From e26434979adc33bd949566ba7bf02dff64e80a3e Mon Sep 17 00:00:00 2001
From: Chris Dyer <cdyer@cab.ark.cs.cmu.edu>
Date: Tue, 2 Oct 2012 00:19:43 -0400
Subject: cdec cleanup, remove bayesian stuff, parsing stuff

---
 .../prjava/src/phrase/VB.java                      | 419 ---------------------
 1 file changed, 419 deletions(-)
 delete mode 100644 gi/posterior-regularisation/prjava/src/phrase/VB.java

(limited to 'gi/posterior-regularisation/prjava/src/phrase/VB.java')

diff --git a/gi/posterior-regularisation/prjava/src/phrase/VB.java b/gi/posterior-regularisation/prjava/src/phrase/VB.java
deleted file mode 100644
index cd3f4966..00000000
--- a/gi/posterior-regularisation/prjava/src/phrase/VB.java
+++ /dev/null
@@ -1,419 +0,0 @@
-package phrase;
-
-import gnu.trove.TIntArrayList;
-
-import io.FileUtil;
-
-import java.io.File;
-import java.io.IOException;
-import java.io.PrintStream;
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.List;
-import java.util.concurrent.Callable;
-import java.util.concurrent.ExecutionException;
-import java.util.concurrent.ExecutorService;
-import java.util.concurrent.Future;
-
-import org.apache.commons.math.special.Gamma;
-
-import phrase.Corpus.Edge;
-
-public class VB {
-
-	public static int MAX_ITER=400;
-	
-	/**@brief
-	 * hyper param for beta
-	 * where beta is multinomial
-	 * for generating words from a topic
-	 */
-	public double lambda=0.1;
-	/**@brief
-	 * hyper param for theta
-	 * where theta is dirichlet for z
-	 */
-	public double alpha=0.0001;
-	/**@brief
-	 * variational param for beta
-	 */
-	private double rho[][][];
-	private double digamma_rho[][][];
-	private double rho_sum[][];
-	/**@brief
-	 * variational param for z
-	 */
-	//private double phi[][];
-	/**@brief
-	 * variational param for theta
-	 */
-	private double gamma[];
-	private static double VAL_DIFF_RATIO=0.005;
-	
-	private int n_positions;
-	private int n_words;
-	private int K;
-	private ExecutorService pool;
-	
-	private Corpus c;
-	public static void main(String[] args) {
-	//	String in="../pdata/canned.con";
-		String in="../pdata/btec.con";
-		String out="../pdata/vb.out";
-		int numCluster=25;
-		Corpus corpus = null;
-		File infile = new File(in);
-		try {
-			System.out.println("Reading concordance from " + infile);
-			corpus = Corpus.readFromFile(FileUtil.reader(infile));
-			corpus.printStats(System.out);
-		} catch (IOException e) {
-			System.err.println("Failed to open input file: " + infile);
-			e.printStackTrace();
-			System.exit(1);
-		}
-		
-		VB vb=new VB(numCluster, corpus);
-		int iter=20;
-		for(int i=0;i<iter;i++){
-			double obj=vb.EM();
-			System.out.println("Iter "+i+": "+obj);
-		}
-		
-		File outfile = new File (out);
-		try {
-			PrintStream ps = FileUtil.printstream(outfile);
-			vb.displayPosterior(ps);
-		//	ps.println();
-		//	c2f.displayModelParam(ps);
-			ps.close();
-		} catch (IOException e) {
-			System.err.println("Failed to open output file: " + outfile);
-			e.printStackTrace();
-			System.exit(1);
-		}
-	}
-
-	public VB(int numCluster, Corpus corpus){
-		c=corpus;
-		K=numCluster;
-		n_positions=c.getNumContextPositions();
-		n_words=c.getNumWords();
-		rho=new double[K][n_positions][n_words];
-		//to init rho
-		//loop through data and count up words
-		double[] phi_tmp=new double[K];
-		for(int i=0;i<K;i++){
-			for(int pos=0;pos<n_positions;pos++){
-				Arrays.fill(rho[i][pos], lambda);
-			}
-		}
-		for(int d=0;d<c.getNumPhrases();d++){
-			List<Edge>doc=c.getEdgesForPhrase(d);
-			for(int n=0;n<doc.size();n++){
-				TIntArrayList context=doc.get(n).getContext();
-				arr.F.randomise(phi_tmp);
-				for(int i=0;i<K;i++){
-					for(int pos=0;pos<n_positions;pos++){
-						rho[i][pos][context.get(pos)]+=phi_tmp[i];
-					}
-				}
-			}
-		}
-		
-	}
-	
-	private double inference(int phraseID, double[][] phi, double[] gamma)
-	{
-		List<Edge > doc=c.getEdgesForPhrase(phraseID);
-		for(int i=0;i<phi.length;i++){
-			for(int j=0;j<phi[i].length;j++){
-				phi[i][j]=1.0/K;
-			}
-		}
-		Arrays.fill(gamma,alpha+1.0/K);
-		
-		double digamma_gamma[]=new double[K];
-		
-		double gamma_sum=digamma(arr.F.l1norm(gamma));
-		for(int i=0;i<K;i++){
-			digamma_gamma[i]=digamma(gamma[i]);
-		}
-		double gammaSum[]=new double [K];
-		double prev_val=0;
-		double obj=0;
-		
-		for(int iter=0;iter<MAX_ITER;iter++){
-			prev_val=obj;
-			obj=0;
-			Arrays.fill(gammaSum,0.0);
-			for(int n=0;n<doc.size();n++){
-				TIntArrayList context=doc.get(n).getContext();
-				double phisum=0;
-				for(int i=0;i<K;i++){
-					double sum=0;
-					for(int pos=0;pos<n_positions;pos++){
-						int word=context.get(pos);
-						sum+=digamma_rho[i][pos][word]-rho_sum[i][pos];
-					}
-					sum+= digamma_gamma[i]-gamma_sum;
-					phi[n][i]=sum;
-					
-					if (i > 0){
-	                    phisum = log_sum(phisum, phi[n][i]);
-					}
-	                else{
-	                    phisum = phi[n][i];
-	                }
-					
-				}//end of  a word
-				
-				for(int i=0;i<K;i++){
-					phi[n][i]=Math.exp(phi[n][i]-phisum);
-					gammaSum[i]+=phi[n][i];
-				}
-				
-			}//end of doc
-			
-			for(int i=0;i<K;i++){
-				gamma[i]=alpha+gammaSum[i];
-			}
-			gamma_sum=digamma(arr.F.l1norm(gamma));
-			for(int i=0;i<K;i++){
-				digamma_gamma[i]=digamma(gamma[i]);
-			}
-			//compute objective for reporting
-
-			obj=0;
-			
-			for(int i=0;i<K;i++){
-				obj+=(alpha-1)*(digamma_gamma[i]-gamma_sum);
-			}
-			
-			
-			for(int n=0;n<doc.size();n++){
-				TIntArrayList context=doc.get(n).getContext();
-				
-				for(int i=0;i<K;i++){
-					//entropy of phi + expected log likelihood of z
-					obj+=phi[n][i]*(digamma_gamma[i]-gamma_sum);
-					
-					if(phi[n][i]>1e-10){
-						obj+=phi[n][i]*Math.log(phi[n][i]);
-					}
-					
-					double beta_sum=0;
-					for(int pos=0;pos<n_positions;pos++){
-						int word=context.get(pos);
-						beta_sum+=(digamma(rho[i][pos][word])-rho_sum[i][pos]);
-					}
-					obj+=phi[n][i]*beta_sum;
-				}
-			}
-			
-			obj-=log_gamma(arr.F.l1norm(gamma));
-			for(int i=0;i<K;i++){
-				obj+=Gamma.logGamma(gamma[i]);
-				obj-=(gamma[i]-1)*(digamma_gamma[i]-gamma_sum);
-			}
-			
-//			System.out.println(phraseID+": "+obj);
-			if(iter>0 && (obj-prev_val)/Math.abs(obj)<VAL_DIFF_RATIO){
-				break;
-			}
-		}//end of inference loop
-		
-		return obj;
-	}//end of inference
-	
-	/**
-	 * @return objective of this iteration
-	 */
-	public double EM(){
-		double emObj=0;
-		if(digamma_rho==null){
-			digamma_rho=new double[K][n_positions][n_words];
-		}
-		for(int i=0;i<K;i++){
-			for (int pos=0;pos<n_positions;pos++){
-				for(int j=0;j<n_words;j++){
-					digamma_rho[i][pos][j]= digamma(rho[i][pos][j]);
-				}
-			}
-		}
-		
-		if(rho_sum==null){
-			rho_sum=new double [K][n_positions];
-		}
-		for(int i=0;i<K;i++){
-			for(int pos=0;pos<n_positions;pos++){
-				rho_sum[i][pos]=digamma(arr.F.l1norm(rho[i][pos]));
-			}
-		}
-
-		//E
-		double exp_rho[][][]=new double[K][n_positions][n_words];
-		if (pool == null)
-		{
-			for (int d=0;d<c.getNumPhrases();d++)
-			{		
-				List<Edge > doc=c.getEdgesForPhrase(d);
-				double[][] phi = new double[doc.size()][K];
-				double[] gamma = new double[K];
-				
-				emObj += inference(d, phi, gamma);
-				
-				for(int n=0;n<doc.size();n++){
-					TIntArrayList context=doc.get(n).getContext();
-					for(int pos=0;pos<n_positions;pos++){
-						int word=context.get(pos);
-						for(int i=0;i<K;i++){	
-							exp_rho[i][pos][word]+=phi[n][i];
-						}
-					}
-				}
-				//if(d!=0 && d%100==0)  System.out.print(".");
-				//if(d!=0 && d%1000==0) System.out.println(d);
-			}
-		}
-		else // multi-threaded version of above loop
-		{
-			class PartialEStep implements Callable<PartialEStep>
-			{
-				double[][] phi;
-				double[] gamma;
-				double obj;
-				int d;
-				PartialEStep(int d) { this.d = d; }
-
-				public PartialEStep call()
-				{
-					phi = new double[c.getEdgesForPhrase(d).size()][K];
-					gamma = new double[K];
-					obj = inference(d, phi, gamma);
-					return this;
-				}			
-			}
-
-			List<Future<PartialEStep>> jobs = new ArrayList<Future<PartialEStep>>();
-			for (int d=0;d<c.getNumPhrases();d++)
-				jobs.add(pool.submit(new PartialEStep(d)));
-		
-			for (Future<PartialEStep> job: jobs)
-			{
-				try {
-					PartialEStep e = job.get();
-					
-					emObj += e.obj;				
-					List<Edge> doc = c.getEdgesForPhrase(e.d);
-					for(int n=0;n<doc.size();n++){
-						TIntArrayList context=doc.get(n).getContext();
-						for(int pos=0;pos<n_positions;pos++){
-							int word=context.get(pos);
-							for(int i=0;i<K;i++){	
-								exp_rho[i][pos][word]+=e.phi[n][i];
-							}
-						}
-					}
-				} catch (ExecutionException e) {
-					System.err.println("ERROR: E-step thread execution failed.");
-					throw new RuntimeException(e);
-				} catch (InterruptedException e) {
-					System.err.println("ERROR: Failed to join E-step thread.");
-					throw new RuntimeException(e);
-				}
-			}
-		}	
-	//	System.out.println("EM Objective:"+emObj);
-		
-		//M
-		for(int i=0;i<K;i++){
-			for(int pos=0;pos<n_positions;pos++){
-				for(int j=0;j<n_words;j++){
-					rho[i][pos][j]=lambda+exp_rho[i][pos][j];
-				}
-			}
-		}
-		
-		//E[\log p(\beta|\lambda)] - E[\log q(\beta)]
-		for(int i=0;i<K;i++){
-			double rhoSum=0;
-			for(int pos=0;pos<n_positions;pos++){
-				for(int j=0;j<n_words;j++){
-					rhoSum+=rho[i][pos][j];
-				}
-				double digamma_rhoSum=Gamma.digamma(rhoSum);
-				emObj-=Gamma.logGamma(rhoSum);
-				for(int j=0;j<n_words;j++){
-					emObj+=(lambda-rho[i][pos][j])*(Gamma.digamma(rho[i][pos][j])-digamma_rhoSum);
-					emObj+=Gamma.logGamma(rho[i][pos][j]);
-				}
-			}
-		}
-		
-		return emObj;
-	}//end of EM
-	
-	public void displayPosterior(PrintStream ps)
-	{	
-		for(int d=0;d<c.getNumPhrases();d++){
-			List<Edge > doc=c.getEdgesForPhrase(d);
-			double[][] phi = new double[doc.size()][K];
-			for(int i=0;i<phi.length;i++)
-				for(int j=0;j<phi[i].length;j++)
-					phi[i][j]=1.0/K;
-			double[] gamma = new double[K];
-
-			inference(d, phi, gamma);
-
-			for(int n=0;n<doc.size();n++){
-				Edge edge=doc.get(n);
-				int tag=arr.F.argmax(phi[n]);
-				ps.print(edge.getPhraseString());
-				ps.print("\t");
-				ps.print(edge.getContextString(true));
-
-				ps.println(" ||| C=" + tag);
-			}
-		}
-	}
-
-	double log_sum(double log_a, double log_b)
-	{
-	  double v;
-
-	  if (log_a < log_b)
-	      v = log_b+Math.log(1 + Math.exp(log_a-log_b));
-	  else
-	      v = log_a+Math.log(1 + Math.exp(log_b-log_a));
-	  return(v);
-	}
-		
-	double digamma(double x)
-	{
-	    double p;
-	    x=x+6;
-	    p=1/(x*x);
-	    p=(((0.004166666666667*p-0.003968253986254)*p+
-		0.008333333333333)*p-0.083333333333333)*p;
-	    p=p+Math.log(x)-0.5/x-1/(x-1)-1/(x-2)-1/(x-3)-1/(x-4)-1/(x-5)-1/(x-6);
-	    return p;
-	}
-	
-	double log_gamma(double x)
-	{
-	     double z=1/(x*x);
-
-	    x=x+6;
-	    z=(((-0.000595238095238*z+0.000793650793651)
-		*z-0.002777777777778)*z+0.083333333333333)/x;
-	    z=(x-0.5)*Math.log(x)-x+0.918938533204673+z-Math.log(x-1)-
-	    Math.log(x-2)-Math.log(x-3)-Math.log(x-4)-Math.log(x-5)-Math.log(x-6);
-	    return z;
-	}
-
-	public void useThreadPool(ExecutorService threadPool) 
-	{
-		pool = threadPool;
-	}
-}//End of  class
-- 
cgit v1.2.3