Add print files (non tested)

This commit is contained in:
julienChemillier 2022-11-01 18:06:52 +01:00
parent caffef3477
commit 59a536aad7
2 changed files with 155 additions and 0 deletions

32
src/cnn/include/print.h Normal file
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#ifndef DEF_PRINT_H
#define DEF_PRINT_H
#include "include/struct.h"
/*
* Affiche le kernel d'une couche de convolution
*/
void print_kernel_cnn(Kernel_cnn* k, int depth_input, int dim_input, int depth_output, int dim_output);
/*
* Affiche une couche de pooling
*/
void print_pooling(int size);
/*
* Affiche le kernel d'une couche de fully connected
*/
void print_kernel_nn(Kernel_nn* k, int size_input, int size_output);
/*
* Affiche une couche d'input
*/
void print_input(float*** input, int depth, int dim);
/*
* Affiche un cnn. Plus précisément:
* input, kernel_cnn, kernel_nn, pooling
*/
void print_cnn(Network* network);
#endif

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src/cnn/print.c Normal file
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#include <stdio.h>
#include "include/print.h"
#define print_bar printf("---------------------------\n")
#define print_space printf("\n")
#define print_dspace printf("\n\n")
#define print_tspace printf("\n\n\n")
#define green printf("\033[0;31m")
#define red printf("\033[0;32m")
#define blue printf("\033[0;34m")
#define purple printf("\033[0;35m")
#define reset_color printf("\033[0m")
void print_kernel_cnn(Kernel_cnn* k, int depth_input, int dim_input, int depth_output, int dim_output) {
int k_size = dim_input - dim_output + 1;
// print bias
green;
for (int i=0; i<depth_output; i++) {
for (int j=0; j<dim_output; j++) {
for (int k=0; k<dim_output; k++) {
printf("%.2f", k->bias[i][j][k]);
}
print_space;
}
print_dspace;
}
print_dspace;
reset_color;
//print weights
red;
for (int i=0; i<; i++) {
printf("------Line %d-----\n", i);
for (int j=0; j<; j++) {
for (int k=0; k<; k++) {
for (int l=0; l<; l++) {
printf("%.2f", k->w[i][j][k][l]);
}
print_space;
}
print_dspace;
}
print_dspace;
}
reset_color;
print_dspace;
}
void print_pooling(int size) {
print_bar;
purple;
printf("-------Pooling %dx%d-------\n", size ,size);
reset_color;
print_bar;
print_dspace;
}
void print_kernel_nn(Kernel_nn* k, int size_input, int size_output) {
// print bias
green;
for (int i=0; i<size_output; i++) {
printf("%.2f ", k->bias[i]);
}
print_dspace;
reset_color;
//print weights
red;
for (int i=0; i<size_output; i++) {
for (int j=0; j<size_input; j++) {
printf("%.2f ", k->weights[j][i]);
}
print_space;
}
reset_color;
print_dspace;
}
void print_input(float*** input, int depth, int dim) {
print_bar;
print_bar;
blue;
for (int i=0; i<depth; i++) {
for (int j=0; j<dim; j++) {
for (int k=0; k<dim; k++) {
printf("%.2f ", input[i][j][k]);
}
print_space;
}
print_dspace;
}
reset_color;
print_dspace;
}
void print_cnn(Network* network) {
int n = network->size;
int input_depth, input_width, output_depth, output_width;
Kernel* k_i;
for (int i=0; i<(n-1); i++) {
input = network->input[i];
input_depth = network->depth[i];
input_width = network->width[i];
output = network->input[i+1];
output_depth = network->depth[i+1];
output_width = network->width[i+1];
k_i = network->kernel[i];
print_input(input, input_depth, input_width);
if (k_i->cnn) { // Convolution
print_kernel_cnn(k_i->cnn, input_depth, input_width, output_depth, output_width);
}
else if (k_i->nn) { // Full connection
print_kernel_nn(k_i->nn, input_width, output_width);
}
else { // Pooling
print_pooling(input_width - output_width +1);
}
}
print_input(input[n-1], network->depth[n-1], network->width[n-1]);
}