diff options
Diffstat (limited to 'dtrain/pairsampling.h')
| -rw-r--r-- | dtrain/pairsampling.h | 36 |
1 files changed, 20 insertions, 16 deletions
diff --git a/dtrain/pairsampling.h b/dtrain/pairsampling.h index bb01cf4f..bac132c6 100644 --- a/dtrain/pairsampling.h +++ b/dtrain/pairsampling.h @@ -12,9 +12,16 @@ accept_pair(score_t a, score_t b, score_t threshold) return true; } +bool +cmp_hyp_by_score_d(ScoredHyp a, ScoredHyp b) +{ + return a.score > b.score; +} + inline void -all_pairs(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, score_t threshold, float _unused = 1) +all_pairs(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, score_t threshold, float _unused=1) { + sort(s->begin(), s->end(), cmp_hyp_by_score_d); unsigned sz = s->size(); for (unsigned i = 0; i < sz-1; i++) { for (unsigned j = i+1; j < sz; j++) { @@ -22,7 +29,8 @@ all_pairs(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, sc if (accept_pair((*s)[i].score, (*s)[j].score, threshold)) training.push_back(make_pair((*s)[i], (*s)[j])); } else { - training.push_back(make_pair((*s)[i], (*s)[j])); + if ((*s)[i].score != (*s)[j].score) + training.push_back(make_pair((*s)[i], (*s)[j])); } } } @@ -34,15 +42,11 @@ all_pairs(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, sc * compare top X to middle Y and low X * cmp middle Y to low X */ -bool -_XYX_cmp_hyp_by_score(ScoredHyp a, ScoredHyp b) -{ - return a.score > b.score; -} + inline void partXYX(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, score_t threshold, float hi_lo) { - sort(s->begin(), s->end(), _XYX_cmp_hyp_by_score); + sort(s->begin(), s->end(), cmp_hyp_by_score_d); unsigned sz = s->size(); unsigned sep = round(sz*hi_lo); for (unsigned i = 0; i < sep; i++) { @@ -51,7 +55,7 @@ partXYX(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, scor if (accept_pair((*s)[i].score, (*s)[j].score, threshold)) training.push_back(make_pair((*s)[i], (*s)[j])); } else { - if((*s)[i].score != (*s)[j].score) + if ((*s)[i].score != (*s)[j].score) training.push_back(make_pair((*s)[i], (*s)[j])); } } @@ -62,7 +66,7 @@ partXYX(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, scor if (accept_pair((*s)[i].score, (*s)[j].score, threshold)) training.push_back(make_pair((*s)[i], (*s)[j])); } else { - if((*s)[i].score != (*s)[j].score) + if ((*s)[i].score != (*s)[j].score) training.push_back(make_pair((*s)[i], (*s)[j])); } } @@ -77,17 +81,17 @@ partXYX(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, scor * cut = top 50 */ bool -_PRO_cmp_pair_by_diff(pair<ScoredHyp,ScoredHyp> a, pair<ScoredHyp,ScoredHyp> b) +_PRO_cmp_pair_by_diff_d(pair<ScoredHyp,ScoredHyp> a, pair<ScoredHyp,ScoredHyp> b) { return (fabs(a.first.score - a.second.score)) > (fabs(b.first.score - b.second.score)); } inline void -PROsampling(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, score_t threshold, float _unused = 1) +PROsampling(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, score_t threshold, float _unused=1) { - unsigned max_count = 5000, count = 0; + unsigned max_count = 5000, count = 0, sz = s->size(); bool b = false; - for (unsigned i = 0; i < s->size()-1; i++) { - for (unsigned j = i+1; j < s->size(); j++) { + for (unsigned i = 0; i < sz-1; i++) { + for (unsigned j = i+1; j < sz; j++) { if (accept_pair((*s)[i].score, (*s)[j].score, threshold)) { training.push_back(make_pair((*s)[i], (*s)[j])); if (++count == max_count) { @@ -99,7 +103,7 @@ PROsampling(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, if (b) break; } if (training.size() > 50) { - sort(training.begin(), training.end(), _PRO_cmp_pair_by_diff); + sort(training.begin(), training.end(), _PRO_cmp_pair_by_diff_d); training.erase(training.begin()+50, training.end()); } return; |