adaptive hope-fear learner

2 files changed, 16 insertions, 1 deletions

diff --git a/training/utils/candidate_set.cc b/training/utils/candidate_set.cc
index 33dae9a3..36f5b271 100644
--- a/training/utils/candidate_set.cc
+++ b/training/utils/candidate_set.cc
@@ -171,4 +171,19 @@ void CandidateSet::AddKBestCandidates(const Hypergraph& hg, size_t kbest_size, c
   Dedup();
 }
 
+void CandidateSet::AddUniqueKBestCandidates(const Hypergraph& hg, size_t kbest_size, const SegmentEvaluator* scorer) {
+  typedef KBest::KBestDerivations<vector<WordID>, ESentenceTraversal, KBest::FilterUnique> K;
+  K kbest(hg, kbest_size);
+
+  for (unsigned i = 0; i < kbest_size; ++i) {
+    const K::Derivation* d =
+      kbest.LazyKthBest(hg.nodes_.size() - 1, i);
+    if (!d) break;
+    cs.push_back(Candidate(d->yield, d->feature_values));
+    if (scorer)
+      scorer->Evaluate(d->yield, &cs.back().eval_feats);
+  }
+  Dedup();
+}
+
 }
diff --git a/training/utils/candidate_set.h b/training/utils/candidate_set.h
index 9d326ed0..17a650f5 100644
--- a/training/utils/candidate_set.h
+++ b/training/utils/candidate_set.h
@@ -47,7 +47,7 @@ class CandidateSet {
   void ReadFromFile(const std::string& file);
   void WriteToFile(const std::string& file) const;
   void AddKBestCandidates(const Hypergraph& hg, size_t kbest_size, const SegmentEvaluator* scorer = NULL);
-  // TODO add code to do unique k-best
+  void AddUniqueKBestCandidates(const Hypergraph& hg, size_t kbest_size, const SegmentEvaluator* scorer = NULL);
   // TODO add code to draw k samples
 
  private: