crp with explicit table tracking

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

1 files changed, 53 insertions, 34 deletions

diff --git a/gi/clda/src/clda.cc b/gi/clda/src/clda.cc
index 757a4691..ea224a27 100644
--- a/gi/clda/src/clda.cc
+++ b/gi/clda/src/clda.cc
@@ -1,9 +1,11 @@
 #include <iostream>
 #include <vector>
 #include <map>
+#include <string>
 
 #include "timer.h"
 #include "crp.h"
+#include "ccrp.h"
 #include "sampler.h"
 #include "tdict.h"
 const size_t MAX_DOC_LEN_CHARS = 10000000;
@@ -18,12 +20,44 @@ void ShowTopWordsForTopic(const map<WordID, int>& counts) {
   for (multimap<int, WordID>::reverse_iterator it = ms.rbegin(); it != ms.rend(); ++it) {
     cerr << it->first << ':' << TD::Convert(it->second) << " ";
     ++cc;
-    if (cc==12) break;
+    if (cc==20) break;
   }
   cerr << endl;
 }
 
+void tc() {
+  MT19937 rng;
+  CCRP<string> crp(0.1, 5);
+  double un = 0.25;
+  int tt = 0;
+  tt += crp.increment("hi", un, &rng);
+  tt += crp.increment("foo", un, &rng);
+  tt += crp.increment("bar", un, &rng);
+  tt += crp.increment("bar", un, &rng);
+  tt += crp.increment("bar", un, &rng);
+  tt += crp.increment("bar", un, &rng);
+  tt += crp.increment("bar", un, &rng);
+  tt += crp.increment("bar", un, &rng);
+  tt += crp.increment("bar", un, &rng);
+  cout << "tt=" << tt << endl;
+  cout << crp << endl;
+  cout << "  P(bar)=" << crp.prob("bar", un) << endl;
+  cout << "  P(hi)=" << crp.prob("hi", un) << endl;
+  cout << "  P(baz)=" << crp.prob("baz", un) << endl;
+  cout << "  P(foo)=" << crp.prob("foo", un) << endl;
+  double x = crp.prob("bar", un) + crp.prob("hi", un) + crp.prob("baz", un) + crp.prob("foo", un);
+  cout << "    tot=" << x << endl;
+  tt += crp.decrement("hi", &rng);
+  tt += crp.decrement("bar", &rng);
+  cout << crp << endl;
+  tt += crp.decrement("bar", &rng);
+  cout << crp << endl;
+  cout << "tt=" << tt << endl;
+  cout << crp.llh() << endl;
+}
+
 int main(int argc, char** argv) {
+  tc();
   if (argc != 3) {
     cerr << "Usage: " << argv[0] << " num-classes num-samples\n";
     return 1;
@@ -54,10 +88,13 @@ int main(int argc, char** argv) {
   MT19937 rng;
   cerr << "INITIALIZING RANDOM TOPIC ASSIGNMENTS\n";
   zji.resize(wji.size());
-  double beta = 0.1;
-  double alpha = 50.0 / num_classes;
-  vector<CRP<int> > dr(zji.size(), CRP<int>(beta)); // dr[i] describes the probability of using a topic in document i
-  vector<CRP<int> > wr(num_classes, CRP<int>(alpha)); // wr[k] describes the probability of generating a word in topic k
+  double disc = 0.05;
+  double beta = 10.0;
+  double alpha = 50.0;
+  double uniform_topic = 1.0 / num_classes;
+  double uniform_word = 1.0 / TD::NumWords();
+  vector<CCRP<int> > dr(zji.size(), CCRP<int>(disc, beta)); // dr[i] describes the probability of using a topic in document i
+  vector<CCRP<int> > wr(num_classes, CCRP<int>(disc, alpha)); // wr[k] describes the probability of generating a word in topic k
   for (int j = 0; j < zji.size(); ++j) {
     const size_t num_words = wji[j].size();
     vector<int>& zj = zji[j];
@@ -68,19 +105,15 @@ int main(int argc, char** argv) {
       if (random_topic == num_classes) { --random_topic; }
       zj[i] = random_topic;
       const int word = wj[i];
-      dr[j].increment(random_topic);
-      wr[random_topic].increment(word);
+      dr[j].increment(random_topic, uniform_topic, &rng);
+      wr[random_topic].increment(word, uniform_word, &rng);
     }
   }
   cerr << "SAMPLING\n";
   vector<map<WordID, int> > t2w(num_classes);
   Timer timer;
-  SampleSet ss;
+  SampleSet<double> ss;
   const int num_types = TD::NumWords();
-  const prob_t class_p0(1.0 / num_classes);
-  const prob_t word_p0(1.0 / num_types);
-  cerr << "CLASS PRIOR    PROB: " << class_p0 << endl;
-  cerr << " WORD PRIOR LOGPROB: " << log(word_p0) << endl;
   ss.resize(num_classes);
   double total_time = 0;
   for (int iter = 0; iter < num_iterations; ++iter) {
@@ -88,23 +121,6 @@ int main(int argc, char** argv) {
     if (iter && iter % 10 == 0) {
       total_time += timer.Elapsed();
       timer.Reset();
-      prob_t lh = prob_t::One();
-      for (int j = 0; j < zji.size(); ++j) {
-        const size_t num_words = wji[j].size();
-        vector<int>& zj = zji[j];
-        const vector<int>& wj = wji[j];
-        for (int i = 0; i < num_words; ++i) {
-          const int word = wj[i];
-          const int cur_topic = zj[i];
-          lh *= dr[j].prob(cur_topic, class_p0);
-          lh *= wr[cur_topic].prob(word, word_p0);
-          if (iter > burnin_size) {
-            ++t2w[cur_topic][word];
-          }
-        }
-      }
-      if (iter && iter % 40 == 0) { cerr << " [ITER=" << iter << " SEC/SAMPLE=" << (total_time / 40) << " LLH=" << log(lh) << "]\n"; total_time=0; }
-      //cerr << "ITERATION " << iter << " LOG LIKELIHOOD: " << log(lh) << endl;
     }
     for (int j = 0; j < zji.size(); ++j) {
       const size_t num_words = wji[j].size();
@@ -113,16 +129,19 @@ int main(int argc, char** argv) {
       for (int i = 0; i < num_words; ++i) {
         const int word = wj[i];
         const int cur_topic = zj[i];
-        dr[j].decrement(cur_topic);
-        wr[cur_topic].decrement(word);
+        dr[j].decrement(cur_topic, &rng);
+        wr[cur_topic].decrement(word, &rng);
  
         for (int k = 0; k < num_classes; ++k) {
-          ss[k]= dr[j].prob(k, class_p0) * wr[k].prob(word, word_p0);
+          ss[k]= dr[j].prob(k, uniform_topic) * wr[k].prob(word, uniform_word);
         }
         const int new_topic = rng.SelectSample(ss);
-        dr[j].increment(new_topic);
-        wr[new_topic].increment(word);
+        dr[j].increment(new_topic, uniform_topic, &rng);
+        wr[new_topic].increment(word, uniform_word, &rng);
         zj[i] = new_topic;
+        if (iter > burnin_size) {
+          ++t2w[cur_topic][word];
+        }
       }
     }
   }