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neuralNetworkTests.c

@@ -9,19 +9,19 @@
 
 static void writeWeights(Layer layer, FILE *file)
 {
-    unsigned int n = (unsigned int)layer.weights.rows * layer.weights.cols; //col und row müssen nicht extra eingelesen werden, da loadModel die Dimensionen aus der Fkt loadModel() selbst liest
+    unsigned int n = (unsigned int)layer.weights.rows * layer.weights.cols; //col und row müssen nicht extra eingelesen werden, da loadModel die Dimensionen selbst aus der Datei liest
     fwrite(layer.weights.buffer, sizeof(MatrixType), n, file);
 }
 
 static void writeBiases(Layer layer, FILE *file)
 {
-    unsigned int n = (unsigned int)layer.weights.rows * layer.weights.cols;
-    fwrite(layer.biases.buffer, sizeof(float ), n, file);
+    unsigned int n = (unsigned int)layer.biases.rows * layer.biases.cols;
+    fwrite(layer.biases.buffer, sizeof(MatrixType), n, file);
 }
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-//file erstellen und zum binärschreiben öffnen
+    //file erstellen und zum Binärschreiben öffnen
     FILE *file = fopen(path, "wb");
     if(file == NULL)
         return;
@@ -41,19 +41,19 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
     unsigned int inputDim = (unsigned int)nn.layers[0].weights.cols;
     fwrite(&inputDim, sizeof(unsigned int), 1, file);
 
-    //für jede Schicht: Dimension, Gewichte und Biases einlesen
+    //für jede Schicht: Dimension, Gewichte und Biases schreiben
     for (unsigned int i = 0; i < nn.numberOfLayers; i++)
     {
         Layer layer = nn.layers[i];
    
-        int outputDim = (unsigned int)layer.weights.rows;
+        unsigned int outputDim = (unsigned int)layer.weights.rows;
         fwrite(&outputDim, sizeof(unsigned int), 1, file);
    
-        //dimensionen festlegen(weights)  
+        //Weight-Matrixwerte schreiben
         writeWeights(layer, file);
     
 
-        //dimension festlegen(bias)
+        //Bias-Vektorwerte schreiben
         writeBiases(layer, file);