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authorAvneesh Saluja <asaluja@gmail.com>2013-03-28 18:28:16 -0700
committerAvneesh Saluja <asaluja@gmail.com>2013-03-28 18:28:16 -0700
commit3d8d656fa7911524e0e6885647173474524e0784 (patch)
tree81b1ee2fcb67980376d03f0aa48e42e53abff222 /training/utils/candidate_set.h
parentbe7f57fdd484e063775d7abf083b9fa4c403b610 (diff)
parent96fedabebafe7a38a6d5928be8fff767e411d705 (diff)
fixed conflicts
Diffstat (limited to 'training/utils/candidate_set.h')
-rw-r--r--training/utils/candidate_set.h60
1 files changed, 60 insertions, 0 deletions
diff --git a/training/utils/candidate_set.h b/training/utils/candidate_set.h
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+#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