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-rw-r--r--training/mira/kbest_cut_mira.cc11
1 files changed, 6 insertions, 5 deletions
diff --git a/training/mira/kbest_cut_mira.cc b/training/mira/kbest_cut_mira.cc
index 990609d7..e0b6eecb 100644
--- a/training/mira/kbest_cut_mira.cc
+++ b/training/mira/kbest_cut_mira.cc
@@ -133,6 +133,7 @@ static const int MAX_SMO = 10;
int cur_pass;
struct HypothesisInfo {
+ HypothesisInfo() : mt_metric(), hope(), fear(), alpha(), oracle_loss() {}
SparseVector<double> features;
vector<WordID> hyp;
double mt_metric;
@@ -414,8 +415,9 @@ struct TrainingObserver : public DecoderObserver {
template <class Filter>
void UpdateOracles(int sent_id, const Hypergraph& forest) {
- if (stream) sent_id = 0;
+ if (stream) sent_id = 0;
bool PRINT_LIST= false;
+ assert(sent_id < oracles.size());
vector<boost::shared_ptr<HypothesisInfo> >& cur_good = oracles[sent_id].good;
vector<boost::shared_ptr<HypothesisInfo> >& cur_bad = oracles[sent_id].bad;
//TODO: look at keeping previous iterations hypothesis lists around
@@ -810,7 +812,6 @@ int main(int argc, char** argv) {
}
else if(optimizer == 1) //sgd - nonadapted step size
{
-
lambdas += (cur_good.features) * max_step_size;
lambdas -= (cur_bad.features) * max_step_size;
}
@@ -928,11 +929,11 @@ int main(int argc, char** argv) {
lambdas += (cur_pair[1]->features) * step_size;
lambdas -= (cur_pair[0]->features) * step_size;
- cerr << " Lambdas " << lambdas << endl;
- //reload weights based on update
+ //reload weights based on update
dense_weights.clear();
lambdas.init_vector(&dense_weights);
+ ShowLargestFeatures(dense_weights);
dense_w_local = dense_weights;
iter++;
@@ -971,7 +972,7 @@ int main(int argc, char** argv) {
for(int u=0;u!=cur_constraint.size();u++)
{
- cerr << cur_constraint[u]->alpha << " " << cur_constraint[u]->hope << " " << cur_constraint[u]->fear << endl;
+ cerr << "alpha=" << cur_constraint[u]->alpha << " hope=" << cur_constraint[u]->hope << " fear=" << cur_constraint[u]->fear << endl;
temp_objective += cur_constraint[u]->alpha * cur_constraint[u]->fear;
}
objective += temp_objective;