From 6963e15557b6da8d69af54692dfed8c6559d4ddf Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lilli=20K=C3=BChnemund?=
 <kuehnemundli103965@th-nuernberg.de>
Date: Wed, 4 Nov 2026 09:31:59 +0100
Subject: [PATCH] Implement neural network file preparation

---
 Startcode/neuralNetworkTests.c | 56 ++++++++++++++++++++++++++++++++++
 1 file changed, 56 insertions(+)

diff --git a/Startcode/neuralNetworkTests.c b/Startcode/neuralNetworkTests.c
index 21ab370..bd6f0ed 100644
--- a/Startcode/neuralNetworkTests.c
+++ b/Startcode/neuralNetworkTests.c
@@ -9,6 +9,62 @@
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
     // TODO
+	// 1. Datei Öffnen
+	FILE *file = fopen(path, "wb")
+
+	// überprüfen ob das öffnen funktioniert hat
+	if (file == NULL)
+	{
+		return;
+	}
+
+	// 2. Datei-Header schreiben (Überschrifft bzw. Stempel was in der Datei steht)
+	const char *fileTag = "__info2_neural_network_file_format__";
+	fwrite(fileTag, sizeof(char), strlen(fileTag), file);
+
+	// 3. Eingabe- und Ausgabedimension bestimmen
+	int inputDimension = nn.layers[0].weights.cols;
+	int outputDimension = nn.layers[0].weights.rows;
+	// in unser File speichern
+	fwrite(&inputDimension, sizeof(int), 1, file);
+	fwrite(&outputDimension, sizeof(int), 1, file);
+
+	for(unsigned int i = 0; i < nn.numberOfLayers; i++)
+	{
+		// Speichern der aktuellen Speicheradresse
+		const Layer *layer = &nn.layers[i];
+
+		// Gewichtsmatrix des aktuellen Layers in die Datei speichern
+		fwrite
+		(
+    		layer->weights.buffer,
+    		sizeof(MatrixType),
+    		layer->weights.rows * layer->weights.cols,
+    		file
+		);
+
+		//Bias-Matrix
+		fwrite
+		(
+    		layer->biases.buffer,
+    		sizeof(MatrixType),
+    		layer->biases.rows * layer->biases.cols,
+    		file
+		);
+
+		//
+		if (i + 1 < nn.numberOfLayers)
+		{
+    		outputDimension = nn.layers[i + 1].weights.rows;
+		}
+		else
+		{
+    		outputDimension = 0;
+		}
+		fwrite(&outputDimension, sizeof(int), 1, file);
+	}
+
+	fclose(file);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)