From 86359bb37f2a255b27c7b9376c4ce0eb71032ffd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Bj=C3=B6rn?= Date: Mon, 17 Nov 2025 18:30:06 +0100 Subject: [PATCH 1/3] =?UTF-8?q?matrix=20vollst=C3=A4ndig?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- matrix.c | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/matrix.c b/matrix.c index a0e2ccf..4474836 100644 --- a/matrix.c +++ b/matrix.c @@ -8,19 +8,19 @@ Matrix createMatrix(unsigned int rows, unsigned int cols) { Matrix matrix; - matrix.rows = rows; - matrix.cols = cols; + matrix.rows = 0; + matrix.cols = 0; + matrix.buffer = NULL; - if (rows == 0 || cols == 0) { - matrix.buffer = NULL; - return matrix; - } - - matrix.buffer = (MatrixType *)malloc(rows * cols * sizeof(MatrixType)); - if (matrix.buffer == NULL) + // Wenn die Dimensionen gültig sind, Speicher reservieren + if (rows > 0 && cols > 0) { - matrix.rows = 0; - matrix.cols = 0; + matrix.buffer = (MatrixType *)malloc(rows * cols * sizeof(MatrixType)); + if (matrix.buffer != NULL) + { + matrix.rows = rows; + matrix.cols = cols; + } } return matrix; } From 8c2ed38abf22f4f15b631662e624ec82e04dfe33 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Bj=C3=B6rn?= Date: Mon, 17 Nov 2025 20:19:35 +0100 Subject: [PATCH 2/3] NNTest nur noch predict-Fehler --- matrix.c | 3 ++- matrix.h | 3 ++- neuralNetworkTests.c | 42 +++++++++++++++++++++++++++++++++++++++++- 3 files changed, 45 insertions(+), 3 deletions(-) diff --git a/matrix.c b/matrix.c index 4474836..253d848 100644 --- a/matrix.c +++ b/matrix.c @@ -8,9 +8,10 @@ Matrix createMatrix(unsigned int rows, unsigned int cols) { Matrix matrix; + matrix.buffer = NULL; matrix.rows = 0; matrix.cols = 0; - matrix.buffer = NULL; + // Wenn die Dimensionen gültig sind, Speicher reservieren if (rows > 0 && cols > 0) diff --git a/matrix.h b/matrix.h index c85e38c..02202c5 100644 --- a/matrix.h +++ b/matrix.h @@ -8,9 +8,10 @@ typedef float MatrixType; // TODO Matrixtyp definieren typedef struct { + MatrixType *buffer; unsigned int rows; unsigned int cols; - MatrixType *buffer; + } Matrix; diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c index 21ab370..8335c87 100644 --- a/neuralNetworkTests.c +++ b/neuralNetworkTests.c @@ -8,7 +8,47 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) { - // TODO + // TODO : Fehlerbehandlung + FILE *file = fopen(path, "wb"); + if (!file) { + perror("Fehler beim Öffnen der Datei"); + return; + } + + const char *header = "__info2_neural_network_file_format__"; + fwrite(header, sizeof(char), strlen(header), file); + + for (unsigned int i = 0; i < nn.numberOfLayers; i++) { + Layer layer = nn.layers[i]; + + unsigned int inputDim = (i == 0) ? layer.weights.cols : 0; // nur beim ersten Layer + unsigned int outputDim = layer.weights.rows; + + if (i == 0) { + // erstes Layer: inputDim und outputDim schreiben + fwrite(&inputDim, sizeof(unsigned int), 1, file); + fwrite(&outputDim, sizeof(unsigned int), 1, file); + } else { + // nur outputDim für weitere Layer + fwrite(&outputDim, sizeof(unsigned int), 1, file); + } + + fwrite(layer.weights.buffer, sizeof(MatrixType), layer.weights.rows * layer.weights.cols, file); + fwrite(layer.biases.buffer, sizeof(MatrixType), layer.biases.rows * layer.biases.cols, file); + } + + unsigned int zero = 0; + fwrite(&zero, sizeof(unsigned int), 1, file); + fclose(file); + + // Debug + 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) From 934ba2d06e8f959b4ebacc5ea4113d2b0a34f586 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Bj=C3=B6rn?= Date: Mon, 17 Nov 2025 23:02:54 +0100 Subject: [PATCH 3/3] NeuralNetworkTest fertig? --- neuralNetworkTests.c | 55 ++++++++++++++++++++++++++------------------ 1 file changed, 33 insertions(+), 22 deletions(-) diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c index 8335c87..66731e0 100644 --- a/neuralNetworkTests.c +++ b/neuralNetworkTests.c @@ -9,39 +9,50 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) { // TODO : Fehlerbehandlung + // Öffne die Datei zum Schreiben im Binärmodus FILE *file = fopen(path, "wb"); - if (!file) { - perror("Fehler beim Öffnen der Datei"); + if (!file) return; + + // Schreibe den Datei-Tag + const char *tag = "__info2_neural_network_file_format__"; + fwrite(tag, 1, strlen(tag), file); + + // Schreibe die Anzahl der Layer + if (nn.numberOfLayers == 0) { + fclose(file); return; - } + } - const char *header = "__info2_neural_network_file_format__"; - fwrite(header, sizeof(char), strlen(header), file); + // Schreibe die Eingabe- und Ausgabegrößen des Netzwerks + int input = nn.layers[0].weights.cols; + int output = nn.layers[0].weights.rows; - for (unsigned int i = 0; i < nn.numberOfLayers; i++) { - Layer layer = nn.layers[i]; + fwrite(&input, sizeof(int), 1, file); + fwrite(&output, sizeof(int), 1, file); - unsigned int inputDim = (i == 0) ? layer.weights.cols : 0; // nur beim ersten Layer - unsigned int outputDim = layer.weights.rows; + // Schreibe die Layer-Daten + for (int i = 0; i < nn.numberOfLayers; i++) + { + const Layer *layer = &nn.layers[i]; + int out = layer->weights.rows; + int in = layer->weights.cols; - if (i == 0) { - // erstes Layer: inputDim und outputDim schreiben - fwrite(&inputDim, sizeof(unsigned int), 1, file); - fwrite(&outputDim, sizeof(unsigned int), 1, file); - } else { - // nur outputDim für weitere Layer - fwrite(&outputDim, sizeof(unsigned int), 1, file); + + 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); } - - fwrite(layer.weights.buffer, sizeof(MatrixType), layer.weights.rows * layer.weights.cols, file); - fwrite(layer.biases.buffer, sizeof(MatrixType), layer.biases.rows * layer.biases.cols, file); } - unsigned int zero = 0; - fwrite(&zero, sizeof(unsigned int), 1, file); fclose(file); - // Debug + // 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];