimizer.
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* This class implements Powell's method.
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*/
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class SimpleOptimizer : public Optimizer
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{
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private:
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const float kEPS;
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public:
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SimpleOptimizer(unsigned dim, const std::vector<unsigned>& i2O, const std::vector<bool>& positive,
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const std::vector<parameter_t>& start, unsigned int nrandom)
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: Optimizer(dim, i2O, positive, start,nrandom), kEPS(0.0001f) {}
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virtual statscore_t TrueRun(Point&) const;
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};
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/**
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* An optimizer with random directions.
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*/
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class RandomDirectionOptimizer : public Optimizer
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{
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private:
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const float kEPS;
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public:
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RandomDirectionOptimizer(unsigned dim, const std::vector<unsigned>& i2O, const std::vector<bool>& positive,
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const std::vector<parameter_t>& start, unsigned int nrandom)
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: Optimizer(dim, i2O, positive, start, nrandom), kEPS(0.0001f) {}
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virtual statscore_t TrueRun(Point&) const;
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};
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/**
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* Dumb baseline optimizer: just picks a random point and quits.
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*/
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class RandomOptimizer : public Optimizer
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{
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public:
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RandomOptimizer(unsigned dim, const std::vector<unsigned>& i2O, const std::vector<bool>& positive,
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const std::vector<parameter_t>& start, unsigned int nrandom)
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: Optimizer(dim, i2O, positive, start, nrandom) {}
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virtual statscore_t TrueRun(Point&) const;
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};
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}
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#endif // OPTIMIZER_H
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