void
DefaultCandidateSetScorer::Score(Model *model,
CandidateSet &candidates, bool training) {
// N.B.: We assume there is at least one candidate!
CandidateSet::iterator it = candidates.begin();
// Score first candidate, which is perforce the best candidate so far.
model->ScoreCandidate(*(*it), training);
CandidateSet::iterator best_it = it;
CandidateSet::iterator gold_it = it;
++it;
// Score any and all remaining candidates.
for ( ; it != candidates.end(); ++it) {
Candidate &candidate = *(*it);
model->ScoreCandidate(candidate, training);
if (model->score_comparator()->Compare(*model, candidate, **best_it) > 0) {
best_it = it;
}
if (model->gold_comparator()->Compare(*model, candidate, **gold_it) > 0) {
gold_it = it;
}
}
candidates.set_best_scoring_index((*best_it)->index());
candidates.set_gold_index((*gold_it)->index());
}
void
RandomPairCandidateSetScorer::Score(Model *model,
CandidateSet &candidates, bool training) {
// First, pick two candidate indices at random.
size_t idx1 = GetRandomIndex(candidates.size());
size_t idx2 = GetRandomIndex(candidates.size());
Candidate &c1 = candidates.Get(idx1);
Candidate &c2 = candidates.Get(idx2);
// Next, just score those two candidates.
model->ScoreCandidate(c1, training);
model->ScoreCandidate(c2, training);
// Finally, set indices of best scoring and gold amongst just those two.
int score_cmp = model->score_comparator()->Compare(*model, c1, c2);
candidates.set_best_scoring_index(score_cmp > 0 ? c1.index() : c2.index());
int gold_cmp = model->gold_comparator()->Compare(*model, c1, c2);
candidates.set_gold_index(gold_cmp > 0 ? c1.index() : c2.index());
}
