mosesdecoder/mert/Optimizer.h
Tetsuo Kiso e7a2483b22 mert: Prefix private members with "m_" except TER.
Squashed commit of the following:

- Clean up PRO.
- Clean up ScoreStats.
- Clean up ScoreData.
- Clean up ScoreArray.
- Remove unnecessary headers.
- Clean up ScopedVector.
- Clean up Point.
- Clean up PerScorer.
- Clean up Optimizer.
- Clean up MergeScorer.
- Clean up InterpolatedScorer.
- Clean up FileStream.
- Clean up FeatureStats.
- Remove inefficient string concatenation.
- Clean up FeatureData.
- Clean up FeatureArray.
- Clean up Data.
2012-03-10 17:12:34 +09:00

137 lines
3.4 KiB
C++

#ifndef MERT_OPTIMIZER_H_
#define MERT_OPTIMIZER_H_
#include <vector>
#include <string>
#include "Data.h"
#include "FeatureData.h"
#include "Scorer.h"
#include "Types.h"
using namespace std;
typedef float featurescore;
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;
public:
Optimizer(unsigned Pd, vector<unsigned> i2O, 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,vector<unsigned>& bests) const;
/**
* Given a set of nbests, get the Statistical score.
*/
statscore_t GetStatScore(const vector<unsigned>& nbests) const {
return m_scorer->score(nbests);
}
statscore_t GetStatScore(const Point& param) const;
vector<statscore_t> GetIncStatScore(vector<unsigned> ref, vector<vector<pair<unsigned,unsigned> > >) 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, vector<unsigned> i2O, vector<parameter_t> start, unsigned int nrandom)
: Optimizer(dim, i2O, start,nrandom), kEPS(0.0001) {}
virtual statscore_t TrueRun(Point&) const;
};
/**
* An optimizer with random directions.
*/
class RandomDirectionOptimizer : public Optimizer
{
private:
const float kEPS;
public:
RandomDirectionOptimizer(unsigned dim, vector<unsigned> i2O, vector<parameter_t> start, unsigned int nrandom)
: Optimizer(dim, i2O, start, nrandom), kEPS(0.0001) {}
virtual statscore_t TrueRun(Point&) const;
};
/**
* Dumb baseline optimizer: just picks a random point and quits.
*/
class RandomOptimizer : public Optimizer
{
public:
RandomOptimizer(unsigned dim, vector<unsigned> i2O, vector<parameter_t> start, unsigned int nrandom)
: Optimizer(dim, i2O, start, nrandom) {}
virtual statscore_t TrueRun(Point&) const;
};
class OptimizerFactory
{
public:
static vector<string> GetTypeNames();
static Optimizer* BuildOptimizer(unsigned dim, vector<unsigned> tooptimize, vector<parameter_t> start, const string& type, unsigned int nrandom);
private:
OptimizerFactory() {}
~OptimizerFactory() {}
// Add new optimizer here BEFORE NOPTIMZER
enum OptType {
POWELL = 0,
RANDOM_DIRECTION = 1,
RANDOM,
NOPTIMIZER
};
// Get optimizer type.
static OptType GetOType(const string& type);
// Setup optimization types.
static void SetTypeNames();
static vector<string> m_type_names;
};
#endif // OPTIMIZER_H