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#ifndef LINE_OPTIMIZER_H_
#define LINE_OPTIMIZER_H_
#include <vector>
#include "sparse_vector.h"
#include "error_surface.h"
#include "sampler.h"
class EvaluationMetric;
class Weights;
struct LineOptimizer {
// use MINIMIZE_SCORE for things like TER, WER
// MAXIMIZE_SCORE for things like BLEU
enum ScoreType { MAXIMIZE_SCORE, MINIMIZE_SCORE };
// merge all the error surfaces together into a global
// error surface and find (the middle of) the best segment
static double LineOptimize(
const EvaluationMetric* metric,
const std::vector<ErrorSurface>& envs,
const LineOptimizer::ScoreType type,
float* best_score,
const double epsilon = 1.0/65536.0);
// return a random vector of length 1 where all dimensions
// not listed in dimensions will be 0.
static void RandomUnitVector(const std::vector<int>& dimensions,
SparseVector<double>* axis,
RandomNumberGenerator<boost::mt19937>* rng);
// generate a list of directions to optimize; the list will
// contain the orthogonal vectors corresponding to the dimensions in
// primary and then additional_random_directions directions in those
// dimensions as well. All vectors will be length 1.
static void CreateOptimizationDirections(
const std::vector<int>& primary,
int additional_random_directions,
RandomNumberGenerator<boost::mt19937>* rng,
std::vector<SparseVector<double> >* dirs
, bool include_primary=true
);
};
#endif
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