Version 1; prepare Funktion geschrieben

.vscode/settings.json

@@ -0,0 +1,5 @@
+{
+    "files.associations": {
+        "unity.h": "c"
+    }
+}

neuralNetworkTests.c

@@ -8,8 +8,52 @@
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    FILE *file = fopen(path, "wb");
-}.
+    if (!fiile)
+    {
+     return;   
+    }
+
+    // Schreibe den Datei-Tag
+    const char tag = "info2_neural_network_file_format";
+    fwrite(tag, 1, strlen(tag), file);
+
+    // Überprüfe, ob es Layer gibt
+    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;
+
+    fwrite(&input,  sizeof(int), 1, file);
+    fwrite(&output, sizeof(int), 1, file);
+
+    // Schreibe die Layer-Daten
+    for (int i = 0; i < nn.numberOfLayers; i++)
+    {
+        const Layerlayer = &nn.layers[i];
+        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)
+        {
+            int nextOut = nn.layers[i + 1].weights.rows;
+            fwrite(&nextOut, sizeof(int), 1, file);
+        }
+    }
+
+    fclose(file);
+}
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)
 {