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Remove unusable arguments from dense network

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augustin64 2023-03-15 21:34:30 +01:00
parent ca06cbe088
commit bb0c709a50
2 changed files with 5 additions and 14 deletions
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2
src/dense/include/main.h
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@ -49,7 +49,7 @@ void* train_thread(void* parameters);
* nb_images_to_process: nombre d'images sur lesquelles entraîner le réseau (-1 si non utilisé)
* start: index auquel démarrer si nb_images_to_process est utilisé (0 si non utilisé)
*/
void train(int epochs, int layers, int neurons, char* recovery, char* image_file, char* label_file, char* out, char* delta, int nb_images_to_process, int start);
void train(int epochs, char* recovery, char* image_file, char* label_file, char* out, char* delta, int nb_images_to_process, int start);
/*
* Échange deux éléments d'un tableau

17
src/dense/main.c
View File

@ -63,8 +63,6 @@ void help(char* call) {
printf("OPTIONS:\n");
printf("\ttrain:\n");
printf("\t\t--epochs | -e [int]\tNombre d'époques (itérations sur tout le set de données).\n");
printf("\t\t--couches | -c [int]\tNombres de couches.\n");
printf("\t\t--neurones | -n [int]\tNombre de neurones sur la première couche.\n");
printf("\t\t--recover | -r [FILENAME]\tRécupérer depuis un modèle existant.\n");
printf("\t\t--images | -i [FILENAME]\tFichier contenant les images.\n");
printf("\t\t--labels | -l [FILENAME]\tFichier contenant les labels.\n");
@ -135,12 +133,14 @@ void* train_thread(void* parameters) {
}
void train(int epochs, int layers, int neurons, char* recovery, char* image_file, char* label_file, char* out, char* delta, int nb_images_to_process, int start) {
void train(int epochs, char* recovery, char* image_file, char* label_file, char* out, char* delta, int nb_images_to_process, int start) {
// Entraînement du réseau sur le set de données MNIST
Network* network;
Network* delta_network;
//int* repartition = malloc(sizeof(int)*layers);
int layers = 2;
int neurons = 784;
int nb_neurons_last_layer = 10;
int repartition[2] = {neurons, nb_neurons_last_layer};
@ -394,8 +394,6 @@ int main(int argc, char* argv[]) {
}
if (! strcmp(argv[1], "train")) {
int epochs = EPOCHS;
int layers = 2;
int neurons = 784;
int nb_images = -1;
int start = 0;
char* images = NULL;
@ -409,13 +407,6 @@ int main(int argc, char* argv[]) {
if ((! strcmp(argv[i], "--epochs"))||(! strcmp(argv[i], "-e"))) {
epochs = strtol(argv[i+1], NULL, 10);
i += 2;
} else
if ((! strcmp(argv[i], "--couches"))||(! strcmp(argv[i], "-c"))) {
layers = strtol(argv[i+1], NULL, 10);
i += 2;
} else if ((! strcmp(argv[i], "--neurones"))||(! strcmp(argv[i], "-n"))) {
neurons = strtol(argv[i+1], NULL, 10);
i += 2;
} else if ((! strcmp(argv[i], "--images"))||(! strcmp(argv[i], "-i"))) {
images = argv[i+1];
i += 2;
@ -455,7 +446,7 @@ int main(int argc, char* argv[]) {
out = "out.bin";
}
// Entraînement en sourçant neural_network.c
train(epochs, layers, neurons, recovery, images, labels, out, delta, nb_images, start);
train(epochs, recovery, images, labels, out, delta, nb_images, start);
return 0;
}
if (! strcmp(argv[1], "recognize")) {