Option to run on single word phrases before moving to larger ones.

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@272 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 55 insertions, 12 deletions

diff --git a/gi/posterior-regularisation/prjava/src/phrase/PhraseCluster.java b/gi/posterior-regularisation/prjava/src/phrase/PhraseCluster.java
index a369b319..5efaf52e 100644
--- a/gi/posterior-regularisation/prjava/src/phrase/PhraseCluster.java
+++ b/gi/posterior-regularisation/prjava/src/phrase/PhraseCluster.java
@@ -69,16 +69,29 @@ public class PhraseCluster {
 		pool = Executors.newFixedThreadPool(threads);

 	}

 

-	public double EM()

+	public double EM(boolean skipBigPhrases)

 	{

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

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

 		

+		if (skipBigPhrases)

+		{

+			for(double [][]i:exp_emit)

+				for(double []j:i)

+					Arrays.fill(j, 1e-100);

+		}

+		

 		double loglikelihood=0;

 		

 		//E

 		for(int phrase=0; phrase < n_phrases; phrase++)

 		{

+			if (skipBigPhrases && c.getPhrase(phrase).size() >= 2)

+			{

+				System.arraycopy(pi[phrase], 0, exp_pi[phrase], 0, K);

+				continue;

+			}			

+

 			List<Edge> contexts = c.getEdgesForPhrase(phrase);

 

 			for (int ctx=0; ctx<contexts.size(); ctx++)

@@ -116,9 +129,10 @@ public class PhraseCluster {
 		return loglikelihood;

 	}

 	

-	public double VBEM(double alphaEmit, double alphaPi)

+	public double VBEM(double alphaEmit, double alphaPi, boolean skipBigPhrases)

 	{

 		// FIXME: broken - needs to be done entirely in log-space

+		assert !skipBigPhrases : "FIXME: implement this!";

 		

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

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

@@ -217,24 +231,31 @@ public class PhraseCluster {
 		return kl;

 	}

 	

-	public double PREM(double scalePT, double scaleCT)

+	public double PREM(double scalePT, double scaleCT, boolean skipBigPhrases)

 	{

 		if (scaleCT == 0)

 		{

 			if (pool != null)

-				return PREM_phrase_constraints_parallel(scalePT);

+				return PREM_phrase_constraints_parallel(scalePT, skipBigPhrases);

 			else

-				return PREM_phrase_constraints(scalePT);

+				return PREM_phrase_constraints(scalePT, skipBigPhrases);

 		}

 		else

-			return this.PREM_phrase_context_constraints(scalePT, scaleCT);

+			return this.PREM_phrase_context_constraints(scalePT, scaleCT, skipBigPhrases);

 	}

 

 	

-	public double PREM_phrase_constraints(double scalePT)

+	public double PREM_phrase_constraints(double scalePT, boolean skipBigPhrases)

 	{

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

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

+		

+		if (skipBigPhrases)

+		{

+			for(double [][]i:exp_emit)

+				for(double []j:i)

+					Arrays.fill(j, 1e-100);

+		}

 

 		if (lambdaPT == null && cacheLambda)

 			lambdaPT = new double[n_phrases][];

@@ -244,6 +265,12 @@ public class PhraseCluster {
 		long start = System.currentTimeMillis();

 		//E

 		for(int phrase=0; phrase<n_phrases; phrase++){

+			if (skipBigPhrases && c.getPhrase(phrase).size() >= 2)

+			{

+				System.arraycopy(pi[phrase], 0, exp_pi[phrase], 0, K);

+				continue;

+			}

+			

 			PhraseObjective po = new PhraseObjective(this, phrase, scalePT, (cacheLambda) ? lambdaPT[phrase] : null);

 			boolean ok = po.optimizeWithProjectedGradientDescent();

 			if (!ok) ++failures;

@@ -292,7 +319,7 @@ public class PhraseCluster {
 		return primal;

 	}

 

-	public double PREM_phrase_constraints_parallel(final double scalePT)

+	public double PREM_phrase_constraints_parallel(final double scalePT, boolean skipBigPhrases)

 	{

 		assert(pool != null);

 		

@@ -302,10 +329,17 @@ public class PhraseCluster {
 		double [][][]exp_emit=new double [K][n_positions][n_words];

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

 		

+		if (skipBigPhrases)

+		{

+			for(double [][]i:exp_emit)

+				for(double []j:i)

+					Arrays.fill(j, 1e-100);

+		}

+		

 		double loglikelihood=0, kl=0, l1lmax=0, primal=0;

 		final AtomicInteger failures = new AtomicInteger(0);

 		final AtomicLong elapsed = new AtomicLong(0l);

-		int iterations=0;

+		int iterations=0, n=n_phrases;

 		long start = System.currentTimeMillis();

 		

 		if (lambdaPT == null && cacheLambda)

@@ -313,6 +347,12 @@ public class PhraseCluster {
 

 		//E

 		for(int phrase=0;phrase<n_phrases;phrase++){

+			if (skipBigPhrases && c.getPhrase(phrase).size() >= 2)

+			{

+				n -= 1;

+				System.arraycopy(pi[phrase], 0, exp_pi[phrase], 0, K);

+				continue;

+			}

 			final int p=phrase;

 			pool.execute(new Runnable() {

 				public void run() {

@@ -337,7 +377,7 @@ public class PhraseCluster {
 		}

 		

 		// aggregate the expectations as they become available

-		for(int count=0;count<n_phrases;count++) {

+		for(int count=0;count<n;count++) {

 			try {

 				//System.out.println("" + Thread.currentThread().getId() + " reading queue #" + count);

 

@@ -396,8 +436,10 @@ public class PhraseCluster {
 		return primal;

 	}

 	

-	public double PREM_phrase_context_constraints(double scalePT, double scaleCT)

+	public double PREM_phrase_context_constraints(double scalePT, double scaleCT, boolean skipBigPhrases)

 	{	

+		assert !skipBigPhrases : "Not supported yet - FIXME!"; //FIXME

+		

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

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

 

@@ -454,7 +496,8 @@ public class PhraseCluster {
 		TIntArrayList ctx = edge.getContext();

 		for(int tag=0;tag<K;tag++)

 			for(int c=0;c<n_positions;c++)

-				prob[tag]*=emit[tag][c][ctx.get(c)];

+				if (!this.c.isSentinel(ctx.get(c)))

+					prob[tag]*=emit[tag][c][ctx.get(c)];

 		

 		return prob;

 	}