major restructure of the training code

1 files changed, 0 insertions, 60 deletions

diff --git a/training/candidate_set.h b/training/candidate_set.h
deleted file mode 100644
index 9d326ed0..00000000
--- a/training/candidate_set.h
+++ /dev/null
@@ -1,60 +0,0 @@
-#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