mirror of
https://github.com/augustin64/projet-tipe
synced 2025-03-13 22:35:21 +01:00
106 lines
3.2 KiB
C
106 lines
3.2 KiB
C
#include <stdlib.h>
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#include <stdio.h>
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#include "include/free.h"
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void free_a_cube_input_layer(Network* network, int pos, int depth, int dim) {
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for (int i=0; i < depth; i++) {
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for (int j=0; j < dim; j++) {
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free(network->input[pos][i][j]);
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}
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free(network->input[pos][i]);
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}
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free(network->input[pos]);
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}
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void free_a_line_input_layer(Network* network, int pos) {
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free(network->input[pos][0][0]);
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free(network->input[pos][0]);
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free(network->input[pos]);
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}
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void free_average_pooling(Network* network, int pos) {
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free_a_cube_input_layer(network, pos, network->depth[pos-1], network->width[pos-1]/2);
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}
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void free_average_pooling_flatten(Network* network, int pos) {
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free_a_line_input_layer(network, pos);
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}
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void free_convolution(Network* network, int pos) {
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int c = network->kernel[pos]->cnn->columns;
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int k_size = network->kernel[pos]->cnn->k_size;
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int r = network->kernel[pos]->cnn->rows;
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free_a_cube_input_layer(network, pos, c, network->width[pos-1] - 2*(k_size/2));
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for (int i=0; i < c; i++) {
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for (int j=0; j < k_size; j++) {
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free(network->kernel[pos]->cnn->bias[i][j]);
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free(network->kernel[pos]->cnn->d_bias[i][j]);
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}
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free(network->kernel[pos]->cnn->bias[i]);
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free(network->kernel[pos]->cnn->d_bias[i]);
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}
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free(network->kernel[pos]->cnn->bias);
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free(network->kernel[pos]->cnn->d_bias);
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for (int i=0; i < r; i++) {
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for (int j=0; j < c; j++) {
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for (int k=0; k < k_size; k++) {
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free(network->kernel[pos]->cnn->w[i][j][k]);
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free(network->kernel[pos]->cnn->d_w[i][j][k]);
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}
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free(network->kernel[pos]->cnn->w[i][j]);
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free(network->kernel[pos]->cnn->d_w[i][j]);
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}
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free(network->kernel[pos]->cnn->w[i]);
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free(network->kernel[pos]->cnn->d_w[i]);
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}
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free(network->kernel[pos]->cnn->w);
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free(network->kernel[pos]->cnn->d_w);
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free(network->kernel[pos]->cnn);
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}
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void free_dense(Network* network, int pos) {
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free_a_line_input_layer(network, pos);
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int dim = network->kernel[pos]->nn->output_units;
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for (int i=0; i < dim; i++) {
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free(network->kernel[pos]->nn->weights[i]);
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free(network->kernel[pos]->nn->d_weights[i]);
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}
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free(network->kernel[pos]->nn->weights);
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free(network->kernel[pos]->nn->d_weights);
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free(network->kernel[pos]->nn->bias);
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free(network->kernel[pos]->nn->d_bias);
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free(network->kernel[pos]->nn);
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}
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void free_network_creation(Network* network) {
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free_a_cube_input_layer(network, 0, network->depth[0], network->width[0]);
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for (int i=0; i < network->max_size; i++) {
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free(network->dim[i]);
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}
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free(network->dim);
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free(network->kernel);
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free(network->input);
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free(network);
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}
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void free_network_lenet5(Network* network) {
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free_dense(network, 6);
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free_dense(network, 5);
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free_dense(network, 4);
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free_average_pooling_flatten(network, 3);
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free_convolution(network, 2);
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free_average_pooling(network, 1);
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free_convolution(network, 0);
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free_network_creation(network);
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if (network->size != network->max_size) {
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printf("Attention, le réseau LeNet5 n'est pas complet");
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}
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}
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