kegelmannni100026/Neuronale-Netzwerke
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This commit is contained in:
Sara Stark 2025-11-17 13:49:29 +01:00
parent c84c6d3929
commit 0406b66173
2 changed files with 7 additions and 7 deletions
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4
neuralNetwork.c
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@ -128,8 +128,8 @@ NeuralNetwork loadModel(const char *path)
{
if(checkFileHeader(file))
{
unsigned int inputDimension = readDimension(file);
unsigned int outputDimension = readDimension(file);
unsigned int inputDimension = readDimension(file); // übergabe in neuralnetworktests
unsigned int outputDimension = readDimension(file); // übergabe in neuralnetworktests
while(inputDimension > 0 && outputDimension > 0)
{

10
neuralNetworkTests.c
View File

@ -19,8 +19,8 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
for (unsigned int i = 0; i < nn.numberOfLayers; ++i)
{
const Layer *lay = &nn.layers[i];
int inputDim = (int)lay->weights.cols;
int outputDim = (int)lay->weights.rows;
int inputDim = (int)lay->weights.cols; // Die Anzahl der Spalten der Gewichtsmatrix ist immer gleich der Input-Dimension
int outputDim = (int)lay->weights.rows; // Anzahl der Reihen der Gewichtsmatrix ist immer gleich der Output-Dimension
// --- Spezifische Dimensions-Schreiblogik (Spiegelung der Leselogik) ---
if (i == 0) {
@ -37,9 +37,9 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
// --- Matrizen-Daten schreiben ---
// Schreibe Gewichtsmatrix (Daten):
size_t weightCount = (size_t)lay->weights.rows * (size_t)lay->weights.cols; //size_t unsignierter ganzzahltyp
if (weightCount > 0 && lay->weights.buffer != NULL) {
// Schreibe alle MatrixType-Elemente (z.B. floats) der Gewichte.
size_t weightCount = (size_t)lay->weights.rows * (size_t)lay->weights.cols; // Gesamtanzahl der Elemente in der Gewichtsmatrix berechnet (rows x cols) //size_t unsignierter ganzzahltyp
if (weightCount > 0 && lay->weights.buffer != NULL) { //Prüfung ob dimensionen > 0 & Datenpuffer existiert
// Schreibe alle MatrixType-Elemente (z.B. floats) der Gewichte, Anzahl usw.
fwrite(lay->weights.buffer, sizeof(MatrixType), weightCount, file);
}