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