1 files changed, 60 insertions, 0 deletions
diff --git a/training/candidate_set.h b/training/candidate_set.h
new file mode 100644
index 00000000..9d326ed0
--- /dev/null
+++ b/training/candidate_set.h
@@ -0,0 +1,60 @@
+#ifndef _CANDIDATE_SET_H_
+#define _CANDIDATE_SET_H_
+
+#include <vector>
+#include <algorithm>
+
+#include "ns.h"
+#include "wordid.h"
+#include "sparse_vector.h"
+
+class Hypergraph;
+
+namespace training {
+
+struct Candidate {
+  Candidate() {}
+  Candidate(const std::vector<WordID>& e, const SparseVector<double>& fm) :
+      ewords(e),
+      fmap(fm) {}
+  Candidate(const std::vector<WordID>& e,
+            const SparseVector<double>& fm,
+            const SegmentEvaluator& se) :
+      ewords(e),
+      fmap(fm) {
+    se.Evaluate(ewords, &eval_feats);
+  }
+
+  void swap(Candidate& other) {
+    eval_feats.swap(other.eval_feats);
+    ewords.swap(other.ewords);
+    fmap.swap(other.fmap);
+  }
+
+  std::vector<WordID> ewords;
+  SparseVector<double> fmap;
+  SufficientStats eval_feats;
+};
+
+// represents some kind of collection of translation candidates, e.g.
+// aggregated k-best lists, sample lists, etc.
+class CandidateSet {
+ public:
+  CandidateSet() {}
+  inline size_t size() const { return cs.size(); }
+  const Candidate& operator[](size_t i) const { return cs[i]; }
+
+  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
+  // TODO add code to draw k samples
+
+ private:
+  void Dedup();
+  std::vector<Candidate> cs;
+};
+
+}
+
+#endif