unigram pyp lm added

1 files changed, 47 insertions, 0 deletions

diff --git a/utils/alias_sampler.h b/utils/alias_sampler.h
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+++ b/utils/alias_sampler.h
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+#ifndef _ALIAS_SAMPLER_H_
+#define _ALIAS_SAMPLER_H_
+
+#include <vector>
+#include <limits>
+
+// R. A. Kronmal and A. V. Peterson, Jr. (1977) On the alias method for
+// generating random variables from a discrete distribution. In The American
+// Statistician, Vol. 33, No. 4. Pages 214--218.
+//
+// Intuition: a multinomial with N outcomes can be rewritten as a uniform
+// mixture of N Bernoulli distributions. The ith Bernoulli returns i with
+// probability F[i], otherwise it returns an "alias" value L[i]. The
+// constructor computes the F's and L's given an arbitrary multionimial p in
+// O(n) time and Draw returns samples in O(1) time.
+struct AliasSampler {
+  explicit AliasSampler(const std::vector<double>& p) :
+      cutoffs_(p.size()),
+      aliases_(p.size(), std::numeric_limits<unsigned>::max()) {
+    const unsigned N = p.size();
+    std::vector<unsigned> s,g;
+    for (unsigned i = 0; i < N; ++i) {
+      const double cutoff = cutoffs_[i] = N * p[i];
+      if (cutoff >= 1.0) g.push_back(i); else s.push_back(i);
+    }
+    while(!s.empty() && !g.empty()) {
+      const unsigned k = g.back();
+      const unsigned j = s.back();
+      aliases_[j] = k;
+      cutoffs_[k] -= 1.0 - cutoffs_[j];
+      s.pop_back();
+      if (cutoffs_[k] < 1.0) {
+        g.pop_back();
+        s.push_back(k);
+      }
+    }
+  }
+  template <typename Uniform01Generator>
+  unsigned Draw(Uniform01Generator& u01) const {
+    const unsigned n = u01() * cutoffs_.size();
+    if (u01() > cutoffs_[n]) return aliases_[n]; else return n;
+  }
+  std::vector<double> cutoffs_;    // F
+  std::vector<unsigned> aliases_;  // L
+};
+
+#endif