Fixing tests

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

.gitignore

@@ -36,7 +36,8 @@ pom.xml.versionsBackup
 pom.xml.next
 release.properties
 *dependency-reduced-pom.xml
-*/build/*
+**/build/*
+.gradle/*
 
 # Specific for Nd4j
 *.md5
@@ -84,3 +85,14 @@ bruai4j-native-common/cmake*
 /bruai4j-native/bruai4j-native-common/blasbuild/
 /bruai4j-native/bruai4j-native-common/build/
 /cavis-native/cavis-native-lib/blasbuild/
+/cavis-dnn/cavis-dnn-core/build/reports/tests/cudaTest/classes/org.deeplearning4j.gradientcheck.AttentionLayerTest.html
+/cavis-dnn/cavis-dnn-core/build/reports/tests/cudaTest/css/base-style.css
+/cavis-dnn/cavis-dnn-core/build/reports/tests/cudaTest/css/style.css
+/cavis-dnn/cavis-dnn-core/build/reports/tests/cudaTest/js/report.js
+/cavis-dnn/cavis-dnn-core/build/reports/tests/cudaTest/packages/org.deeplearning4j.gradientcheck.html
+/cavis-dnn/cavis-dnn-core/build/reports/tests/cudaTest/index.html
+/cavis-dnn/cavis-dnn-core/build/resources/main/iris.dat
+/cavis-dnn/cavis-dnn-core/build/resources/test/junit-platform.properties
+/cavis-dnn/cavis-dnn-core/build/resources/test/logback-test.xml
+/cavis-dnn/cavis-dnn-core/build/test-results/cudaTest/TEST-org.deeplearning4j.gradientcheck.AttentionLayerTest.xml
+/cavis-dnn/cavis-dnn-core/build/tmp/jar/MANIFEST.MF

cavis-dnn/cavis-dnn-core/src/test/java/org/deeplearning4j/exceptions/TestInvalidConfigurations.java

@@ -309,7 +309,7 @@ public class TestInvalidConfigurations extends BaseDL4JTest {
 
         try {
             NeuralNetConfiguration conf = NeuralNetConfiguration.builder().convolutionMode(ConvolutionMode.Strict)
-                            .list()
+
                             .layer(0, ConvolutionLayer.builder().kernelSize(2, 3).stride(2, 2).padding(0, 0).nOut(5)
                                             .build())
                             .layer(1, OutputLayer.builder().nOut(10).build())

cavis-dnn/cavis-dnn-core/src/test/java/org/deeplearning4j/gradientcheck/CNN3DGradientCheckTest.java

@@ -114,7 +114,6 @@ public class CNN3DGradientCheckTest extends BaseDL4JTest {
                                                     .dataType(DataType.DOUBLE)
                                                     .updater(new NoOp()).weightInit(WeightInit.LECUN_NORMAL)
                                                     .dist(new NormalDistribution(0, 1))
-                                                    .list()
                                                     .layer(0, Convolution3D.builder().activation(afn).kernelSize(kernel)
                                                             .stride(stride).nIn(convNIn).nOut(convNOut1).hasBias(false)
                                                             .convolutionMode(mode).dataFormat(df)

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/NeuralNetBaseBuilderConfiguration.java

@@ -565,6 +565,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
       this.activation = activation;
       return self();
     }
+    @JsonIgnore
     public B activation(IActivation activation) {
       this.activation = activation;
       return self();
@@ -583,7 +584,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
     public B constrainWeights(LayerConstraint... constraints) {
       constrainWeights$value = Arrays.asList(constraints);
       constrainWeights$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -618,7 +619,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
     public B constrainAllParameters(LayerConstraint... constraints) {
       allParamConstraints$value = Arrays.asList(constraints);
       allParamConstraints$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -635,7 +636,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
     public B constrainBias(LayerConstraint... constraints) {
       biasConstraints$value = Arrays.asList(constraints);
       biasConstraints$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -645,10 +646,11 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
      * @param processor what to use to preProcess the data.
      * @return builder pattern
      */
-    public B inputPreProcessor(Integer layer, InputPreProcessor processor) {
+    public B inputPreProcessor(@NonNull Integer layer, @NonNull InputPreProcessor processor) {
+      if(inputPreProcessors$value==null) inputPreProcessors$value=new LinkedHashMap<>();
       inputPreProcessors$value.put(layer, processor);
       inputPreProcessors$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -658,7 +660,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
      * @param layer the layer
      * @return builder
      */
-    public B layer(Integer index, @NonNull LayerConfiguration layer) {
+    public B layer(@NonNull Integer index, @NonNull LayerConfiguration layer) {
       innerConfigurations$value.add(index, layer);
       innerConfigurations$set = true;
       return self();
@@ -680,10 +682,11 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
      * @param layer the layer
      * @return builder
      */
+    @JsonIgnore
     public B layer(@NonNull LayerConfiguration layer) {
       innerConfigurations$value.add(layer);
       innerConfigurations$set = true;
-      return (B) this;
+      return self();
     }
     public B layer(@NonNull LayerConfiguration.LayerConfigurationBuilder<?, ?> layer) {
       return this.layer(layer.build());
@@ -699,7 +702,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
     public B layersFromArray(@NonNull LayerConfiguration[] arrLayers) {
       innerConfigurations$value.addAll(List.of(arrLayers));
       innerConfigurations$set = true;
-      return (B) this;
+      return self();
     }
 
     /** Specify additional layer configurations */
@@ -707,7 +710,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
     public B layersFromList(@NonNull List<LayerConfiguration> listLayers) {
       innerConfigurations$value.addAll(listLayers);
       innerConfigurations$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -723,7 +726,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
         regularization$value.add(new L1Regularization(l1));
       }
       regularization$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -751,7 +754,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
         regularization$value.add(new L2Regularization(l2));
       }
       regularization$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -766,7 +769,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
         regularizationBias$value.add(new L1Regularization(l1Bias));
       }
       regularizationBias$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -791,7 +794,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
             "L2 bias regularization removed: incompatible with added WeightDecay regularization");
         regularizationBias$value.add(new L2Regularization(l2Bias));
       }
-      return (B) this;
+      return self();
     }
 
     /**
@@ -833,7 +836,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
         regularization$value.add(new WeightDecay(coefficient, applyLR));
       }
       regularization$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -870,7 +873,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
         regularizationBias$value.add(new WeightDecay(coefficient, applyLR));
       }
       regularization$set = true;
-      return (B) this;
+      return self();
     }
 
 
@@ -881,7 +884,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
      */
     @Deprecated
     public B list() {
-      return (B) this;
+      return self();
     }
 
     /**
@@ -897,19 +900,19 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
     public B weightInit(Distribution distribution) {
       this.weightInit$value = new WeightInitDistribution(distribution);
       this.weightInit$set = true;
-      return (B) this;
+      return self();
     }
     @JsonIgnore
     public B weightInit(WeightInit weightInit) {
       this.weightInit$value = weightInit.getWeightInitFunction();
       this.weightInit$set = true;
-      return (B) this;
+      return self();
     }
 
     public B weightInit(IWeightInit iWeightInit) {
       this.weightInit$value = iWeightInit;
       this.weightInit$set = true;
-      return (B) this;
+      return self();
     }
 
     /**
@@ -919,11 +922,11 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
      * @return
      */
     public B dist(@NonNull Distribution distribution) {
-      return (B) weightInit(distribution);
+      return weightInit(distribution);
     }
 
     public B dropOut(@NonNull IDropout dropout) {
-      return (B) idropOut(dropout);
+      return idropOut(dropout);
     }
 
     /**
@@ -933,7 +936,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
      * @return builder
      */
     public B dropOut(double dropout) {
-      return (B) idropOut(new Dropout(dropout));
+      return idropOut(new Dropout(dropout));
     }
 
     /**
@@ -946,7 +949,7 @@ public abstract class NeuralNetBaseBuilderConfiguration implements INeuralNetwor
     public B confs(@NonNull List<NeuralNetConfiguration> confs) {
       innerConfigurations$value.addAll(confs);
       innerConfigurations$set = true;
-      return (B) this;
+      return self();
     }
   }
 }

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/Convolution3D.java

@@ -38,6 +38,7 @@ import org.nd4j.linalg.api.buffer.DataType;
 import org.nd4j.linalg.api.ndarray.INDArray;
 
 @Data
+@NoArgsConstructor
 @ToString(callSuper = true)
 @EqualsAndHashCode(callSuper = true)
 @SuperBuilder(builderMethodName = "innerBuilder")

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/ConvolutionLayer.java

@@ -47,6 +47,7 @@ import org.nd4j.linalg.api.ndarray.INDArray;
  * size, the stride and padding The pooling layer takes the kernel size
  */
 @ToString(callSuper = true)
+@NoArgsConstructor
 @EqualsAndHashCode(callSuper = true)
 @SuperBuilder(builderMethodName = "innerBuilder")
 public class ConvolutionLayer extends FeedForwardLayer {
@@ -361,7 +362,7 @@ public class ConvolutionLayer extends FeedForwardLayer {
      * @param kernelSize kernel size
      */
     public B kernelSize(int... kernelSize) {
-      this.kernelSize$value = ValidationUtils.validate2NonNegative(kernelSize, false, "kernelSize");
+      this.kernelSize$value = ValidationUtils.validate3NonNegative(kernelSize,"kernelSize");
       this.kernelSize$set = true;
       return self();
     }
@@ -371,7 +372,7 @@ public class ConvolutionLayer extends FeedForwardLayer {
      * @param stride kernel size
      */
     public B stride(int... stride) {
-      this.stride$value = ValidationUtils.validate2NonNegative(stride, false, "stride");
+      this.stride$value = ValidationUtils.validate3NonNegative(stride,  "stride");
       this.stride$set = true;
       return self();
     }
@@ -382,7 +383,7 @@ public class ConvolutionLayer extends FeedForwardLayer {
      * @param padding kernel size
      */
     public B padding(int... padding) {
-      this.padding$value = ValidationUtils.validate2NonNegative(padding, false, "padding");
+      this.padding$value = ValidationUtils.validate3NonNegative(padding,  "padding");
       this.padding$set = true;
       return self();
     }
@@ -392,7 +393,7 @@ public class ConvolutionLayer extends FeedForwardLayer {
      * @param dilation kernel size
      */
     public B dilation(int... dilation) {
-      this.dilation$value = ValidationUtils.validate2NonNegative(dilation, false, "dilation");
+      this.dilation$value = ValidationUtils.validate3NonNegative(dilation, "dilation");
       this.dilation$set = true;
       return self();
     }

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/DenseLayer.java

@@ -38,6 +38,7 @@ import org.nd4j.linalg.api.ndarray.INDArray;
 
 /** Dense Layer Uses WeightInitXavier as default */
 @Data
+@NoArgsConstructor
 @ToString(callSuper = true)
 @EqualsAndHashCode(callSuper = true)
 @SuperBuilder

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/FeedForwardLayer.java

@@ -20,6 +20,7 @@
 
 package org.deeplearning4j.nn.conf.layers;
 
+import com.fasterxml.jackson.annotation.JsonIgnore;
 import lombok.*;
 import lombok.experimental.SuperBuilder;
 import org.deeplearning4j.nn.conf.DataFormat;
@@ -44,7 +45,7 @@ public abstract class FeedForwardLayer extends BaseLayerConfiguration {
      */
     @Getter
     protected long nIn;
-
+@JsonIgnore
     public void setNIn(int in) {
         this.nIn = in;
     }

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/LayerConfiguration.java

@@ -326,7 +326,7 @@ public abstract class LayerConfiguration
     log.warn("Calling getUpdater() in {} will always return no-Op Updater.", LayerConfiguration.class.getSimpleName());
     return Updater.NONE.getIUpdaterWithDefaultConfig();
   }
-  @Deprecated
+  @Deprecated @JsonIgnore
   public void setUpdater(Updater updater) {
     setUpdater(updater.getIUpdaterWithDefaultConfig());
   }

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/OutputLayer.java

@@ -35,6 +35,7 @@ import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.lossfunctions.LossFunctions;
 
 @Data
+@NoArgsConstructor
 @ToString(callSuper = true)
 @EqualsAndHashCode(callSuper = true)
 @SuperBuilder(builderMethodName = "innerBuilder")

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/ocnn/OCNNOutputLayer.java

@@ -48,7 +48,7 @@ public class OCNNOutputLayer extends BaseOutputLayer {
    * The hidden layer size for the one class neural network. Note this would be nOut on a dense
    * layer. NOut in this neural net is always set to 1 though.
    */
-  @Builder.Default @Getter private int hiddenLayerSize; // embedded hidden layer size aka "K"
+  @Getter private int hiddenLayerSize; // embedded hidden layer size aka "K"
   /** For nu definition see the paper */
   @Builder.Default @Getter private double nu = 0.04;
   /**