B4J Question Neural network error

[claudiob4]

Hi all
I'm testing a neural network in Java. Unfortunately the compilation gives me a class not found error and I can't solve the problem. Can anyone help me?


Error:

Waiting for debugger to connect...
Program started.
Error occurred on line: 43 (Main)
java.lang.ClassNotFoundException: org.deeplearning4j$nn$conf$NeuralNetConfiguration$Builder
at anywheresoftware.b4j.object.JavaObject.getCorrectClassName(JavaObject.java:289)
at anywheresoftware.b4j.object.JavaObject.InitializeNewInstance(JavaObject.java:84)
at b4j.example.main._initializeneuralnetconfiguration(main.java:122)
at b4j.example.main._appstart(main.java:79)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at anywheresoftware.b4a.shell.Shell.runMethod(Shell.java:629)
at anywheresoftware.b4a.shell.Shell.raiseEventImpl(Shell.java:237)
at anywheresoftware.b4a.shell.Shell.raiseEvent(Shell.java:167)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at anywheresoftware.b4a.BA.raiseEvent2(BA.java:109)
at anywheresoftware.b4a.shell.ShellBA.raiseEvent2(ShellBA.java:98)
at anywheresoftware.b4a.BA.raiseEvent(BA.java:96)
at b4j.example.main.start(main.java:38)
at javafx.graphics/com.sun.javafx.application.LauncherImpl.lambda$launchApplication1$9(LauncherImpl.java:846)
at javafx.graphics/com.sun.javafx.application.PlatformImpl.lambda$runAndWait$12(PlatformImpl.java:455)
at javafx.graphics/com.sun.javafx.application.PlatformImpl.lambda$runLater$10(PlatformImpl.java:428)
at java.base/java.security.AccessController.doPrivileged(Native Method)
at javafx.graphics/com.sun.javafx.application.PlatformImpl.lambda$runLater$11(PlatformImpl.java:427)
at javafx.graphics/com.sun.glass.ui.InvokeLaterDispatcher$Future.run(InvokeLaterDispatcher.java:96)
at javafx.graphics/com.sun.glass.ui.win.WinApplication._runLoop(Native Method)
at javafx.graphics/com.sun.glass.ui.win.WinApplication.lambda$runLoop$3(WinApplication.java:174)
at java.base/java.lang.Thread.run(Thread.java:834)

#Region Project Attributes
    #MainFormWidth: 600
    #MainFormHeight: 600
#End Region

#AdditionalJar: deeplearning4j-core-1.0.0-M2.1.jar
#AdditionalJar: nd4j-native-platform-1.0.0-M2.1.jar
#AdditionalJar: slf4j-api-2.1.0-alpha1.jar
#AdditionalJar: slf4j-simple-2.1.0-alpha1.jar

Sub Process_Globals
    Private fx As JFX
    Private MainForm As Form
End Sub

Sub AppStart (Form1 As Form, Args() As String)
    MainForm = Form1
    MainForm.Show

    ' Costruzione della configurazione della rete neurale
    Dim nnConf As JavaObject
    nnConf = InitializeNeuralNetConfiguration
    If nnConf.IsInitialized Then
        Log("Neural network configuration initialized successfully")
    Else
        Log("Failed to initialize neural network configuration")
    End If

    ' Creazione del modello
    Dim model As JavaObject
    model.InitializeNewInstance("org.deeplearning4j.nn.multilayer.MultiLayerNetwork", Array(nnConf))
    model.RunMethod("init", Null)

    ' Stampa del sommario del modello
    Log(model.RunMethod("summary", Null))

    ' Esempio di addestramento con dati fittizi
    TrainModel(model)
End Sub

Sub InitializeNeuralNetConfiguration As JavaObject
    Dim nnConf As JavaObject
    nnConf.InitializeNewInstance("org.deeplearning4j.nn.conf.NeuralNetConfiguration$Builder", Null)
    nnConf = nnConf.RunMethod("seed", Array(12345)) ' Seed per la randomizzazione dei pesi
    nnConf = nnConf.RunMethod("updater", Array(CreateUpdater("adam"))) ' Ottimizzatore Adam
    nnConf = nnConf.RunMethod("list", Null)
    nnConf = nnConf.RunMethod("layer", Array(0, CreateDenseLayer(8, 26, "relu"))) ' Primo layer
    nnConf = nnConf.RunMethod("layer", Array(1, CreateDenseLayer(26, 26, "relu"))) ' Secondo layer
    nnConf = nnConf.RunMethod("layer", Array(2, CreateDenseLayer(26, 26, "relu"))) ' Terzo layer
    nnConf = nnConf.RunMethod("layer", Array(3, CreateDenseLayer(26, 8, "relu"))) ' Quarto layer
    nnConf = nnConf.RunMethod("layer", Array(4, CreateOutputLayer(8, 8, "softmax"))) ' Output layer
    nnConf = nnConf.RunMethod("build", Null)
    Return nnConf
End Sub

Sub CreateDenseLayer(numInput As Int, numOutput As Int, activation As String) As JavaObject
    Dim denseLayerBuilder As JavaObject
    denseLayerBuilder.InitializeNewInstance("org.deeplearning4j.nn.conf.layers.DenseLayer$Builder", Null)
    denseLayerBuilder = denseLayerBuilder.RunMethod("nIn", Array(numInput))
    denseLayerBuilder = denseLayerBuilder.RunMethod("nOut", Array(numOutput))
    denseLayerBuilder = denseLayerBuilder.RunMethod("activation", Array(activation))
    denseLayerBuilder = denseLayerBuilder.RunMethod("weightInit", Array("xavier"))
    Return denseLayerBuilder.RunMethod("build", Null)
End Sub

Sub CreateOutputLayer(numInput As Int, numOutput As Int, activation As String) As JavaObject
    Dim outputLayerBuilder As JavaObject
    outputLayerBuilder.InitializeNewInstance("org.deeplearning4j.nn.conf.layers.OutputLayer$Builder", Null)
    outputLayerBuilder = outputLayerBuilder.RunMethod("nIn", Array(numInput))
    outputLayerBuilder = outputLayerBuilder.RunMethod("nOut", Array(numOutput))
    outputLayerBuilder = outputLayerBuilder.RunMethod("activation", Array(activation))
    outputLayerBuilder = outputLayerBuilder.RunMethod("weightInit", Array("xavier"))
    outputLayerBuilder = outputLayerBuilder.RunMethod("lossFunction", Array("negativeloglikelihood"))
    Return outputLayerBuilder.RunMethod("build", Null)
End Sub

Sub CreateUpdater(updaterType As String) As JavaObject
    Dim updater As JavaObject
    updater.InitializeStatic("org.nd4j.linalg.learning.config." & updaterType.SubString2(0,1).ToUpperCase & updaterType.SubString(1).ToLowerCase)
    Return updater
End Sub

Sub TrainModel(model As JavaObject)
    ' Esempio di dati fittizi per l'addestramento
    Dim features(,) As Double = Array(Array(1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), Array(0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0))
    Dim labels(,) As Double = Array(Array(1.0, 0.0), Array(0.0, 1.0))
    
    ' Creazione delle matrici di input e output
    Dim Nd4j As JavaObject
    Nd4j.InitializeStatic("org.nd4j.linalg.factory.Nd4j")
    Dim input As JavaObject = Nd4j.RunMethod("create", Array(features))
    Dim output As JavaObject = Nd4j.RunMethod("create", Array(labels))
    
    ' Addestramento del modello
    For i = 1 To 1000
        model.RunMethod("fit", Array(input, output))
    Next
    
    ' Predizione con il modello addestrato
    Dim prediction As JavaObject = model.RunMethod("output", Array(input))
    Log("Predictions: " & prediction)
End Sub

Sub MainForm_CloseRequest (EventData As Event)
    MainForm.Close
End Sub

 

[Daestrum]

think you are missing some additional jars

I can get past your class not found - but hit a problem later

these are the jars I am using in #AdditionalJar

    #AdditionalJar: deeplearning4j-core-1.0.0-M2.1.jar
    #AdditionalJar: nd4j-native-platform-1.0.0-M2.jar
    #AdditionalJar: deeplearning4j-nn-1.0.0-M2.1.jar
    #AdditionalJar: nd4j-api-1.0.0-M2.1.jar

 

[Daestrum]

The list got a bit bgger so far - just chasing more and more errors

    #AdditionalJar: deeplearning4j-core-1.0.0-M2.1.jar
    #AdditionalJar: deeplearning4j-nn-1.0.0-M2.1.jar
    #AdditionalJar: nd4j-api-1.0.0-M2.1.jar
    #additionaljar: javacpp-1.5.10.jar
    #AdditionalJar: slf4j-simple-2.0.13.jar
    #AdditionalJar: slf4j-api-2.0.13.jar
    #AdditionalJar: nd4j-native-platform-1.0.0-M2.1.jar
    #AdditionalJar: nd4j-common-1.0.0-M2.1.jar

now getting "Caused by: java.lang.RuntimeException: org.nd4j.linalg.factory.Nd4jBackend$NoAvailableBackendException: Please ensure that you have an nd4j backend on your classpath.

 

[claudiob4]

Thanks Daestro. Now I try to add these .jars

 

[Daestrum]

This is my current list

    #AdditionalJar: deeplearning4j-core-1.0.0-M2.1.jar
    #AdditionalJar: deeplearning4j-nn-1.0.0-M2.1.jar
    #AdditionalJar: nd4j-api-1.0.0-M2.1.jar
    #additionaljar: javacpp-1.5.10.jar
    #AdditionalJar: slf4j-simple-2.0.13.jar
    #AdditionalJar: slf4j-api-2.0.13.jar
    #AdditionalJar: nd4j-native-platform-1.0.0-M2.1.jar
    #AdditionalJar: nd4j-common-1.0.0-M2.1.jar
    #AdditionalJar: nd4j-x86-0.4-rc3.8.jar
    #AdditionalJar: nd4j-native-api-1.0.0-M2.1.jar
    #AdditionalJar: jblas-1.2.5.jar
    #AdditionalJar: deeplearning4j-datavec-iterators-1.0.0-M2.1.jar
    #AdditionalJar: commons-io-2.16.1.jar
    #AdditionalJar: openblas-platform-0.3.26-1.5.10.jar

The error now is it cant find a backend