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author | Patrick Simianer <simianer@cl.uni-heidelberg.de> | 2012-05-31 13:57:24 +0200 |
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committer | Patrick Simianer <simianer@cl.uni-heidelberg.de> | 2012-05-31 13:57:24 +0200 |
commit | 6f6601111710aa67eee5169e5b7d89102cc33bb8 (patch) | |
tree | 0872544abd6bc76162f3f80eb3920999afbf2c34 /training/candidate_set.h | |
parent | 8cee8b565a9c56a7732365e9563f52ff3c4ff7fd (diff) | |
parent | 090a64e73f94a6a35e5364a9d416dcf75c0a2938 (diff) |
Merge remote-tracking branch 'upstream/master'
Diffstat (limited to 'training/candidate_set.h')
-rw-r--r-- | training/candidate_set.h | 60 |
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 |