1 files changed, 144 insertions, 0 deletions
diff --git a/dtrain/score.h b/dtrain/score.h
new file mode 100644
index 00000000..85cd0317
--- /dev/null
+++ b/dtrain/score.h
@@ -0,0 +1,144 @@
+#ifndef _DTRAIN_SCORE_H_
+#define _DTRAIN_SCORE_H_
+
+#include "kbestget.h"
+
+using namespace std;
+
+namespace dtrain
+{
+
+
+struct NgramCounts
+{
+  unsigned N_;
+  map<unsigned, unsigned> clipped;
+  map<unsigned, unsigned> sum;
+
+  NgramCounts(const unsigned N) : N_(N) { Zero(); } 
+
+  inline void
+  operator+=(const NgramCounts& rhs)
+  {
+    assert(N_ == rhs.N_);
+    for (unsigned i = 0; i < N_; i++) {
+      this->clipped[i] += rhs.clipped.find(i)->second;
+      this->sum[i] += rhs.sum.find(i)->second;
+    }
+  }
+
+  inline const NgramCounts
+  operator+(const NgramCounts &other) const
+  {
+    NgramCounts result = *this;
+    result += other;
+    return result;
+  }
+
+  inline void
+  Add(const unsigned count, const unsigned ref_count, const unsigned i)
+  {
+    assert(i < N_);
+    if (count > ref_count) {
+      clipped[i] += ref_count;
+    } else {
+      clipped[i] += count;
+    }
+    sum[i] += count;
+  }
+
+  inline void
+  Zero()
+  {
+    unsigned i;
+    for (i = 0; i < N_; i++) {
+      clipped[i] = 0;
+      sum[i] = 0;
+    }
+  }
+
+  inline void
+  Print()
+  {
+    for (unsigned i = 0; i < N_; i++) {
+      cout << i+1 << "grams (clipped):\t" << clipped[i] << endl;
+      cout << i+1 << "grams:\t\t\t" << sum[i] << endl;
+    }
+  }
+};
+
+typedef map<vector<WordID>, unsigned> Ngrams;
+
+inline Ngrams
+make_ngrams(const vector<WordID>& s, const unsigned N)
+{
+  Ngrams ngrams;
+  vector<WordID> ng;
+  for (size_t i = 0; i < s.size(); i++) {
+    ng.clear();
+    for (unsigned j = i; j < min(i+N, s.size()); j++) {
+      ng.push_back(s[j]);
+      ngrams[ng]++;
+    }
+  }
+  return ngrams;
+}
+
+inline NgramCounts
+make_ngram_counts(const vector<WordID>& hyp, const vector<WordID>& ref, const unsigned N)
+{
+  Ngrams hyp_ngrams = make_ngrams(hyp, N);
+  Ngrams ref_ngrams = make_ngrams(ref, N);
+  NgramCounts counts(N);
+  Ngrams::iterator it;
+  Ngrams::iterator ti;
+  for (it = hyp_ngrams.begin(); it != hyp_ngrams.end(); it++) {
+    ti = ref_ngrams.find(it->first);
+    if (ti != ref_ngrams.end()) {
+      counts.Add(it->second, ti->second, it->first.size() - 1);
+    } else {
+      counts.Add(it->second, 0, it->first.size() - 1);
+    }
+  }
+  return counts;
+}
+
+struct BleuScorer : public LocalScorer
+{
+  score_t Bleu(NgramCounts& counts, const unsigned hyp_len, const unsigned ref_len);
+  score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned rank);
+};
+
+struct StupidBleuScorer : public LocalScorer
+{
+  score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned rank);
+};
+
+struct SmoothBleuScorer : public LocalScorer
+{
+  score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned rank);
+};
+
+struct ApproxBleuScorer : public BleuScorer
+{
+  NgramCounts glob_onebest_counts;
+  unsigned glob_hyp_len, glob_ref_len;
+
+  ApproxBleuScorer(unsigned N) : glob_onebest_counts(NgramCounts(N))
+  {
+    glob_hyp_len = glob_ref_len = 0;
+  }
+
+  inline void Reset() {
+    glob_onebest_counts.Zero();
+    glob_hyp_len = glob_ref_len = 0;
+  }
+
+  score_t Score(vector<WordID>& hyp, vector<WordID>& ref, const unsigned rank);
+};
+
+
+} // namespace
+
+#endif
+