ParallelExtract.java
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package is2.parser;
import java.util.ArrayList;
import java.util.concurrent.Callable;
import is2.data.Cluster;
import is2.data.DataFES;
import is2.data.F2SF;
import is2.data.Instances;
import is2.data.Long2IntInterface;
/**
* @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;
}
@Override
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 (short label2 : labels) {
short label = label2;
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 (short label2 : labels) {
int label = label2;
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] = 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);
}
}