ParallelExtract.java
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package is2.parser;
import is2.data.Cluster;
import is2.data.DataFES;
import is2.data.F2SF;
import is2.data.FV;
import is2.data.Instances;
import is2.data.Long2IntInterface;
import is2.util.DB;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.concurrent.Callable;
/**
* @author Bernd Bohnet, 30.08.2009
*
* This class implements a parallel feature extractor.
*/
final public class ParallelExtract implements Callable<Object>
{
// the data space of the weights for a dependency tree
final DataFES d;
// the data extractor does the actual work
final Extractor extractor;
private Instances is;
private int i;
private F2SF para;
private Cluster cluster;
public ParallelExtract(Extractor e, Instances is, int i, DataFES d, F2SF para,Cluster cluster) {
this.is =is;
extractor=e;
this.d =d;
this.i=i;
this.para=para;
this.cluster = cluster;
}
public static class DSet {
int w1,w2;
}
public Object call() {
try {
F2SF f= para;
short[] pos=is.pposs[i];
int length = pos.length;
long[] gvs = new long[50];
long[] svs = new long[220];
while (true) {
DSet set = get();
if (set ==null) break;
int w1=set.w1;
int w2=set.w2;
f.clear();
extractor.basic(pos, w1, w2, f);
d.pl[w1][w2]=f.getScoreF();
f.clear();
extractor.basic(pos, w2, w1, f);
d.pl[w2][w1]=f.getScoreF();
short[] labels = Edges.get(pos[w1], pos[w2]);
float[] lab = d.lab[w1][w2];
final Long2IntInterface li = extractor.li;
int c = extractor.firstm(is, i, w1, w2, 0, cluster, svs);
for (int l = 0; l <lab.length ; l++) lab[l]=-100 ;
for (int l = 0; l <labels.length ; l++) {
short label = labels[l];
f.clear();
int lv = extractor.d0.computeLabeValue(label,Extractor.s_type);
for(int k=0;k<c;k++)if (svs[k]>0) f.add(li.l2i(svs[k]+lv));
lab[label]=f.getScoreF();
}
labels = Edges.get(pos[w2], pos[w1]);
lab = d.lab[w2][w1];
for (int l = 0; l <lab.length ; l++) lab[l]=-100 ;
for (int l = 0; l <labels.length ; l++) {
int label = labels[l];
f.clear();
int lv = extractor.d0.computeLabeValue(label + Extractor.s_rel1 ,Extractor.s_type);
for(int k=0;k<c;k++)if (svs[k]>0) f.add(li.l2i(svs[k]+lv));
lab[label]=f.getScoreF();
}
int s = w1<w2 ? w1 : w2;
int e = w1<w2 ? w2 : w1;
for(int m=0;m<length;m++) {
int g = (m==s||e==m) ? -1 : m;
int cn =extractor.second(is, i, w1,w2,g, 0, cluster, svs);
int cc = extractor.addClusterFeatures(is,i, w1, w2, g, cluster, 0, gvs,0);
//for(int k=0;k<c;k++) dl1.map(f,svs[k]);
if(m>=w1) {
labels = Edges.get(pos[w1], pos[w2]);
float[] lab2 = new float[labels.length];
for (int l = 0; l <labels.length ; l++) {
short label = labels[l];
int lx =label+Extractor.s_rel1*( g < w2?0:2 );
f.clear();
int lv = extractor.d0.computeLabeValue(lx,Extractor.s_type);
for(int k=0;k<cn;k++)if (svs[k]>0) f.add(li.l2i(svs[k]+lv));
for(int k=0;k<cc;k++)if (gvs[k]>0) f.add(li.l2i(gvs[k]+lv));
lab2[l] = f.getScoreF();
}
d.gra[w1][w2][m] =lab2;
}
if (m<=w2) {
labels = Edges.get(pos[w2], pos[w1]);
float lab2[];
d.gra[w2][w1][m] = lab2 = new float[labels.length];
for (int l = 0; l <labels.length ; l++) {
int label = labels[l] ;
int lx =label+Extractor.s_rel1*(1 + (g < w1?0:2) );
f.clear();
int lv = extractor.d0.computeLabeValue(lx,Extractor.s_type);
for(int k=0;k<cn;k++)if (svs[k]>0) f.add(li.l2i(svs[k]+lv));
for(int k=0;k<cc;k++)if (gvs[k]>0) f.add(li.l2i(gvs[k]+lv));
lab2[l] = f.getScoreF();
}
}
g = (m==s||e==m) ? -1 : m;
// int cn = extractor.second(is,i,w1,w2,g,0, cluster, svs,Extractor._SIB);
if (m >=w1 && m<=w2) {
labels = Edges.get(pos[w1], pos[w2]);
float lab2[]= new float[labels.length];
d.sib[w1][w2][m] = lab2;
for (int l = 0; l <labels.length ; l++) {
short label = labels[l];
int lx =label+Extractor.s_rel1*( 8);
f.clear();
int lv = extractor.d0.computeLabeValue(lx,Extractor.s_type);
for(int k=0;k<cn;k++) if (svs[k]>0) f.add(li.l2i(svs[k]+lv));
for(int k=0;k<cc;k++) if (gvs[k]>0) f.add(li.l2i(gvs[k]+lv));
lab2[l] = (float)f.score;//f.getScoreF();
}
}
if (m >=w1 && m <=w2) {
labels = Edges.get(pos[w2], pos[w1]);
float[] lab2 = new float[labels.length];
d.sib[w2][w1][m]=lab2;
for (int l = 0; l <labels.length ; l++) {
int label = labels[l] ;
int lx =label+Extractor.s_rel1*(9);
f.clear();
int lv = extractor.d0.computeLabeValue(lx,Extractor.s_type);
for(int k=0;k<cn;k++) if (svs[k]>0) f.add(li.l2i(svs[k]+lv));
for(int k=0;k<cc;k++) if (gvs[k]>0) f.add(li.l2i(gvs[k]+lv));
lab2[l] = f.score;//f.getScoreF();
}
}
}
}
} catch(Exception e ) {
e.printStackTrace();
}
return null;
}
static ArrayList<DSet> sets = new ArrayList<DSet>();
private DSet get() {
synchronized (sets) {
if (sets.size()==0) return null;
return sets.remove(sets.size()-1);
}
}
static public void add(int w1, int w2){
DSet ds =new DSet();
ds.w1=w1;
ds.w2=w2;
sets.add(ds);
}
}