Prettyfied output regarding optimization failure.

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@210 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 11 insertions, 7 deletions

diff --git a/gi/posterior-regularisation/prjava/src/phrase/PhraseObjective.java b/gi/posterior-regularisation/prjava/src/phrase/PhraseObjective.java
index 3314f74a..f24b903d 100644
--- a/gi/posterior-regularisation/prjava/src/phrase/PhraseObjective.java
+++ b/gi/posterior-regularisation/prjava/src/phrase/PhraseObjective.java
@@ -22,7 +22,7 @@ public class PhraseObjective extends ProjectedObjective
 {

 	static final double GRAD_DIFF = 0.00002;

 	static double INIT_STEP_SIZE = 300;

-	static double VAL_DIFF = 1e-4; // FIXME needs to be tuned - and this might be too weak

+	static double VAL_DIFF = 1e-6; // FIXME needs to be tuned - and this might be too weak

 	static int ITERATIONS = 100;

 	//private double c1=0.0001; // wolf stuff

 	//private double c2=0.9;

@@ -164,7 +164,9 @@ public class PhraseObjective extends ProjectedObjective
 		return q;

 	}

 	

-	public void optimizeWithProjectedGradientDescent(){

+	public int iterations = 0;

+	

+	public boolean optimizeWithProjectedGradientDescent(){

 		LineSearchMethod ls =

 			new ArmijoLineSearchMinimizationAlongProjectionArc

 				(new InterpolationPickFirstStep(INIT_STEP_SIZE));

@@ -181,13 +183,14 @@ public class PhraseObjective extends ProjectedObjective
 		compositeStop.add(stopValue);

 		optimizer.setMaxIterations(ITERATIONS);

 		updateFunction();

-		boolean succed = optimizer.optimize(this,stats,compositeStop);

+		boolean success = optimizer.optimize(this,stats,compositeStop);

+		iterations += optimizer.getCurrentIteration();

 //		System.out.println("Ended optimzation Projected Gradient Descent\n" + stats.prettyPrint(1));

-		if(succed){

+		//if(succed){

 			//System.out.println("Ended optimization in " + optimizer.getCurrentIteration());

-		}else{

-			System.out.println("Failed to optimize");

-		}

+		//}else{

+//			System.out.println("Failed to optimize");

+		//}

 		lambda[phrase]=parameters;

 		//	ps.println(Arrays.toString(parameters));

 		

@@ -195,6 +198,7 @@ public class PhraseObjective extends ProjectedObjective
 		//	ps.println(Arrays.toString(q[edge]));

 		//	}

 		

+		return success;

 	}

 	

 	public double KL_divergence()