tipe/src/cnn/function.c

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#include <stdio.h>
#include <math.h>
#include <float.h>
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#include "../include/colors.h"
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#include "include/function.h"
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#define BOUND_RELU 15
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float identity(float x) {
return x;
}
float identity_derivative(float x) {
(void)x;
return 1;
}
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float sigmoid(float x) {
return 1/(1 + exp(-x));
}
float sigmoid_derivative(float x) {
float tmp = exp(-x);
return tmp/((1+tmp)*(1+tmp));
}
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float relu(float x) {
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return fmaxf(0, fminf(x, BOUND_RELU));
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}
float relu_derivative(float x) {
if (x > 0)
return 1;
return 0;
}
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float leaky_relu(float x) {
if (x>0)
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return fminf(x, BOUND_RELU);
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return x*LEAKER;
}
float leaky_relu_derivative(float x) {
if (x > 0)
return 1;
return LEAKER;
}
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float tanh_(float x) {
return tanh(x);
}
float tanh_derivative(float x) {
float a = tanh(x);
return 1 - a*a;
}
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void apply_softmax_input(float ***input, int depth, int rows, int columns) {
float m = FLT_MIN;
float sum=0;
for (int i=0; i < depth; i++) {
for (int j=0; j < rows; j++) {
for (int k=0; k < columns; k++) {
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m = fmaxf(m, input[i][j][k]);
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}
}
}
for (int i=0; i < depth; i++) {
for (int j=0; j < rows; j++) {
for (int k=0; k < columns; k++) {
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input[i][j][k] = exp(m-input[i][j][k]);
sum += input[i][j][k];
}
}
}
for (int i=0; i < depth; i++) {
for (int j=0; j < rows; j++) {
for (int k=0; k < columns; k++) {
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input[i][j][k] = input[i][j][k]/sum;
}
}
}
}
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void apply_function_input(float (*f)(float), float*** input, int depth, int rows, int columns) {
for (int i=0; i < depth; i++) {
for (int j=0; j < rows; j++) {
for (int k=0; k < columns; k++) {
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input[i][j][k] = (*f)(input[i][j][k]);
}
}
}
}
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void apply_function_to_matrix(int activation, float*** input, int depth, int dim) {
if (activation == SOFTMAX) {
return apply_softmax_input(input, depth, dim, dim);
}
if (activation > 1) { // Exclude negative values (derivative) and 1 (identity)
ptr f = get_activation_function(activation);
return apply_function_input(f, input, depth, dim, dim);
}
printf_error("fonction d'activation inconnue (apply_function_to_matrix): ");
printf("%d\n", activation);
}
void apply_function_to_vector(int activation, float*** input, int dim) {
if (activation == SOFTMAX) {
return apply_softmax_input(input, 1, 1, dim);
}
if (activation > 1) { // Exclude negative values (derivative) and 1 (identity)
ptr f = get_activation_function(activation);
return apply_function_input(f, input, 1, 1, dim);
}
printf_error("fonction d'activation inconnue (apply_function_to_vector): ");
printf("%d\n", activation);
}
ptr get_activation_function(int activation) {
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if (activation == RELU) {
return &relu;
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}
if (activation == -RELU) {
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return &relu_derivative;
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}
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if (activation == IDENTITY) {
return &identity;
}
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if (activation == -IDENTITY) {
return &identity_derivative;
}
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if (activation == SIGMOID) {
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return &sigmoid;
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}
if (activation == -SIGMOID) {
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return &sigmoid_derivative;
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}
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if (activation == SOFTMAX) {
printf_error("impossible de renvoyer la fonction softmax\n");
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return NULL;
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}
if (activation == -SOFTMAX) {
printf_error("impossible de renvoyer la dérivée de la fonction softmax\n");
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return NULL;
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}
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if (activation == TANH) {
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return &tanh_;
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}
if (activation == -TANH) {
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return &tanh_derivative;
}
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if (activation == LEAKY_RELU) {
return &leaky_relu;
}
if (activation == -LEAKY_RELU) {
return &leaky_relu_derivative;
}
printf_error("fonction d'activation inconnue (get_activation_function): ");
printf("%d\n", activation);
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return NULL;
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}