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#ifndef _CANDIDATE_SET_H_
#define _CANDIDATE_SET_H_
#include <vector>
#include <algorithm>
#include "wordid.h"
#include "sparse_vector.h"
class Hypergraph;
struct SegmentEvaluator;
struct EvaluationMetric;
namespace training {
struct Candidate {
Candidate() : g_(-100.0f) {}
Candidate(const std::vector<WordID>& e, const SparseVector<double>& fm) : ewords(e), fmap(fm), g_(-100.0f) {}
std::vector<WordID> ewords;
SparseVector<double> fmap;
double g(const SegmentEvaluator& scorer, const EvaluationMetric* metric) const;
void swap(Candidate& other) {
std::swap(g_, other.g_);
ewords.swap(other.ewords);
fmap.swap(other.fmap);
}
private:
mutable float g_;
//SufficientStats score_stats;
};
// represents some kind of collection of translation candidates, e.g.
// aggregated k-best lists, sample lists, etc.
class CandidateSet {
public:
CandidateSet() {}
inline size_t size() const { return cs.size(); }
const Candidate& operator[](size_t i) const { return cs[i]; }
void ReadFromFile(const std::string& file);
void WriteToFile(const std::string& file) const;
void AddKBestCandidates(const Hypergraph& hg, size_t kbest_size);
// TODO add code to do unique k-best
// TODO add code to draw k samples
private:
void Dedup();
std::vector<Candidate> cs;
};
}
#endif
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