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-rw-r--r--pro-train/mr_pro_map.cc9
1 files changed, 4 insertions, 5 deletions
diff --git a/pro-train/mr_pro_map.cc b/pro-train/mr_pro_map.cc
index 2aa0dc6f..bb13fdf4 100644
--- a/pro-train/mr_pro_map.cc
+++ b/pro-train/mr_pro_map.cc
@@ -92,7 +92,6 @@ struct DiffOrder {
void Sample(const unsigned gamma,
const unsigned xi,
const training::CandidateSet& J_i,
- const SegmentEvaluator& scorer,
const EvaluationMetric* metric,
vector<TrainingInstance>* pv) {
const bool invert_score = metric->IsErrorMetric();
@@ -102,8 +101,8 @@ void Sample(const unsigned gamma,
const size_t a = rng->inclusive(0, J_i.size() - 1)();
const size_t b = rng->inclusive(0, J_i.size() - 1)();
if (a == b) continue;
- float ga = J_i[a].g(scorer, metric);
- float gb = J_i[b].g(scorer, metric);
+ float ga = metric->ComputeScore(J_i[a].score_stats);
+ float gb = metric->ComputeScore(J_i[b].score_stats);
bool positive = gb < ga;
if (invert_score) positive = !positive;
const float gdiff = fabs(ga - gb);
@@ -187,10 +186,10 @@ int main(int argc, char** argv) {
J_i.ReadFromFile(kbest_file);
HypergraphIO::ReadFromJSON(rf.stream(), &hg);
hg.Reweight(weights);
- J_i.AddKBestCandidates(hg, kbest_size);
+ J_i.AddKBestCandidates(hg, kbest_size, ds[sent_id]);
J_i.WriteToFile(kbest_file);
- Sample(gamma, xi, J_i, *ds[sent_id], metric, &v);
+ Sample(gamma, xi, J_i, metric, &v);
for (unsigned i = 0; i < v.size(); ++i) {
const TrainingInstance& vi = v[i];
cout << vi.y << "\t" << vi.x << endl;