move model 1 code

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@665 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 13 insertions, 12 deletions

diff --git a/training/model1.cc b/training/model1.cc
index f571700f..92a70985 100644
--- a/training/model1.cc
+++ b/training/model1.cc
@@ -1,4 +1,5 @@
 #include <iostream>
+#include <cmath>
 
 #include "lattice.h"
 #include "stringlib.h"
@@ -14,7 +15,7 @@ int main(int argc, char** argv) {
     return 1;
   }
   const int ITERATIONS = 5;
-  const prob_t BEAM_THRESHOLD(0.0001);
+  const double BEAM_THRESHOLD = 0.0001;
   TTable tt;
   const WordID kNULL = TD::Convert("<eps>");
   bool use_null = true;
@@ -24,7 +25,7 @@ int main(int argc, char** argv) {
     cerr << "ITERATION " << (iter + 1) << (final_iteration ? " (FINAL)" : "") << endl;
     ReadFile rf(argv[1]);
     istream& in = *rf.stream();
-    prob_t likelihood = prob_t::One();
+    double likelihood = 0;
     double denom = 0.0;
     int lc = 0;
     bool flag = false;
@@ -43,10 +44,10 @@ int main(int argc, char** argv) {
       assert(src.size() > 0);
       assert(trg.size() > 0);
       denom += 1.0;
-      vector<prob_t> probs(src.size() + 1);
+      vector<double> probs(src.size() + 1);
       for (int j = 0; j < trg.size(); ++j) {
         const WordID& f_j = trg[j][0].label;
-        prob_t sum = prob_t::Zero();
+        double sum = 0;
         if (use_null) {
           probs[0] = tt.prob(kNULL, f_j);
           sum += probs[0];
@@ -57,7 +58,7 @@ int main(int argc, char** argv) {
         }
         if (final_iteration) {
           WordID max_i = 0;
-          prob_t max_p = prob_t::Zero();
+          double max_p = -1;
           if (use_null) {
             max_i = kNULL;
             max_p = probs[0];
@@ -75,23 +76,23 @@ int main(int argc, char** argv) {
           for (int i = 1; i <= src.size(); ++i)
             tt.Increment(src[i-1][0].label, f_j, probs[i] / sum);
         }
-        likelihood *= sum;
+        likelihood += log(sum);
       }
     }
     if (flag) { cerr << endl; }
-    cerr << "  log likelihood: " << log(likelihood) << endl;
-    cerr << "    cross entopy: " << (-log(likelihood) / denom) << endl;
-    cerr << "      perplexity: " << pow(2.0, -log(likelihood) / denom) << endl;
+    cerr << "  log likelihood: " << likelihood << endl;
+    cerr << "    cross entopy: " << (-likelihood / denom) << endl;
+    cerr << "      perplexity: " << pow(2.0, -likelihood / denom) << endl;
     if (!final_iteration) tt.Normalize();
   }
   for (TTable::Word2Word2Double::iterator ei = tt.ttable.begin(); ei != tt.ttable.end(); ++ei) {
     const TTable::Word2Double& cpd = ei->second;
     const TTable::Word2Double& vit = was_viterbi[ei->first];
     const string& esym = TD::Convert(ei->first);
-    prob_t max_p = prob_t::Zero();
+    double max_p = -1;
     for (TTable::Word2Double::const_iterator fi = cpd.begin(); fi != cpd.end(); ++fi)
-      if (fi->second > max_p) max_p = prob_t(fi->second);
-    const prob_t threshold = max_p * BEAM_THRESHOLD;
+      if (fi->second > max_p) max_p = fi->second;
+    const double threshold = max_p * BEAM_THRESHOLD;
     for (TTable::Word2Double::const_iterator fi = cpd.begin(); fi != cpd.end(); ++fi) {
       if (fi->second > threshold || (vit.count(fi->first) > 0)) {
         cout << esym << ' ' << TD::Convert(fi->first) << ' ' << log(fi->second) << endl;