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#ifndef _DTRAIN_SCORE_H_
#define _DTRAIN_SCORE_H_
#include "kbestget.h"
using namespace std;
namespace dtrain
{
struct NgramCounts
{
unsigned N_;
map<unsigned, score_t> clipped_;
map<unsigned, score_t> sum_;
NgramCounts(const unsigned N) : N_(N) { Zero(); }
inline void
operator+=(const NgramCounts& rhs)
{
if (rhs.N_ > N_) Resize(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;
}
}
inline const NgramCounts
operator+(const NgramCounts &other) const
{
NgramCounts result = *this;
result += other;
return result;
}
inline void
operator*=(const score_t rhs)
{
for (unsigned i = 0; i < N_; i++) {
this->clipped_[i] *= rhs;
this->sum_[i] *= rhs;
}
}
inline void
Add(const unsigned count, const unsigned ref_count, const unsigned i)
{
assert(i < N_);
if (count > ref_count) {
clipped_[i] += ref_count;
} else {
clipped_[i] += count;
}
sum_[i] += count;
}
inline void
Zero()
{
for (unsigned i = 0; i < N_; i++) {
clipped_[i] = 0.;
sum_[i] = 0.;
}
}
inline void
One()
{
for (unsigned i = 0; i < N_; i++) {
clipped_[i] = 1.;
sum_[i] = 1.;
}
}
inline 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;
}
}
inline void Resize(unsigned N)
{
if (N == N_) return;
else if (N > N_) {
for (unsigned i = N_; i < N; i++) {
clipped_[i] = 0.;
sum_[i] = 0.;
}
} else { // N < N_
for (unsigned i = N_-1; i > N-1; i--) {
clipped_.erase(i);
sum_.erase(i);
}
}
N_ = N;
}
};
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 BleuScorer : public LocalScorer
{
score_t Bleu(NgramCounts& counts, const unsigned hyp_len, const unsigned ref_len);
score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned /*rank*/, const unsigned /*src_len*/);
};
struct StupidBleuScorer : public LocalScorer
{
score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned /*rank*/, const unsigned /*src_len*/);
};
struct SmoothBleuScorer : public LocalScorer
{
score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned /*rank*/, const unsigned /*src_len*/);
};
struct SmoothSingleBleuScorer : public LocalScorer
{
score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned /*rank*/, const unsigned /*src_len*/);
};
struct ApproxBleuScorer : public BleuScorer
{
NgramCounts glob_onebest_counts_;
unsigned glob_hyp_len_, glob_ref_len_, glob_src_len_;
score_t discount_;
ApproxBleuScorer(unsigned N, score_t d) : glob_onebest_counts_(NgramCounts(N)), discount_(d)
{
glob_hyp_len_ = glob_ref_len_ = glob_src_len_ = 0;
}
inline void Reset() {
glob_onebest_counts_.Zero();
glob_hyp_len_ = glob_ref_len_ = glob_src_len_ = 0.;
}
score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned rank, const unsigned src_len);
};
struct LinearBleuScorer : public BleuScorer
{
unsigned onebest_len_;
NgramCounts onebest_counts_;
LinearBleuScorer(unsigned N) : onebest_len_(1), onebest_counts_(N)
{
onebest_counts_.One();
}
score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned rank, const unsigned /*src_len*/);
inline void Reset() {
onebest_len_ = 1;
onebest_counts_.One();
}
};
} // namespace
#endif
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