1 files changed, 10 insertions, 14 deletions

diff --git a/gi/posterior-regularisation/prjava/src/phrase/PhraseCluster.java b/gi/posterior-regularisation/prjava/src/phrase/PhraseCluster.java
index e4db2a1a..63a60682 100644
--- a/gi/posterior-regularisation/prjava/src/phrase/PhraseCluster.java
+++ b/gi/posterior-regularisation/prjava/src/phrase/PhraseCluster.java
@@ -18,7 +18,7 @@ public class PhraseCluster {
 	public double scalePT, scaleCT;

 	private int n_phrases, n_words, n_contexts, n_positions;

 	public Corpus c;

-	private ExecutorService pool; 

+	public ExecutorService pool; 

 	

 	// emit[tag][position][word] = p(word | tag, position in context)

 	private double emit[][][];

@@ -88,7 +88,8 @@ public class PhraseCluster {
 		//cluster.displayModelParam(ps);

 		//ps.close();

 		

-		cluster.finish();

+		if (cluster.pool != null)

+			cluster.pool.shutdown();

 	}

 

 	public PhraseCluster(int numCluster, Corpus corpus, double scalep, double scalec, int threads){

@@ -100,7 +101,7 @@ public class PhraseCluster {
 		n_positions=c.getNumContextPositions();

 		this.scalePT = scalep;

 		this.scaleCT = scalec;

-		if (threads > 0 && scalec <= 0)

+		if (threads > 0)

 			pool = Executors.newFixedThreadPool(threads);

 		

 		emit=new double [K][n_positions][n_words];

@@ -116,12 +117,7 @@ public class PhraseCluster {
 			arr.F.randomise(j);

 		}

 	}

-	

-	public void finish()

-	{

-		if (pool != null)

-			pool.shutdown();

-	}

+

 		

 	public double EM(){

 		double [][][]exp_emit=new double [K][n_positions][n_words];

@@ -318,13 +314,13 @@ public class PhraseCluster {
 	public double PREM_phrase_context_constraints(){

 		assert (scaleCT > 0);

 		

-		double [][][]exp_emit=new double [K][n_positions][n_words];

-		double [][]exp_pi=new double[n_phrases][K];

+		double[][][] exp_emit = new double [K][n_positions][n_words];

+		double[][] exp_pi = new double[n_phrases][K];

+		double[] lambda = null;

 

 		//E step

-		// TODO: cache the lambda values (the null below)

-		PhraseContextObjective pco = new PhraseContextObjective(this, null);

-		pco.optimizeWithProjectedGradientDescent();

+		PhraseContextObjective pco = new PhraseContextObjective(this, lambda, pool);

+		lambda = pco.optimizeWithProjectedGradientDescent();

 

 		//now extract expectations

 		List<Corpus.Edge> edges = c.getEdges();