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https://github.com/augustin64/projet-tipe
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Update cnn neuron_io
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@ -20,7 +20,7 @@ void write_network(char* filename, Network* network);
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/*
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* Écrit une couche dans le fichier spécifié par le pointeur ptr
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*/
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void write_couche(Kernel* kernel, int type_couche, FILE* ptr);
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void write_couche(Network* network, int indice_couche, int type_couche, FILE* ptr);
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// Lecture d'un réseau neuronal
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@ -33,5 +33,5 @@ Network* read_network(char* filename);
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/*
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* Lit une kernel dans le fichier spécifié par le pointeur ptr
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*/
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Kernel* read_kernel(int type_couche, FILE* ptr);
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Kernel* read_kernel(int type_couche, int output_dim, FILE* ptr);
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#endif
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@ -47,17 +47,19 @@ void write_network(char* filename, Network* network) {
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// Écriture du pré-corps et corps
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for (int i=0; i < size; i++) {
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write_couche(network->kernel[i], type_couche[i], ptr);
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write_couche(network, i, type_couche[i], ptr);
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}
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fclose(ptr);
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}
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void write_couche(Kernel* kernel, int type_couche, FILE* ptr) {
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void write_couche(Network* network, int indice_couche, int type_couche, FILE* ptr) {
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Kernel* kernel = network->kernel[indice_couche];
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int indice_buffer = 0;
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if (type_couche == 0) { // Cas du CNN
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Kernel_cnn* cnn = kernel->cnn;
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int output_dim = network->width[indice_couche];
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// Écriture du pré-corps
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uint32_t pre_buffer[4];
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@ -68,11 +70,12 @@ void write_couche(Kernel* kernel, int type_couche, FILE* ptr) {
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fwrite(pre_buffer, sizeof(pre_buffer), 1, ptr);
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// Écriture du corps
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float buffer[cnn->k_size*cnn->k_size*cnn->columns*(cnn->rows+1)];
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float buffer[cnn->columns*(cnn->k_size*cnn->k_size*cnn->rows+output_dim*output_dim)];
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for (int i=0; i < cnn->columns; i++) {
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for (int j=0; j < cnn->k_size; j++) {
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for (int k=0; k < cnn->k_size; k++) {
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for (int j=0; j < output_dim; j++) {
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for (int k=0; k < output_dim; k++) {
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printf("%f\n", cnn->bias[i][j][k]);
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bufferAdd(cnn->bias[i][j][k]);
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}
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}
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@ -166,7 +169,7 @@ Network* read_network(char* filename) {
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network->kernel = (Kernel**)malloc(sizeof(Kernel*)*size);
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for (int i=0; i < (int)size; i++) {
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network->kernel[i] = read_kernel(type_couche[i], ptr);
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network->kernel[i] = read_kernel(type_couche[i], network->width[i], ptr);
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}
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network->input = (float****)malloc(sizeof(float***)*size);
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@ -187,7 +190,7 @@ Network* read_network(char* filename) {
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return network;
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}
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Kernel* read_kernel(int type_couche, FILE* ptr) {
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Kernel* read_kernel(int type_couche, int output_dim, FILE* ptr) {
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Kernel* kernel = (Kernel*)malloc(sizeof(Kernel));
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if (type_couche == 0) { // Cas du CNN
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// Lecture du "Pré-corps"
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@ -209,12 +212,12 @@ Kernel* read_kernel(int type_couche, FILE* ptr) {
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cnn->bias = (float***)malloc(sizeof(float**)*cnn->columns);
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cnn->d_bias = (float***)malloc(sizeof(float**)*cnn->columns);
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for (int i=0; i < cnn->columns; i++) {
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cnn->bias[i] = (float**)malloc(sizeof(float*)*cnn->k_size);
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cnn->d_bias[i] = (float**)malloc(sizeof(float*)*cnn->k_size);
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for (int j=0; j < cnn->k_size; j++) {
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cnn->bias[i][j] = (float*)malloc(sizeof(float)*cnn->k_size);
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cnn->d_bias[i][j] = (float*)malloc(sizeof(float)*cnn->k_size);
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for (int k=0; k < cnn->k_size; k++) {
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cnn->bias[i] = (float**)malloc(sizeof(float*)*output_dim);
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cnn->d_bias[i] = (float**)malloc(sizeof(float*)*output_dim);
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for (int j=0; j < output_dim; j++) {
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cnn->bias[i][j] = (float*)malloc(sizeof(float)*output_dim);
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cnn->d_bias[i][j] = (float*)malloc(sizeof(float)*output_dim);
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for (int k=0; k < output_dim; k++) {
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fread(&tmp, sizeof(tmp), 1, ptr);
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cnn->bias[i][j][k] = tmp;
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cnn->d_bias[i][j][k] = 0.;
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