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#ifndef _DTRAIN_SCORE_H_
#define _DTRAIN_SCORE_H_
#include <iostream>
#include <vector>
#include <map>
#include <cassert>
#include <cmath>
#include "kbestget.h"
#include "wordid.h" // cdec
using namespace std;
namespace dtrain
{
struct NgramCounts
{
unsigned N_;
map<unsigned, unsigned> clipped;
map<unsigned, unsigned> sum;
NgramCounts(const unsigned N) : N_(N) { Zero(); }
void
operator+=(const NgramCounts& rhs)
{
assert(N_ == rhs.N_);
for (unsigned i = 0; i < N_; i++) {
this->clipped[i] += rhs.clipped.find(i)->second;
this->sum[i] += rhs.sum.find(i)->second;
}
}
const NgramCounts
operator+(const NgramCounts &other) const
{
NgramCounts result = *this;
result += other;
return result;
}
void
Add(unsigned count, unsigned ref_count, unsigned i)
{
assert(i < N_);
if (count > ref_count) {
clipped[i] += ref_count;
} else {
clipped[i] += count;
}
sum[i] += count;
}
void
Zero()
{
unsigned i;
for (i = 0; i < N_; i++) {
clipped[i] = 0;
sum[i] = 0;
}
}
void
Print()
{
for (unsigned i = 0; i < N_; i++) {
cout << i+1 << "grams (clipped):\t" << clipped[i] << endl;
cout << i+1 << "grams:\t\t\t" << sum[i] << endl;
}
}
};
typedef map<vector<WordID>, unsigned> Ngrams;
inline Ngrams
make_ngrams(const vector<WordID>& s, const unsigned N)
{
Ngrams ngrams;
vector<WordID> ng;
for (size_t i = 0; i < s.size(); i++) {
ng.clear();
for (unsigned j = i; j < min(i+N, s.size()); j++) {
ng.push_back(s[j]);
ngrams[ng]++;
}
}
return ngrams;
}
inline NgramCounts
make_ngram_counts(const vector<WordID>& hyp, const vector<WordID>& ref, const unsigned N)
{
Ngrams hyp_ngrams = make_ngrams(hyp, N);
Ngrams ref_ngrams = make_ngrams(ref, N);
NgramCounts counts(N);
Ngrams::iterator it;
Ngrams::iterator ti;
for (it = hyp_ngrams.begin(); it != hyp_ngrams.end(); it++) {
ti = ref_ngrams.find(it->first);
if (ti != ref_ngrams.end()) {
counts.Add(it->second, ti->second, it->first.size() - 1);
} else {
counts.Add(it->second, 0, it->first.size() - 1);
}
}
return counts;
}
struct LocalScorer
{
unsigned N_;
vector<score_t> w_;
virtual score_t
Score(ScoredHyp& hyp, vector<WordID>& ref_ids, unsigned id)=0;
void
Init(unsigned N, vector<score_t> weights)
{
assert(N > 0);
N_ = N;
if (weights.empty()) for (unsigned i = 0; i < N_; i++) w_.push_back(1./N_);
else w_ = weights;
}
score_t
brevity_penaly(const unsigned hyp_len, const unsigned ref_len)
{
if (hyp_len > ref_len) return 1;
return exp(1 - (score_t)ref_len/hyp_len);
}
};
struct BleuScorer : public LocalScorer
{
score_t Bleu(NgramCounts& counts, const unsigned hyp_len, const unsigned ref_len);
score_t Score(ScoredHyp& hyp, vector<WordID>& ref_ids, unsigned id);
};
struct StupidBleuScorer : public LocalScorer
{
score_t Score(ScoredHyp& hyp, vector<WordID>& ref_ids, unsigned id);
};
struct SmoothBleuScorer : public LocalScorer
{
score_t Score(ScoredHyp& hyp, vector<WordID>& ref_ids, unsigned id);
};
// FIXME
/*struct ApproxBleuScorer : public LocalScorer
{
NgramCounts glob_onebest_counts;
unsigned glob_hyp_len, glob_ref_len;
void Prep(NgramCounts& counts, const unsigned hyp_len, const unsigned ref_len);
void Reset();
score_t Score(ScoredHyp& hyp, vector<WordID>& ref_ids, unsigned id);
ApproxBleuScorer()
{
glob_onebest_counts.Zero();
glob_hyp_len = 0;
glob_ref_len = 0;
}
};*/
} // namespace
#endif
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