ParallelDecoder.java
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package decoder;
import java.util.ArrayList;
import java.util.concurrent.Callable;
import is2.data.Closed;
import is2.data.DataF;
import is2.data.Edges;
import is2.data.Open;
/**
* @author Bernd Bohnet, 30.08.2009
*
* This class implements a parallel feature extractor.
*/
final public class ParallelDecoder implements Callable<Object> {
// some constants
private static final float INIT_BEST = (-1.0F / 0.0F);
private static final boolean[] DIR = { false, true };
// the data space of the weights for a dependency tree
final private DataF x;
private short[] pos;
private Open O[][][][];
private Closed C[][][][];
private int n;
boolean done = false;
public boolean waiting = false;
/**
* Initialize the parallel decoder.
*
* @param pos
* part-of-speech
* @param d
* data
* @param edges
* part-of-speech edge mapping
* @param o
* open spans
* @param c
* closed spans
* @param n
* number of words
*/
public ParallelDecoder(short[] pos, DataF d, Open o[][][][], Closed c[][][][], int n) {
this.pos = pos;
this.x = d;
this.O = o;
this.C = c;
this.n = n;
}
private static class DSet {
short w1, w2;
}
@Override
public Object call() {
while (true) {
DSet set = get();
if (done && set == null)
break;
if (set == null)
return null;
short s = set.w1, t = set.w2;
for (short dir = 1; dir >= 0; dir--) {
short[] labs = (dir == 1) ? Edges.get(pos[s], pos[t], false) : Edges.get(pos[t], pos[s], true);
O[s][t][dir] = new Open[labs.length];
for (int l = O[s][t][dir].length - 1; l >= 0; l--) {
double tRP = INIT_BEST;
Closed tL = null, tR = null;
for (int r = s; r < t; r++) {
if (s == 0 && r != 0)
continue;
double tLPr = INIT_BEST, tRPr = INIT_BEST;
Closed tLCld = null, tRCld = null;
if (r == s)
tLPr = dir == 1 ? x.sib[s][t][s][0][l] : x.gra[t][s][s][1][l];
else
for (int i = s + 1; i <= r; i++)
if (((dir == 1 ? x.sib[s][t][i][0][l] : x.gra[t][s][i][1][l])
+ C[s][r][1][i].p) > tLPr) {
tLPr = ((dir == 1 ? x.sib[s][t][i][0][l] : x.gra[t][s][i][1][l]) + C[s][r][1][i].p);
tLCld = C[s][r][1][i];
}
if (r == t - 1)
tRPr = dir == 1 ? x.gra[s][t][s][0][l] : x.sib[t][s][s][1][l];
else
for (int i = r + 1; i < t; i++)
if (((dir == 1 ? x.gra[s][t][i][0][l] : x.sib[t][s][i][1][l])
+ C[r + 1][t][0][i].p) > tRPr) {
tRPr = ((dir == 1 ? x.gra[s][t][i][0][l] : x.sib[t][s][i][1][l])
+ C[r + 1][t][0][i].p);
tRCld = C[r + 1][t][0][i];
}
if (tLPr + tRPr > tRP) {
tRP = tLPr + tRPr;
tL = tLCld;
tR = tRCld;
}
}
O[s][t][dir][l] = new Open(s, t, dir, labs[l], tL, tR,
(float) (tRP + ((dir == 1) ? x.pl[s][t] : x.pl[t][s])
+ ((dir == 1) ? x.lab[s][t][labs[l]][0] : x.lab[t][s][labs[l]][1])));
}
}
C[s][t][1] = new Closed[n];
C[s][t][0] = new Closed[n];
for (int m = s; m <= t; m++) {
for (boolean d : DIR) {
if ((d && m != s) || !d && (m != t && s != 0)) {
// create closed structure
double top = INIT_BEST;
Open tU = null;
Closed tL = null;
int numLabels = O[(d ? s : m)][(d ? m : t)][d ? 1 : 0].length;
// for (int l = numLabels-1; l >=0; l--) {
for (int l = 0; l < numLabels; l++) {
Open hi = O[(d ? s : m)][(d ? m : t)][d ? 1 : 0][l];
for (int amb = m + (d ? 1 : -1); amb != (d ? t : s) + (d ? 1 : -1); amb += (d ? 1 : -1)) {
if ((hi.p + C[d ? m : s][d ? t : m][d ? 1 : 0][amb].p
+ x.gra[d ? s : t][m][amb][d ? 0 : 1][l]) > top) {
top = (hi.p + C[d ? m : s][d ? t : m][d ? 1 : 0][amb].p
+ x.gra[d ? s : t][m][amb][(d ? 0 : 1)][l]);
tU = hi;
tL = C[d ? m : s][d ? t : m][d ? 1 : 0][amb];
}
}
if ((m == (d ? t : s)) && (hi.p + x.gra[d ? s : t][m][d ? s : t][(d ? 0 : 1)][l]) > top) {
top = (hi.p + x.gra[(d ? s : t)][m][d ? s : t][d ? 0 : 1][l]);
tU = hi;
tL = null;
}
}
C[s][t][d ? 1 : 0][m] = new Closed(s, t, m, d ? 1 : 0, tU, tL, (float) top);
}
}
}
}
return null;
}
public static ArrayList<DSet> sets = new ArrayList<DSet>();
static synchronized private DSet get() {
synchronized (sets) {
if (sets.size() == 0)
return null;
return sets.remove(sets.size() - 1);
}
}
public static void add(short w1, short w2) {
DSet ds = new DSet();
ds.w1 = w1;
ds.w2 = w2;
sets.add(ds);
}
}