NeuralNetwork.tests.c eingefuegt

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silvana884 2025-11-26 10:31:46 +01:00
parent 74e7a21999
commit cc54d4e1dc

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@ -4,13 +4,47 @@
#include <math.h>
#include "unity.h"
#include "neuralNetwork.h"
//Dateischichten sind in neuralNetwork.h definiert
// Dateiname: __info2_neural_network_file_format__
static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
{
// TODO
FILE *file = fopen(path, "wb");
if (!file) return;
// Header schreiben
fwrite(FILE_HEADER_STRING, 1, strlen(FILE_HEADER_STRING), file);
// Anzahl Layer schreiben
uint32_t nLayers = nn.numberOfLayers;
fwrite(&nLayers, sizeof(uint32_t), 1, file);
for (uint32_t i = 0; i < nLayers; i++) {
Layer layer = nn.layers[i];
// Weights-Dimensionen
uint32_t rW = layer.weights.rows;
uint32_t cW = layer.weights.cols;
fwrite(&rW, sizeof(uint32_t), 1, file);
fwrite(&cW, sizeof(uint32_t), 1, file);
// Weights-Werte
fwrite(layer.weights.buffer, sizeof(MatrixType), rW * cW, file);
// Bias-Dimensionen
uint32_t rB = layer.biases.rows;
uint32_t cB = layer.biases.cols;
fwrite(&rB, sizeof(uint32_t), 1, file);
fwrite(&cB, sizeof(uint32_t), 1, file);
// Bias-Werte
fwrite(layer.biases.buffer, sizeof(MatrixType), rB * cB, file);
}
fclose(file);
}
void test_loadModelReturnsCorrectNumberOfLayers(void)
{
const char *path = "some__nn_test_file.info2";