crp with explicit table tracking

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@618 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 19 insertions, 15 deletions

diff --git a/utils/sampler.h b/utils/sampler.h
index 5fef45d0..f75d96b6 100644
--- a/utils/sampler.h
+++ b/utils/sampler.h
@@ -18,7 +18,7 @@
 
 #include "prob.h"
 
-struct SampleSet;
+template <typename F> struct SampleSet;
 
 template <typename RNG>
 struct RandomNumberGenerator {
@@ -45,7 +45,8 @@ struct RandomNumberGenerator {
     m_generator.seed(seed);
   }
 
-  size_t SelectSample(const prob_t& a, const prob_t& b, double T = 1.0) {
+  template <typename F>
+  size_t SelectSample(const F& a, const F& b, double T = 1.0) {
     if (T == 1.0) {
       if (this->next() > (a / (a + b))) return 1; else return 0;
     } else {
@@ -54,7 +55,8 @@ struct RandomNumberGenerator {
   }
 
   // T is the annealing temperature, if desired
-  size_t SelectSample(const SampleSet& ss, double T = 1.0);
+  template <typename F>
+  size_t SelectSample(const SampleSet<F>& ss, double T = 1.0);
 
   // draw a value from U(0,1)
   double next() {return m_random();}
@@ -94,36 +96,38 @@ struct RandomNumberGenerator {
 
 typedef RandomNumberGenerator<boost::mt19937> MT19937;
 
+template <typename F = double>
 class SampleSet {
  public:
-  const prob_t& operator[](int i) const { return m_scores[i]; }
-  prob_t& operator[](int i) { return m_scores[i]; }
+  const F& operator[](int i) const { return m_scores[i]; }
+  F& operator[](int i) { return m_scores[i]; }
   bool empty() const { return m_scores.empty(); }
   void add(const prob_t& s) { m_scores.push_back(s); }
   void clear() { m_scores.clear(); }
   size_t size() const { return m_scores.size(); }
   void resize(int size) { m_scores.resize(size); }
-  std::vector<prob_t> m_scores;
+  std::vector<F> m_scores;
 };
 
 template <typename RNG>
-size_t RandomNumberGenerator<RNG>::SelectSample(const SampleSet& ss, double T) {
+template <typename F>
+size_t RandomNumberGenerator<RNG>::SelectSample(const SampleSet<F>& ss, double T) {
   assert(T > 0.0);
   assert(ss.m_scores.size() > 0);
   if (ss.m_scores.size() == 1) return 0;
-  const prob_t annealing_factor(1.0 / T);
-  const bool anneal = (annealing_factor != prob_t::One());
-  prob_t sum = prob_t::Zero();
+  const double annealing_factor = 1.0 / T;
+  const bool anneal = (T != 1.0);
+  F sum = F(0);
   if (anneal) {
     for (int i = 0; i < ss.m_scores.size(); ++i)
-      sum += ss.m_scores[i].pow(annealing_factor);  // p^(1/T)
+      sum += pow(ss.m_scores[i], annealing_factor);  // p^(1/T)
   } else {
-    sum = std::accumulate(ss.m_scores.begin(), ss.m_scores.end(), prob_t::Zero());
+    sum = std::accumulate(ss.m_scores.begin(), ss.m_scores.end(), F(0));
   }
   //for (size_t i = 0; i < ss.m_scores.size(); ++i) std::cerr << ss.m_scores[i] << ",";
   //std::cerr << std::endl;
 
-  prob_t random(this->next());    // random number between 0 and 1
+  F random(this->next());    // random number between 0 and 1
   random *= sum;                  // scale with normalization factor
   //std::cerr << "Random number " << random << std::endl;
 
@@ -131,9 +135,9 @@ size_t RandomNumberGenerator<RNG>::SelectSample(const SampleSet& ss, double T) {
   size_t position = 1;
   sum = ss.m_scores[0];
   if (anneal) {
-    sum.poweq(annealing_factor);
+    sum = pow(sum, annealing_factor);
     for (; position < ss.m_scores.size() && sum < random; ++position)
-      sum += ss.m_scores[position].pow(annealing_factor);
+      sum += pow(ss.m_scores[position], annealing_factor);
   } else {
     for (; position < ss.m_scores.size() && sum < random; ++position)
       sum += ss.m_scores[position];