Fixed missing imports

Signed-off-by: brian <brian@brutex.de>

brutex-extended-tests/src/test/java/net/brutex/gan/App.java

@@ -21,14 +21,14 @@
 
 package net.brutex.gan;
 
-import java.awt.BorderLayout;
+import java.awt.*;
-import java.awt.Dimension;
-import java.awt.GridLayout;
-import java.awt.Image;
 import java.awt.image.BufferedImage;
 import java.io.File;
+import java.io.IOException;
 import java.util.Arrays;
 import java.util.Random;
+import java.util.UUID;
+import javax.imageio.ImageIO;
 import javax.swing.ImageIcon;
 import javax.swing.JFrame;
 import javax.swing.JLabel;
@@ -82,9 +82,9 @@ public class App {
 
   private static final int X_DIM = 20 ;
   private static final int Y_DIM = 20;
-  private static final int CHANNELS = 3;
+  private static final int CHANNELS = 1;
-  private static final int batchSize = 50;
+  private static final int batchSize = 1;
-  private static final int INPUT = 128;
+  private static final int INPUT = 10;
 
   private static final int OUTPUT_PER_PANEL = 16;
 
@@ -96,6 +96,8 @@ public class App {
   private static JPanel panel;
   private static JPanel panel2;
 
+  private static final String OUTPUT_DIR = "C:/temp/output/";
+
   private static LayerConfiguration[] genLayers() {
     return new LayerConfiguration[] {
         DenseLayer.builder().nIn(INPUT).nOut(X_DIM*Y_DIM*CHANNELS).weightInit(WeightInit.NORMAL).build(),
@@ -103,6 +105,7 @@ public class App {
 
         DenseLayer.builder().nIn(X_DIM*Y_DIM*CHANNELS).nOut(X_DIM*Y_DIM).build(),
         ActivationLayer.builder(new ActivationLReLU(0.2)).build(),
+            DropoutLayer.builder(1 - 0.5).build(),
         DenseLayer.builder().nIn(X_DIM*Y_DIM).nOut(X_DIM*Y_DIM).build(),
         ActivationLayer.builder(new ActivationLReLU(0.2)).build(),
 
@@ -207,6 +210,12 @@ public class App {
 
   @Test
   public void runTest() throws Exception {
+      if(! log.isDebugEnabled()) {
+          log.info("Logging is not set to DEBUG");
+          }
+      else {
+          log.info("Logging is set to DEBUG");
+      }
     main();
   }
 
@@ -240,25 +249,25 @@ public class App {
     MultiLayerNetwork gan = new MultiLayerNetwork(gan());
     gen.init(); log.debug("Generator network: {}", gen);
     dis.init(); log.debug("Discriminator network: {}", dis);
-    gan.init(); log.debug("Complete GAN network: {}", gan);
+    gan.init(); log.info("Complete GAN network: {}", gan);
 
 
     copyParams(gen, dis, gan);
 
-    gen.addTrainingListeners(new PerformanceListener(15, true));
+    //gen.addTrainingListeners(new PerformanceListener(15, true, "GEN"));
-    //dis.addTrainingListeners(new PerformanceListener(10, true));
+    dis.addTrainingListeners(new PerformanceListener(10, true, "DIS"));
-    //gan.addTrainingListeners(new PerformanceListener(10, true));
+    gan.addTrainingListeners(new PerformanceListener(10, true, "GAN"));
     //gan.addTrainingListeners(new ScoreToChartListener("gan"));
     //dis.setListeners(new ScoreToChartListener("dis"));
 
-    System.out.println(gan.toString());
+    //System.out.println(gan.toString());
-    gan.fit(Nd4j.rand(batchSize, CHANNELS, X_DIM, Y_DIM), Nd4j.zeros(batchSize, 1));
+    //gan.fit(Nd4j.rand(batchSize, CHANNELS, X_DIM, Y_DIM), Nd4j.zeros(batchSize, 1));
 
     //gan.fit(new DataSet(trainData.next().getFeatures(), Nd4j.zeros(batchSize, 1)));
     //trainData.reset();
 
     int j = 0;
-    for (int i = 0; i < 201; i++) { //epoch
+    for (int i = 0; i < 51; i++) { //epoch
       while (trainData.hasNext()) {
         j++;
 
@@ -282,6 +291,9 @@ public class App {
 //        int batchSize = (int) real.shape()[0];
 
         INDArray fakeIn = Nd4j.rand(batchSize, CHANNELS, X_DIM, Y_DIM);
+        //INDArray fakeIn = Nd4j.rand(new int[]{batchSize, X_DIM*Y_DIM}); //hack for MNIST only, use above otherwise
+
+
         INDArray fake = gan.activateSelectedLayers(0, gen.getLayers().length - 1, fakeIn);
         fake = fake.reshape(batchSize, CHANNELS, X_DIM, Y_DIM);
 
@@ -299,11 +311,11 @@ public class App {
         updateGan(gen, dis, gan);
 
         //gan.fit(new DataSet(Nd4j.rand(batchSize, INPUT), Nd4j.zeros(batchSize, 1)));
-        gan.fit(new DataSet(Nd4j.rand(batchSize, CHANNELS, X_DIM, Y_DIM), Nd4j.zeros(batchSize, 1)));
+        gan.fit(new DataSet(Nd4j.rand(batchSize, CHANNELS, X_DIM, Y_DIM), Nd4j.ones(batchSize, 1)));
 
         //Visualize and reporting
         if (j % 10 == 1) {
-          System.out.println("Iteration " + j + " Visualizing...");
+          System.out.println("Epoch " + i + " Iteration " + j + " Visualizing...");
           INDArray[] samples = batchSize > OUTPUT_PER_PANEL ? new INDArray[OUTPUT_PER_PANEL] : new INDArray[batchSize];
 
 
@@ -330,11 +342,12 @@ public class App {
       }
         // Copy the GANs generator to gen.
         updateGen(gen, gan);
+        gen.save(new File("mnist-mlp-generator.dlj"));
     }
 
 
 
-    gen.save(new File("mnist-mlp-generator.dlj"));
+
   }
 
   private static void copyParams(MultiLayerNetwork gen, MultiLayerNetwork dis, MultiLayerNetwork gan) {
@@ -342,10 +355,10 @@ public class App {
     for (int i = 0; i < gan.getLayers().length; i++) {
       if (i < genLayerCount) {
         if(gan.getLayer(i).getParams() != null)
-         gen.getLayer(i).setParams(gan.getLayer(i).getParams());
+         gan.getLayer(i).setParams(gen.getLayer(i).getParams());
       } else {
         if(gan.getLayer(i).getParams() != null)
-        dis.getLayer(i - genLayerCount).setParams(gan.getLayer(i).getParams());
+        gan.getLayer(i ).setParams(dis.getLayer(i- genLayerCount).getParams());
       }
     }
   }
@@ -411,14 +424,50 @@ public class App {
         }
       }
     }
-
     ImageIcon orig = new ImageIcon(bi);
-
     Image imageScaled = orig.getImage().getScaledInstance((4 * X_DIM), (4 * Y_DIM), Image.SCALE_DEFAULT);
-
     ImageIcon scaled = new ImageIcon(imageScaled);
-
+    if(! isOrig)  saveImage(imageScaled, batchElement, isOrig);
     return new JLabel(scaled);
 
   }
+
+  private static void saveImage(Image image, int batchElement, boolean isOrig) {
+    String outputDirectory = OUTPUT_DIR; // Set the output directory where the images will be saved
+
+    try {
+      // Save the images to disk
+      saveImage(image, outputDirectory, UUID.randomUUID().toString()+".png");
+
+     log.debug("Images saved successfully.");
+    } catch (IOException e) {
+      log.error("Error saving the images: {}", e.getMessage());
+    }
+}
+    private static void saveImage(Image image, String outputDirectory, String fileName) throws IOException {
+        File directory = new File(outputDirectory);
+        if (!directory.exists()) {
+            directory.mkdir();
+        }
+
+        File outputFile = new File(directory, fileName);
+        ImageIO.write(imageToBufferedImage(image), "png", outputFile);
+    }
+
+    public static BufferedImage imageToBufferedImage(Image image) {
+        if (image instanceof BufferedImage) {
+            return (BufferedImage) image;
+        }
+
+        // Create a buffered image with the same dimensions and transparency as the original image
+        BufferedImage bufferedImage = new BufferedImage(image.getWidth(null), image.getHeight(null), BufferedImage.TYPE_INT_ARGB);
+
+        // Draw the original image onto the buffered image
+        Graphics2D g2d = bufferedImage.createGraphics();
+        g2d.drawImage(image, 0, 0, null);
+        g2d.dispose();
+
+        return bufferedImage;
+    }
+
 }

brutex-extended-tests/src/test/resources/simplelogger.properties

@@ -25,7 +25,7 @@
 # Default logging detail level for all instances of SimpleLogger.
 # Must be one of ("trace", "debug", "info", "warn", or "error").
 # If not specified, defaults to "info".
-org.slf4j.simpleLogger.defaultLogLevel=trace
+org.slf4j.simpleLogger.defaultLogLevel=debug
 
 # Logging detail level for a SimpleLogger instance named "xxxxx".
 # Must be one of ("trace", "debug", "info", "warn", or "error").
@@ -42,8 +42,8 @@ org.slf4j.simpleLogger.defaultLogLevel=trace
 # If the format is not specified or is invalid, the default format is used.
 # The default format is yyyy-MM-dd HH:mm:ss:SSS Z.
 #org.slf4j.simpleLogger.dateTimeFormat=yyyy-MM-dd HH:mm:ss:SSS Z
-org.slf4j.simpleLogger.dateTimeFormat=yyyy-MM-dd HH:mm:ss
+#org.slf4j.simpleLogger.dateTimeFormat=yyyy-MM-dd HH:mm:ss
 
 # Set to true if you want to output the current thread name.
 # Defaults to true.
-org.slf4j.simpleLogger.showThreadName=true
+#org.slf4j.simpleLogger.showThreadName=true

cavis-dnn/cavis-dnn-modelimport/src/test/java/org/deeplearning4j/nn/modelimport/keras/configurations/JsonTest.java

@@ -23,6 +23,7 @@ package org.deeplearning4j.nn.modelimport.keras.configurations;
 import org.deeplearning4j.nn.conf.InputPreProcessor;
 import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
 import org.deeplearning4j.BaseDL4JTest;
+import org.deeplearning4j.nn.conf.serde.CavisMapper;
 import org.deeplearning4j.nn.modelimport.keras.preprocessors.KerasFlattenRnnPreprocessor;
 import org.deeplearning4j.nn.modelimport.keras.preprocessors.PermutePreprocessor;
 import org.deeplearning4j.nn.modelimport.keras.preprocessors.ReshapePreprocessor;

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/optimize/listeners/PerformanceListener.java

@@ -55,6 +55,8 @@ public class PerformanceListener extends BaseTrainingListener implements Seriali
     private boolean reportEtl = true;
     private boolean reportTime = true;
 
+    private final String name;
+
 
 
     public PerformanceListener(int frequency) {
@@ -66,14 +68,22 @@ public class PerformanceListener extends BaseTrainingListener implements Seriali
     }
 
     public PerformanceListener(int frequency, boolean reportScore, boolean reportGC) {
+       this(frequency, reportScore, reportGC, "no-name");
+    }
+    public PerformanceListener(int frequency, boolean reportScore, boolean reportGC, String name) {
         Preconditions.checkArgument(frequency > 0, "Invalid frequency, must be > 0: Got " + frequency);
         this.frequency = frequency;
         this.reportScore = reportScore;
         this.reportGC = reportGC;
+        this.name = name;
 
         lastTime.set(System.currentTimeMillis());
     }
 
+    public PerformanceListener(int frequency, boolean reportScore, String name) {
+        this(frequency, reportScore, false, name);
+    }
+
     @Override
     public void iterationDone(IModel model, int iteration, int epoch) {
         // we update lastTime on every iteration
@@ -116,6 +126,7 @@ public class PerformanceListener extends BaseTrainingListener implements Seriali
 
 
             StringBuilder builder = new StringBuilder();
+            builder.append("Name: '"+name+"'");
 
             if (Nd4j.getAffinityManager().getNumberOfDevices() > 1)
                 builder.append("Device: [").append(Nd4j.getAffinityManager().getDeviceForCurrentThread()).append("]; ");

gradle/wrapper/gradle-wrapper.properties

@@ -1,5 +1,5 @@
 distributionBase=GRADLE_USER_HOME
 distributionPath=wrapper/dists
-distributionUrl=https\://services.gradle.org/distributions/gradle-7.5.1-bin.zip
+distributionUrl=https\://services.gradle.org/distributions/gradle-8.2.1-bin.zip
 zipStoreBase=GRADLE_USER_HOME
 zipStorePath=wrapper/dists

gradlew

@@ -116,7 +116,6 @@ esac
 
 CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
 
-
 # Determine the Java command to use to start the JVM.
 if [ -n "$JAVA_HOME" ]; then
   if [ -x "$JAVA_HOME/jre/sh/java" ]; then
@@ -145,12 +144,14 @@ if ! "$cygwin" && ! "$darwin" && ! "$nonstop" ; then
   max*)
     MAX_FD=$(ulimit -H -n) ||
       warn "Could not query maximum file descriptor limit"
+    ;;
   esac
   case $MAX_FD in #(
   '' | soft) : ;; #(
   *)
     ulimit -n "$MAX_FD" ||
       warn "Could not set maximum file descriptor limit to $MAX_FD"
+    ;;
   esac
 fi
 
@@ -170,12 +171,14 @@ if "$cygwin" || "$msys" ; then
   JAVACMD=$(cygpath --unix "$JAVACMD")
 
   # Now convert the arguments - kludge to limit ourselves to /bin/sh
-    for arg do
+  for arg; do
     if
       case $arg in #(
       -*) false ;; # don't mess with options #(
-              /?*)  t=${arg#/} t=/${t%%/*}              # looks like a POSIX filepath
+      /?*)
-                    [ -e "$t" ] ;;                      #(
+        t=${arg#/} t=/${t%%/*} # looks like a POSIX filepath
+        [ -e "$t" ]
+        ;; #(
       *) false ;;
       esac
     then
@@ -205,6 +208,11 @@ set -- \
   org.gradle.wrapper.GradleWrapperMain \
   "$@"
 
+# Stop when "xargs" is not available.
+if ! command -v xargs >/dev/null 2>&1; then
+  die "xargs is not available"
+fi
+
 # Use "xargs" to parse quoted args.
 #
 # With -n1 it outputs one arg per line, with the quotes and backslashes removed.

gradlew.bat

@@ -40,7 +40,7 @@ if defined JAVA_HOME goto findJavaFromJavaHome
 
 set JAVA_EXE=java.exe
 %JAVA_EXE% -version >NUL 2>&1
-if "%ERRORLEVEL%" == "0" goto execute
+if %ERRORLEVEL% equ 0 goto execute
 
 echo.
 echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
@@ -75,13 +75,15 @@ set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
 
 :end
 @rem End local scope for the variables with windows NT shell
-if "%ERRORLEVEL%"=="0" goto mainEnd
+if %ERRORLEVEL% equ 0 goto mainEnd
 
 :fail
 rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
 rem the _cmd.exe /c_ return code!
-if  not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
+set EXIT_CODE=%ERRORLEVEL%
-exit /b 1
+if %EXIT_CODE% equ 0 set EXIT_CODE=1
+if not ""=="%GRADLE_EXIT_CONSOLE%" exit %EXIT_CODE%
+exit /b %EXIT_CODE%
 
 :mainEnd
 if "%OS%"=="Windows_NT" endlocal

settings.gradle

@@ -70,7 +70,7 @@ apply from: "chooseBackend.gradle"
 rootProject.name = "Cavis"
 
 enableFeaturePreview("TYPESAFE_PROJECT_ACCESSORS")
-enableFeaturePreview("VERSION_CATALOGS")
+//enableFeaturePreview("VERSION_CATALOGS") //only needed for gradle <8
 
 
 sourceControl {