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Test 4

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This commit is contained in:
Alexei Keller 2025-11-24 12:36:57 +01:00
parent fa26fbfb39
commit dd542429c9
1 changed files with 19 additions and 13 deletions
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32
neuralNetworkTests.c
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@ -8,24 +8,21 @@
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn) static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
{ {
FILE *file = fopen(path, "wb"); // TODO : Fehlerbehandlung
if (!file) // Öffne die Datei zum Schreiben im Binärmodus
{ FILE *file = fopen(path, "wb");
return; if (!file) return;
}
// Schreibe den Datei-Tag // 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); fwrite(tag, 1, strlen(tag), file);
// Überprüfe, ob es Layer gibt // Schreibe die Anzahl der Layer
if (nn.numberOfLayers == 0) if (nn.numberOfLayers == 0) {
{
fclose(file); fclose(file);
return; return;
} }
// Schreibe die Eingabe- und Ausgabegrößen des Netzwerks // Schreibe die Eingabe- und Ausgabegrößen des Netzwerks
int input = nn.layers[0].weights.cols; int input = nn.layers[0].weights.cols;
int output = nn.layers[0].weights.rows; 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 out = layer->weights.rows;
int in = layer->weights.cols; int in = layer->weights.cols;
fwrite(layer->weights.buffer, sizeof(MatrixType), out * in, file); fwrite(layer->weights.buffer, sizeof(MatrixType), out * in, file);
fwrite(layer->biases.buffer, sizeof(MatrixType), out * 1, file); fwrite(layer->biases.buffer, sizeof(MatrixType), out * 1, file);
if (i + 1 < nn.numberOfLayers) if (i + 1 < nn.numberOfLayers)
@ -54,6 +51,15 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
} }
fclose(file); 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) void test_loadModelReturnsCorrectNumberOfLayers(void)