reimplementation of computeSoftMax

Author: Lukas Molzberger

src/main/java/network/aika/Document.java

@@ -27,6 +27,7 @@
 import network.aika.neuron.activation.Activation.OscillatingActivationsException;
 import network.aika.neuron.activation.Position;
 import network.aika.neuron.activation.link.Linker;
+import network.aika.neuron.activation.search.Option;
 import network.aika.neuron.activation.search.SearchNode;
 import network.aika.neuron.activation.search.SearchNode.TimeoutException;
 import network.aika.neuron.activation.*;
@@ -38,6 +39,7 @@
 
 import static network.aika.neuron.INeuron.Type.*;
 import static network.aika.neuron.activation.Activation.CANDIDATE_COMP;
+import static network.aika.neuron.activation.search.Decision.SELECTED;
 import static network.aika.neuron.activation.search.Decision.UNKNOWN;
 
 
@@ -445,24 +447,9 @@ public void storeFinalState() {
 
 
     private void computeSoftMax() {
-/*        for (Activation act : activationsById.values()) {
-            double offset = Double.MAX_VALUE;
-            for (Option option : act.getOptions()) {
-                offset = Math.min(offset, Math.log(option.cacheFactor) + option.weight);
-            }
-
-            double norm = 0.0;
-            for (Option option : act.getOptions()) {
-                norm += Math.exp(Math.log(option.cacheFactor) + option.weight - offset);
-            }
-
-            for (Option option : act.getOptions()) {
-                if (option.decision == SELECTED) {
-                    option.p = Math.exp(Math.log(option.cacheFactor) + option.weight - offset) / norm;
-                }
-            }
+        for (Activation act : activationsById.values()) {
+            act.computeSoftMax();
         }
-        */
     }
 
 

src/main/java/network/aika/neuron/activation/Activation.java

@@ -777,6 +777,23 @@ public boolean match(Predicate<Link> filter) {
     }
 
 
+    public void computeSoftMax() {
+        rootOption.traverse((o) -> o.computeRemainingWeight());
+
+        final double[] offset = new double[] {Double.MAX_VALUE};
+        rootOption.traverse(o -> offset[0] = Math.min(offset[0], Math.log(o.cacheFactor) + o.remainingWeight));
+
+        final double[] norm = new double[] {0.0};
+        rootOption.traverse(o -> norm[0] += Math.log(o.cacheFactor) + o.remainingWeight - offset[0]);
+
+        rootOption.traverse(o -> {
+            if (o.decision == SELECTED) {
+                o.p = Math.exp(Math.log(o.cacheFactor) + o.remainingWeight - offset[0]) / norm[0];
+            }
+        });
+    }
+
+
     public String toString() {
         return id + " " + getNeuron().getId() + ":" + getINeuron().typeToString() + " " + getLabel() + " " + slotsToString() + " " + identityToString() + " - " +
                 " UB:" + Utils.round(upperBound) +

src/main/java/network/aika/neuron/activation/search/Option.java

@@ -22,6 +22,10 @@
 import network.aika.neuron.activation.State;
 
 import java.util.*;
+import java.util.concurrent.Callable;
+import java.util.function.BiFunction;
+import java.util.function.Consumer;
+import java.util.function.Predicate;
 import java.util.stream.Collectors;
 
 import static network.aika.Document.MAX_ROUND;
@@ -50,6 +54,7 @@ public class Option implements Comparable<Option> {
     public Decision decision;
 
     public double weight;
+    public double remainingWeight;
     public int cacheFactor = 1;
     public double p;
 
@@ -154,6 +159,24 @@ public Activation getAct() {
     }
 
 
+    public void computeRemainingWeight() {
+        double sum = 0.0;
+        for(Option c: children) {
+            sum += c.weight;
+        }
+
+        remainingWeight = weight - sum;
+    }
+
+
+    public void traverse(Consumer<Option> f) {
+        for(Option c: children) {
+            c.traverse(f);
+            f.accept(c);
+        }
+    }
+
+
     public String toString() {
         StringBuilder sb = new StringBuilder();
         sb.append(" snId:" + (searchNode != null ? searchNode.getId() : "-") + " d:"  + decision + " cacheFactor:" + cacheFactor + " w:" + Utils.round(weight) + " p:" + p + " value:" + Utils.round(state.value));

src/main/java/network/aika/neuron/activation/search/SearchNode.java

@@ -233,7 +233,6 @@ public static void search(Document doc, SearchNode root, long v, Long timeoutInM
                     returnWeight = sn.finalStep();
                     returnWeightSum = sn.getWeightSum();
 
-                    sn.currentChildDecision = UNKNOWN;
                     sn = sn.parent;
                     break;
                 default:
@@ -319,8 +318,6 @@ private boolean prepareStep(Document doc, Decision d) throws OscillatingActivati
 
         act.debugDecisionCounts[d.ordinal()]++;
 
-        currentChildDecision = d;
-
         return true;
     }