From dd542429c955b96a91a845d304c4af23f59e7b81 Mon Sep 17 00:00:00 2001
From: Alexei <kelleral99467@th-nuernberg.de>
Date: Mon, 24 Nov 2025 12:36:57 +0100
Subject: [PATCH] Test 4

---
 neuralNetworkTests.c | 32 +++++++++++++++++++-------------
 1 file changed, 19 insertions(+), 13 deletions(-)

diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c
index 1c6b33a..66731e0 100644
--- a/neuralNetworkTests.c
+++ b/neuralNetworkTests.c
@@ -8,24 +8,21 @@
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    FILE *file = fopen(path, "wb");
-    if (!file)
-    {
-     return;   
-    }
+    // TODO : Fehlerbehandlung
+    // Öffne die Datei zum Schreiben im Binärmodus
+  FILE *file = fopen(path, "wb");
+    if (!file) return;
 
     // Schreibe den Datei-Tag
-    const char *tag = "info2_neural_network_file_format";
+    const char *tag = "__info2_neural_network_file_format__";
     fwrite(tag, 1, strlen(tag), file);
 
-    // Überprüfe, ob es Layer gibt
-    if (nn.numberOfLayers == 0) 
-    {
+    // Schreibe die Anzahl der Layer
+    if (nn.numberOfLayers == 0) {
         fclose(file);
         return;
-    }
+    }  
 
-    
     // Schreibe die Eingabe- und Ausgabegrößen des Netzwerks
     int input  = nn.layers[0].weights.cols;
     int output = nn.layers[0].weights.rows;
@@ -40,10 +37,10 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
         int out = layer->weights.rows;
         int in  = layer->weights.cols;
 
-
+        
         fwrite(layer->weights.buffer, sizeof(MatrixType), out * in, file);
 
-
+        
         fwrite(layer->biases.buffer, sizeof(MatrixType), out * 1, file);
 
         if (i + 1 < nn.numberOfLayers)
@@ -54,6 +51,15 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
     }
 
     fclose(file);
+
+    // Debuging-Ausgabe
+    printf("prepareNeuralNetworkFile: Datei '%s' erstellt mit %u Layer(n)\n", path, nn.numberOfLayers);
+    for (unsigned int i = 0; i < nn.numberOfLayers; i++) {
+        Layer layer = nn.layers[i];
+        printf("Layer %u: weights (%u x %u), biases (%u x %u)\n", 
+               i, layer.weights.rows, layer.weights.cols, layer.biases.rows, layer.biases.cols);
+    }
+
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)