Added support for different activation and loss functions

.idea/gradle.xml

@@ -1,5 +1,6 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
+  <component name="GradleMigrationSettings" migrationVersion="1" />
   <component name="GradleSettings">
     <option name="linkedExternalProjectsSettings">
       <GradleProjectSettings>

.idea/workspace.xml

@@ -4,11 +4,13 @@
     <option name="autoReloadType" value="SELECTIVE" />
   </component>
   <component name="ChangeListManager">
-    <list default="true" id="75a8c215-b746-4a4d-aa16-f3223c12b1ed" name="Changes" comment="Initial commit">
+    <list default="true" id="75a8c215-b746-4a4d-aa16-f3223c12b1ed" name="Changes" comment="Commented out not yet working code">
+      <change afterPath="$PROJECT_DIR$/src/main/java/ActivationFunctions.java" afterDir="false" />
+      <change afterPath="$PROJECT_DIR$/src/main/java/LossFunctions.java" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/.idea/gradle.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/gradle.xml" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/src/main/java/ActivationLayer.java" beforeDir="false" afterPath="$PROJECT_DIR$/src/main/java/ActivationLayer.java" afterDir="false" />
-      <change beforePath="$PROJECT_DIR$/src/main/java/FCLayer.java" beforeDir="false" afterPath="$PROJECT_DIR$/src/main/java/FCLayer.java" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/src/main/java/ExampleXOR.java" beforeDir="false" afterPath="$PROJECT_DIR$/src/main/java/ExampleXOR.java" afterDir="false" />
-      <change beforePath="$PROJECT_DIR$/src/main/java/Layer.java" beforeDir="false" afterPath="$PROJECT_DIR$/src/main/java/Layer.java" afterDir="false" />
       <change beforePath="$PROJECT_DIR$/src/main/java/Network.java" beforeDir="false" afterPath="$PROJECT_DIR$/src/main/java/Network.java" afterDir="false" />
     </list>
     <option name="SHOW_DIALOG" value="false" />
@@ -21,6 +23,23 @@
       <ProjectState />
     </projectState>
   </component>
+  <component name="ExternalProjectsManager">
+    <system id="GRADLE">
+      <state>
+        <projects_view>
+          <tree_state>
+            <expand>
+              <path>
+                <item name="" type="6a2764b6:ExternalProjectsStructure$RootNode" />
+                <item name="JavaNN" type="f1a62948:ProjectNode" />
+              </path>
+            </expand>
+            <select />
+          </tree_state>
+        </projects_view>
+      </state>
+    </system>
+  </component>
   <component name="FileTemplateManagerImpl">
     <option name="RECENT_TEMPLATES">
       <list>
@@ -29,6 +48,11 @@
     </option>
   </component>
   <component name="Git.Settings">
+    <option name="RECENT_BRANCH_BY_REPOSITORY">
+      <map>
+        <entry key="$PROJECT_DIR$" value="a431e08264a1ba49995b5b45ab2e2233f40a9a1d" />
+      </map>
+    </option>
     <option name="RECENT_GIT_ROOT_PATH" value="$PROJECT_DIR$" />
   </component>
   <component name="MarkdownSettingsMigration">
@@ -59,6 +83,7 @@
     <recent_temporary>
       <list>
         <item itemvalue="Application.ExampleXOR" />
+        <item itemvalue="Application.ExampleXOR" />
       </list>
     </recent_temporary>
   </component>
@@ -71,6 +96,14 @@
       <option name="presentableId" value="Default" />
       <updated>1653154357924</updated>
     </task>
+    <task id="LOCAL-00001" summary="Commented out not yet working code">
+      <created>1653168727185</created>
+      <option name="number" value="00001" />
+      <option name="presentableId" value="LOCAL-00001" />
+      <option name="project" value="LOCAL" />
+      <updated>1653168727186</updated>
+    </task>
+    <option name="localTasksCounter" value="2" />
     <servers />
   </component>
   <component name="Vcs.Log.Tabs.Properties">
@@ -86,9 +119,10 @@
   </component>
   <component name="VcsManagerConfiguration">
     <MESSAGE value="Initial commit" />
-    <option name="LAST_COMMIT_MESSAGE" value="Initial commit" />
+    <MESSAGE value="Commented out not yet working code" />
+    <option name="LAST_COMMIT_MESSAGE" value="Commented out not yet working code" />
   </component>
   <component name="com.intellij.coverage.CoverageDataManagerImpl">
-    <SUITE FILE_PATH="coverage/JavaNN$ExampleXOR.ic" NAME="ExampleXOR Coverage Results" MODIFIED="1653164239216" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="idea" COVERAGE_BY_TEST_ENABLED="false" COVERAGE_TRACING_ENABLED="false" />
+    <SUITE FILE_PATH="coverage/JavaNN$ExampleXOR.ic" NAME="ExampleXOR Coverage Results" MODIFIED="1653174521293" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="idea" COVERAGE_BY_TEST_ENABLED="false" COVERAGE_TRACING_ENABLED="false" />
   </component>
 </project>

src/main/java/ActivationFunctions.java

@@ -0,0 +1,39 @@
+import org.ejml.simple.SimpleMatrix;
+
+public class ActivationFunctions {
+    public static SimpleMatrix tanh(SimpleMatrix A) {
+        SimpleMatrix B = new SimpleMatrix(A);
+        for (int i = 0; i < A.getNumElements(); i++) {
+            B.set(i, Math.tanh(A.get(i)));
+        }
+        return B;
+    }
+
+    public static SimpleMatrix tanhPrime(SimpleMatrix A) {
+        SimpleMatrix B = new SimpleMatrix(A);
+        for (int i = 0; i < A.getNumElements(); i++) {
+            B.set(i, 1 - Math.pow(Math.tanh(A.get(i)), 2));
+        }
+        return B;
+    }
+
+    public static SimpleMatrix logistic(SimpleMatrix A) {
+        SimpleMatrix B = new SimpleMatrix(A);
+        for (int i = 0; i < A.getNumElements(); i++) {
+            B.set(i, sigma(-A.get(i)));
+        }
+        return B;
+    }
+
+    public static SimpleMatrix logisticPrime(SimpleMatrix A) {
+        SimpleMatrix B = new SimpleMatrix(A);
+        for (int i = 0; i < A.getNumElements(); i++) {
+            B.set(i, sigma(A.get(i) * (1 - sigma(A.get(i)))));
+        }
+        return B;
+    }
+
+    private static double sigma(double value) {
+        return 1 / (1 + Math.exp(-value));
+    }
+}

src/main/java/ActivationLayer.java

@@ -1,7 +1,8 @@
 import org.ejml.simple.SimpleMatrix;
 
+import java.util.function.Function;
+
 public class ActivationLayer extends Layer {
-    /* custom activation functions not yet supported
     Function<SimpleMatrix, SimpleMatrix> activation;
     Function<SimpleMatrix, SimpleMatrix> activationPrime;
 
@@ -9,35 +10,16 @@ public class ActivationLayer extends Layer {
         this.activation = activation;
         this.activationPrime = activationPrime;
     }
-    */
-
-    public ActivationLayer() {}
 
     @Override
     public SimpleMatrix forwardPropagation(SimpleMatrix input) {
         this.input = input;
-        this.output = tanh(input);
+        this.output = activation.apply(input);
         return this.output;
     }
 
     @Override
     public SimpleMatrix backwardPropagation(SimpleMatrix outputError, double learningRate) {
-        return tanhPrime(this.input).elementMult(outputError);
+        return activationPrime.apply(this.input).elementMult(outputError);
-    }
-
-    private SimpleMatrix tanh(SimpleMatrix A) {
-        SimpleMatrix B = new SimpleMatrix(A);
-        for (int i = 0; i < A.getNumElements(); i++) {
-            B.set(i, Math.tanh(A.get(i)));
-        }
-        return B;
-    }
-
-    private SimpleMatrix tanhPrime(SimpleMatrix A) {
-        SimpleMatrix B = new SimpleMatrix(A);
-        for (int i = 0; i < A.getNumElements(); i++) {
-            B.set(i, 1 - Math.pow(Math.tanh(A.get(i)), 2));
-        }
-        return B;
     }
 }

src/main/java/ExampleXOR.java

@@ -1,7 +1,5 @@
 import org.ejml.simple.SimpleMatrix;
 
-import java.util.ArrayList;
-
 public class ExampleXOR {
     public static void main(String[] args) {
         SimpleMatrix[] X_train = {new SimpleMatrix(new double[][]{{0, 0}}),
@@ -15,13 +13,14 @@ public class ExampleXOR {
 
         Network network = new Network();
         network.add(new FCLayer(2, 3));
-        network.add(new ActivationLayer());
+        network.add(new ActivationLayer(ActivationFunctions::tanh, ActivationFunctions::tanhPrime));
         network.add(new FCLayer(3, 1));
-        network.add(new ActivationLayer());
+        network.add(new ActivationLayer(ActivationFunctions::tanh, ActivationFunctions::tanhPrime));
 
+        network.use(LossFunctions::MSE, LossFunctions::MSEPrime);
         network.fit(X_train, y_train, 1000, 0.1d);
 
-        ArrayList<SimpleMatrix> output = network.predict(X_train);
+        SimpleMatrix[] output = network.predict(X_train);
         for (SimpleMatrix entry : output) {
             System.out.println("Prediction:");
             for (int i = 0; i < entry.getNumElements(); i++) {

src/main/java/LossFunctions.java

@@ -0,0 +1,17 @@
+import org.ejml.simple.SimpleMatrix;
+
+public class LossFunctions {
+    public static double MSE(SimpleMatrix y_true, SimpleMatrix y_pred) {
+        SimpleMatrix temp = y_true.minus(y_pred);
+        temp = temp.elementMult(temp);
+        double sum = 0;
+        for (int i = 0; i < temp.getNumElements(); i++) {
+            sum += temp.get(i);
+        }
+        return sum / temp.getNumElements();
+    }
+
+    public static SimpleMatrix MSEPrime(SimpleMatrix y_true, SimpleMatrix y_pred) {
+        return y_true.minus(y_pred).divide((double) y_true.getNumElements()/2);
+    }
+}

src/main/java/Network.java

@@ -1,20 +1,13 @@
 import org.ejml.simple.SimpleMatrix;
 
 import java.util.ArrayList;
+import java.util.function.BiFunction;
 
 public class Network {
 
     ArrayList<Layer> layers;
-
+    BiFunction<SimpleMatrix, SimpleMatrix, Double> loss;
-    /* custom loss functions not yet supported
+    BiFunction<SimpleMatrix, SimpleMatrix, SimpleMatrix> lossPrime;
-    Function<SimpleMatrix, Double> loss;
-    Function<SimpleMatrix, Double> lossPrime;
-
-    public void use(Function<SimpleMatrix, Double> loss, Function<SimpleMatrix, Double> lossPrime) {
-        this.loss = loss;
-        this.lossPrime = lossPrime;
-    }
-    */
 
     public Network() {
         layers = new ArrayList<>();
@@ -24,16 +17,23 @@ public class Network {
         layers.add(layer);
     }
 
-    public ArrayList<SimpleMatrix> predict(SimpleMatrix[] inputs) {
+    public void use(BiFunction<SimpleMatrix, SimpleMatrix, Double> loss, BiFunction<SimpleMatrix, SimpleMatrix, SimpleMatrix> lossPrime) {
-        ArrayList<SimpleMatrix> result = new ArrayList<>();
+        this.loss = loss;
+        this.lossPrime = lossPrime;
+    }
+
+    public SimpleMatrix[] predict(SimpleMatrix[] inputs) {
+        SimpleMatrix[] result = new SimpleMatrix[inputs.length];
         SimpleMatrix output;
+        int i = 0;
 
         for (SimpleMatrix input : inputs) {
             output = input;
             for (Layer l : layers) {
                 output = l.forwardPropagation(output);
             }
-            result.add(output);
+            result[i] = output;
+            i++;
         }
 
         return result;
@@ -52,10 +52,10 @@ public class Network {
                 }
 
                 // compute loss (for display purpose only)
-                err = MSE(y_train[j], output);
+                err = loss.apply(y_train[j], output);
 
                 // backward propagation
-                SimpleMatrix error = MSEPrime(y_train[j], output);
+                SimpleMatrix error = lossPrime.apply(y_train[j], output);
                 for (int k = layers.size() - 1; k >= 0; k--) {
                     error = layers.get(k).backwardPropagation(error, learningRate);
                 }
@@ -65,18 +65,4 @@ public class Network {
             System.out.println("epoch " + (i+1) + "/" + epochs + "  error=" + err);
         }
     }
-
-    private double MSE(SimpleMatrix y_true, SimpleMatrix y_pred) {
-        SimpleMatrix temp = y_true.minus(y_pred);
-        temp = temp.elementMult(temp);
-        double sum = 0;
-        for (int i = 0; i < temp.getNumElements(); i++) {
-            sum += temp.get(i);
-        }
-        return sum / temp.getNumElements();
-    }
-
-    private SimpleMatrix MSEPrime(SimpleMatrix y_true, SimpleMatrix y_pred) {
-        return y_true.minus(y_pred).divide((double) y_true.getNumElements()/2);
-    }
 }