- fixed isPosFeedbackSlotBlocked for primary BindingActivations

lukas.molzberger · lukas.molzberger · commit 517250f97ccc · 2024-05-06T08:41:11.000+02:00
diff --git a/core/src/main/java/network/aika/elements/activations/types/BindingActivation.java b/core/src/main/java/network/aika/elements/activations/types/BindingActivation.java
@@ -131,7 +131,7 @@ public boolean checkPrimary() {
     private boolean isPosFeedbackSlotBlocked() {
         SynapseSlot<InnerPositiveFeedbackSynapse, InnerPositiveFeedbackLink> slot = getInputSlotBySynapseType(InnerPositiveFeedbackSynapse.class);
 
-        if(slot == null)
+        if(slot == null || slot.getLinks().count() == 0)
             return false;
 
         InnerPositiveFeedbackLink l = slot.getSelectedLink();
diff --git a/core/src/main/java/network/aika/elements/links/CategoryInputLink.java b/core/src/main/java/network/aika/elements/links/CategoryInputLink.java
@@ -44,10 +44,6 @@ default void instantiateCategoryLink(Activation instanceAct) {
         if(categoryAct == null || instanceAct == null)
             return;
 
-        Link l = categoryAct.getInputLink(instanceAct, getSynapse().getSynapseId());
-        if(l != null)
-            return;
-
         CategorySynapse s = createCategorySynapse();
         s.initFromTemplate(instanceAct.getNeuron(), categoryAct.getNeuron(), getSynapse());
 
diff --git a/core/src/main/java/network/aika/elements/neurons/Neuron.java b/core/src/main/java/network/aika/elements/neurons/Neuron.java
@@ -83,7 +83,7 @@ public abstract class Neuron<N extends Neuron, A extends Activation> implements
 
     protected boolean allowTraining = true;
 
-    private boolean instantiable = true;
+    private boolean instantiable;
 
     protected InitParams initParams;
 
diff --git a/core/src/main/java/network/aika/elements/synapses/Synapse.java b/core/src/main/java/network/aika/elements/synapses/Synapse.java
@@ -77,8 +77,8 @@ public abstract class Synapse<S extends Synapse, I extends Neuron, O extends Neu
 
     private Relation relation;
 
-    private boolean inputSideInstantiable = true;
-    private boolean outputSideInstantiable = true;
+    private boolean inputSideInstantiable;
+    private boolean outputSideInstantiable;
 
     protected SumField weight = (SumField) new SumField(this, "weight", TOLERANCE)
             .setQueued(getQueue(), TRAINING, false)
diff --git a/core/src/main/java/network/aika/elements/synapses/slots/SynapseOutputSlot.java b/core/src/main/java/network/aika/elements/synapses/slots/SynapseOutputSlot.java
@@ -16,7 +16,6 @@
  */
 package network.aika.elements.synapses.slots;
 
-import network.aika.elements.activations.Activation;
 import network.aika.elements.activations.ConjunctiveActivation;
 import network.aika.elements.links.ConjunctiveLink;
 import network.aika.elements.synapses.ConjunctiveSynapse;
diff --git a/text/src/main/java/network/aika/meta/NetworkMotifs.java b/text/src/main/java/network/aika/meta/NetworkMotifs.java
@@ -90,7 +90,8 @@ public static OuterPositiveFeedbackSynapse addOuterPositiveFeedbackLoop(
             PatternNeuron pn,
             BindingNeuron bn,
             PatternNeuron feedbackPN,
-            double psWeight
+            double psWeight,
+            boolean instantiable
     ) {
         addPositiveFeedbackLoop(
                 bn,
@@ -99,43 +100,27 @@ public static OuterPositiveFeedbackSynapse addOuterPositiveFeedbackLoop(
                 0.0,
                 false,
                 false,
-                true
+                instantiable
         ).setPropagable(true);
 
         return new OuterPositiveFeedbackSynapse()
                 .setWeight(getPositiveFeedbackWeight(bn.getTargetNet(), bn.getTargetValue()))
                 .link(feedbackPN, bn)
+                .setInstantiable(true, true)
                 .adjustBias();
     }
 
-    public static void addInhibitoryLoop(BindingNeuron bn, InhibitoryNeuron in, double weight) {
+    public static void addInhibitoryLoop(BindingNeuron bn, InhibitoryNeuron in, double weight, boolean instantiable) {
         new InhibitorySynapse()
                 .setWeight(1.0)
-                .link(bn, in);
+                .link(bn, in)
+                .setInstantiable(instantiable, instantiable);
 
         new NegativeFeedbackSynapse()
                 .setWeight(weight)
                 .link(in, bn)
-                .adjustBias();
-    }
-
-    public static InnerPositiveFeedbackSynapse addPositiveFeedbackLoop(
-            BindingNeuron bn,
-            PatternNeuron pn,
-            double weight,
-            double weakInputMargin,
-            boolean allowRelaxedMatching,
-            boolean isOptional
-    ) {
-        return addPositiveFeedbackLoop(
-                bn,
-                pn,
-                weight,
-                weakInputMargin,
-                allowRelaxedMatching,
-                isOptional,
-                true
-        );
+                .adjustBias()
+                .setInstantiable(instantiable, instantiable);
     }
 
     public static InnerPositiveFeedbackSynapse addPositiveFeedbackLoop(
diff --git a/text/src/main/java/network/aika/meta/entities/EntityModel.java b/text/src/main/java/network/aika/meta/entities/EntityModel.java
@@ -135,7 +135,8 @@ public void initTemplateNeurons() {
                 .adjustBias()
                 .setInstantiable(true, true)
                 .getInput()
-                .setPersistent(true);
+                .setPersistent(true)
+                .setInstantiable(true);
 
         addInputObjectSynapse(
                 entityPattern,
@@ -151,20 +152,24 @@ public void initTemplateNeurons() {
                 10.0,
                 BINDING_NET_TARGET,
                 true
-        ).setTypeDescription("Abstract Phrase -> Entity BN");
+        )
+                .setTypeDescription("Abstract Phrase -> Entity BN");
 
         entityBN.makeAbstract()
                 .setWeight(getDefaultInputCategorySynapseWeight(entityBN.getType()))
                 .adjustBias()
-                .setInstantiable(true, true);
+                .setInstantiable(true, true)
+                .getInput()
+                .setInstantiable(true);
 
         addPositiveFeedbackLoop(
                 entityBN,
                 entityPattern,
                 2.5,
                 0.0,
                 false,
-                false
+                false,
+                true
         );
 
         inhibitoryN = new InhibitoryNeuron(getModel(), TEMPLATE_MODEL)
@@ -174,12 +179,15 @@ public void initTemplateNeurons() {
 
         inhibitoryN.makeAbstract()
                 .setInstantiable(true, true)
-                .setWeight(1.0);
+                .setWeight(1.0)
+                .getInput()
+                .setInstantiable(true);
 
         addInhibitoryLoop(
                 entityBN,
                 inhibitoryN,
-                NEG_MARGIN * -entityBN.getTargetNet()
+                NEG_MARGIN * -entityBN.getTargetNet(),
+                true
         );
 
         topicBN = addBindingNeuron(
@@ -191,7 +199,9 @@ public void initTemplateNeurons() {
         topicBN.makeAbstract()
                 .setWeight(getDefaultInputCategorySynapseWeight(topicBN.getType()))
                 .adjustBias()
-                .setInstantiable(true, true);
+                .setInstantiable(true, true)
+                .getInput()
+                .setInstantiable(true);
 
         disable();
     }
@@ -202,7 +212,8 @@ public void initOuterSynapses() {
                 entityPattern,
                 topicBN,
                 topicModel.getTopicPatternNeuron(),
-                2.5
+                2.5,
+                true
         );
     }
 
@@ -231,19 +242,20 @@ public Neuron resolveInstance(Neuron template, Document doc) {
     @Override
     public void prepareInstantiation() {
         setInstantiable(true);
-        phraseModel.getEntityBN().setInstantiable(false);
-        phraseModel.getPatternNeuron().setInstantiable(false);
+        phraseModel.setInstantiable(false);
     }
 
     @Override
     public void mapResults(Document doc) {
         phraseModel.getEntityBN().setInstantiable(false);
         phraseModel.getPatternNeuron().setInstantiable(true);
+        phraseModel.getInhibitoryNeuron().setInstantiable(false);
 
         entityPattern = lookupInstance(doc, parent.entityPattern);
         entityPattern.setPersistent(true);
 
         entityPattern.getOutputSynapseByType(OuterPositiveFeedbackSynapse.class)
+                .setInstantiable(true, true)
                 .setOptional(true);
 
         Synapse s = entityPattern.getOutputSynapse(getTopicModel().getTopicBindingNeuron().getProvider());
@@ -294,6 +306,9 @@ public void setInstantiable(boolean instantiable) {
 
         topicBN.setInstantiable(instantiable);
         topicBN.setInputSynapsesInstantiable(instantiable, instantiable);
+
+        inhibitoryN.setInstantiable(instantiable);
+        inhibitoryN.setInputSynapsesInstantiable(instantiable, instantiable);
     }
 
     public Model getModel() {
diff --git a/text/src/main/java/network/aika/meta/sequences/PhraseModel.java b/text/src/main/java/network/aika/meta/sequences/PhraseModel.java
@@ -59,6 +59,12 @@ public BindingNeuron getEntityBN() {
         return entityBN;
     }
 
+    public void setInstantiable(boolean instantiable) {
+        entityBN.setInstantiable(instantiable);
+        sequencePatternN.setInstantiable(instantiable);
+        inhibitoryN.setInstantiable(instantiable);
+    }
+
     @Override
     public String getPatternType() {
         return "Phrase";
@@ -78,6 +84,8 @@ public void initStaticNeurons() {
         entityBN.makeAbstract()
                 .setWeight(getDefaultInputCategorySynapseWeight(entityBN.getType()))
                 .adjustBias();
+
+        setInstantiable(true);
     }
 
     @Override
@@ -86,7 +94,8 @@ public void initOuterSynapses() {
                 sequencePatternN,
                 entityBN,
                 entityModel.getEntityPattern(),
-                2.5
+                2.5,
+                true
         ).setOptional(true);
     }
 
diff --git a/text/src/main/java/network/aika/meta/sequences/SequenceModel.java b/text/src/main/java/network/aika/meta/sequences/SequenceModel.java
@@ -223,6 +223,7 @@ protected BindingNeuron createSubPhraseBindingNeuron() {
                 2.5,
                 0.0,
                 false,
+                true,
                 true
         );
 
@@ -303,7 +304,8 @@ protected BindingNeuron createBindingNeuron(
         addInhibitoryLoop(
                 bn,
                 inhibitoryN,
-                getNegMargin(pos) * -bn.getTargetNet()
+                getNegMargin(pos) * -bn.getTargetNet(),
+                true
         );
 
         addPositiveFeedbackLoop(
@@ -312,7 +314,8 @@ protected BindingNeuron createBindingNeuron(
                 p.pfWeight,
                 p.weakInputMargin,
                 allowRelaxedMatching,
-                isOptional
+                isOptional,
+                true
         );
 
         return bn;
diff --git a/text/src/main/java/network/aika/meta/topics/TopicModel.java b/text/src/main/java/network/aika/meta/topics/TopicModel.java
@@ -177,6 +177,7 @@ public void initTemplateNeurons() {
                 2.5,
                 0.0,
                 false,
+                true,
                 true
         );
 
@@ -194,7 +195,8 @@ public void initTemplateNeurons() {
         addInhibitoryLoop(
                 topicBN,
                 inhibitoryN,
-                NEG_MARGIN * -topicBN.getTargetNet()
+                NEG_MARGIN * -topicBN.getTargetNet(),
+                true
         );
 
         setInstantiable(false);
diff --git a/text/src/test/java/network/aika/TestHelper.java b/text/src/test/java/network/aika/TestHelper.java
@@ -195,8 +195,8 @@ public static void initPatternTheDog(Model m, Dictionary dict, InhibitoryNeuron
 
         PatternNeuron theDogP = initPatternLoop(m, "the dog", theBN, dogBN);
 
-        addInhibitoryLoop(theBN, inhibNThe, -10.0);
-        addInhibitoryLoop(theBN, new InhibitoryNeuron(m, NEURON_EXTERNAL).setLabel("I-the (tg)"), -10.0);
+        addInhibitoryLoop(theBN, inhibNThe, -10.0, true);
+        addInhibitoryLoop(theBN, new InhibitoryNeuron(m, NEURON_EXTERNAL).setLabel("I-the (tg)"), -10.0, true);
 
         theDogP.setBias(3.0);
 
diff --git a/text/src/test/java/network/aika/TestUtils.java b/text/src/test/java/network/aika/TestUtils.java
@@ -52,7 +52,7 @@ public static InhibitoryNeuron addOuterInhibitoryLoop(InhibitoryNeuron inhibN, b
             return null;
 
         for(BindingNeuron bn: bns) {
-            NetworkMotifs.addInhibitoryLoop(bn, inhibN, -20.0);
+            NetworkMotifs.addInhibitoryLoop(bn, inhibN, -20.0, true);
         }
         return inhibN;
     }
@@ -68,7 +68,8 @@ public static PatternNeuron initPatternLoop(Model m, String label, BindingNeuron
                     10.0,
                     0.1,
                     false,
-                    false
+                    false,
+                    true
             );
         }
         return patternN;
