Added initial VB implementation for symetric Dirichlet prior.

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@215 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 13 insertions, 2 deletions

diff --git a/gi/posterior-regularisation/prjava/src/phrase/Trainer.java b/gi/posterior-regularisation/prjava/src/phrase/Trainer.java
index b19f3fb9..439fb337 100644
--- a/gi/posterior-regularisation/prjava/src/phrase/Trainer.java
+++ b/gi/posterior-regularisation/prjava/src/phrase/Trainer.java
@@ -27,6 +27,9 @@ public class Trainer
         parser.accepts("scale-context").withRequiredArg().ofType(Double.class).defaultsTo(0.0);
         parser.accepts("seed").withRequiredArg().ofType(Long.class).defaultsTo(0l);
         parser.accepts("convergence-threshold").withRequiredArg().ofType(Double.class).defaultsTo(1e-6);
+        parser.accepts("variational-bayes");
+        parser.accepts("alpha-emit").withRequiredArg().ofType(Double.class).defaultsTo(0.1);
+        parser.accepts("alpha-pi").withRequiredArg().ofType(Double.class).defaultsTo(0.01);
         OptionSet options = parser.parse(args);
 
         if (options.has("help") || !options.has("in"))
@@ -47,6 +50,9 @@ public class Trainer
 		double scale_context = (Double) options.valueOf("scale-context");
 		int threads = (Integer) options.valueOf("threads");
 		double threshold = (Double) options.valueOf("convergence-threshold");
+		boolean vb = options.has("variational-bayes");
+		double alphaEmit = (vb) ? (Double) options.valueOf("alpha-emit") : 0;
+		double alphaPi = (vb) ? (Double) options.valueOf("alpha-pi") : 0;
 		
 		if (options.has("seed"))
 			F.rng = new Random((Long) options.valueOf("seed"));
@@ -75,14 +81,19 @@ public class Trainer
  				"and " + threads + " threads");
  		System.out.println();
 		
-		PhraseCluster cluster = new PhraseCluster(tags, corpus, scale_phrase, scale_context, threads);
+		PhraseCluster cluster = new PhraseCluster(tags, corpus, scale_phrase, scale_context, threads, alphaEmit, alphaPi);
 				
 		double last = 0;
 		for (int i=0; i<em_iterations+pr_iterations; i++)
 		{
 			double o;
 			if (i < em_iterations) 
-				o = cluster.EM();
+			{
+				if (!vb)
+					o = cluster.EM();
+				else
+					o = cluster.VBEM();
+			}
 			else if (scale_context == 0)
 			{
 				if (threads >= 1)