diff --git a/src/cnn/cnn.c b/src/cnn/cnn.c
index 03daa07..7581005 100644
--- a/src/cnn/cnn.c
+++ b/src/cnn/cnn.c
@@ -6,6 +6,7 @@
 #include "include/initialisation.h"
 #include "include/function.h"
 #include "include/creation.h"
+#include "include/update.h"
 #include "include/make.h"
 
 #include "../include/colors.h"
@@ -130,85 +131,6 @@ void copy_input_to_input_z(float*** output, float*** output_a, int output_depth,
     }
 }
 
-void update_weights(Network* network) {
-    int n = network->size;
-    int input_depth, input_width, output_depth, output_width;
-    Kernel* k_i;
-    Kernel* k_i_1;
-    for (int i=0; i<(n-1); i++) {
-        k_i = network->kernel[i];
-        k_i_1 = network->kernel[i+1];
-        input_depth = network->depth[i];
-        input_width = network->width[i];
-        output_depth = network->depth[i+1];
-        output_width = network->width[i+1];
-
-        if (k_i->cnn) { // Convolution
-            Kernel_cnn* cnn = k_i_1->cnn;
-            int k_size = cnn->k_size;
-            for (int a=0; a<input_depth; a++) {
-                for (int b=0; b<output_depth; b++) {
-                    for (int c=0; c<k_size; c++) {
-                        for (int d=0; d<k_size; d++) {
-                            cnn->w[a][b][c][d] += cnn->d_w[a][b][c][d];
-                        }
-                    }
-                }
-            }
-        } else if (k_i->nn) { // Full connection
-            if (input_depth==1) { // Vecteur -> Vecteur
-                Kernel_nn* nn = k_i_1->nn;
-                for (int a=0; a<input_width; a++) {
-                    for (int b=0; b<output_width; b++) {
-                        nn->weights[a][b] += nn->d_weights[a][b];
-                    }
-                }
-            } else { // Matrice -> vecteur
-                Kernel_nn* nn = k_i_1->nn;
-                int input_size = input_width*input_width*input_depth;
-                for (int a=0; a<input_size; a++) {
-                    for (int b=0; b<output_width; b++) {
-                        nn->weights[a][b] += nn->d_weights[a][b];
-                    }
-                }
-            }
-        } else { // Pooling
-            (void)0; // Ne rien faire pour la couche pooling
-        }
-    }
-}
-
-void update_bias(Network* network) {
-    int n = network->size;
-    int output_width, output_depth;
-    Kernel* k_i;
-    Kernel* k_i_1;
-    for (int i=0; i<(n-1); i++) {
-        k_i = network->kernel[i];
-        k_i_1 = network->kernel[i+1];
-        output_width = network->width[i+1];
-        output_depth = network->depth[i+1];
-
-        if (k_i->cnn) { // Convolution
-            Kernel_cnn* cnn = k_i_1->cnn;
-            for (int a=0; a<output_depth; a++) {
-                for (int b=0; b<output_width; b++) {
-                    for (int c=0; c<output_width; c++) {
-                        cnn->bias[a][b][c] += cnn->d_bias[a][b][c];
-                    }
-                }
-            }
-        } else if (k_i->nn) { // Full connection
-            Kernel_nn* nn = k_i_1->nn;
-            for (int a=0; a<output_width; a++) {
-                nn->bias[a] += nn->d_bias[a];
-            }
-        } else { // Pooling
-            (void)0; // Ne rien faire pour la couche pooling
-        }
-    }
-}
-
 float compute_mean_squared_error(float* output, float* wanted_output, int len) {
     if (len==0) {
         printf("Erreur MSE: la longueur de la sortie est de 0 -> division par 0 impossible\n");
diff --git a/src/cnn/include/update.h b/src/cnn/include/update.h
new file mode 100644
index 0000000..345060f
--- /dev/null
+++ b/src/cnn/include/update.h
@@ -0,0 +1,26 @@
+#ifndef DEF_UPDATE_H
+#define DEF_UPDATE_H
+
+/*
+* Met à jours les poids à partir de données obtenus après plusieurs backpropagations
+* Puis met à 0 tous les d_weights
+*/
+void update_weights(Network* network);
+
+/*
+* Met à jours les biais à partir de données obtenus après plusieurs backpropagations
+* Puis met à 0 tous les d_bias
+*/
+void update_bias(Network* network);
+
+/*
+* Met à 0 toutes les données de backpropagation de poids
+*/
+void reset_d_weights(Network* network);
+
+/*
+* Met à 0 toutes les données de backpropagation de biais
+*/
+void reset_d_bias(Network* network);
+
+#endif
\ No newline at end of file
diff --git a/src/cnn/update.c b/src/cnn/update.c
new file mode 100644
index 0000000..aab9c8f
--- /dev/null
+++ b/src/cnn/update.c
@@ -0,0 +1,165 @@
+
+#include "update.h"
+
+void update_weights(Network* network) {
+    int n = network->size;
+    int input_depth, input_width, output_depth, output_width;
+    Kernel* k_i;
+    Kernel* k_i_1;
+    for (int i=0; i<(n-1); i++) {
+        k_i = network->kernel[i];
+        k_i_1 = network->kernel[i+1];
+        input_depth = network->depth[i];
+        input_width = network->width[i];
+        output_depth = network->depth[i+1];
+        output_width = network->width[i+1];
+
+        if (k_i->cnn) { // Convolution
+            Kernel_cnn* cnn = k_i_1->cnn;
+            int k_size = cnn->k_size;
+            for (int a=0; a<input_depth; a++) {
+                for (int b=0; b<output_depth; b++) {
+                    for (int c=0; c<k_size; c++) {
+                        for (int d=0; d<k_size; d++) {
+                            cnn->w[a][b][c][d] += cnn->d_w[a][b][c][d];
+                            cnn->d_w[a][b][c][d] = 0;
+                        }
+                    }
+                }
+            }
+        } else if (k_i->nn) { // Full connection
+            if (input_depth==1) { // Vecteur -> Vecteur
+                Kernel_nn* nn = k_i_1->nn;
+                for (int a=0; a<input_width; a++) {
+                    for (int b=0; b<output_width; b++) {
+                        nn->weights[a][b] += nn->d_weights[a][b];
+                        nn->d_weights[a][b] = 0;
+                    }
+                }
+            } else { // Matrice -> vecteur
+                Kernel_nn* nn = k_i_1->nn;
+                int input_size = input_width*input_width*input_depth;
+                for (int a=0; a<input_size; a++) {
+                    for (int b=0; b<output_width; b++) {
+                        nn->weights[a][b] += nn->d_weights[a][b];
+                        nn->d_weights[a][b] = 0;
+                    }
+                }
+            }
+        } else { // Pooling
+            (void)0; // Ne rien faire pour la couche pooling
+        }
+    }
+}
+
+void update_bias(Network* network) {
+    int n = network->size;
+    int output_width, output_depth;
+    Kernel* k_i;
+    Kernel* k_i_1;
+    for (int i=0; i<(n-1); i++) {
+        k_i = network->kernel[i];
+        k_i_1 = network->kernel[i+1];
+        output_width = network->width[i+1];
+        output_depth = network->depth[i+1];
+
+        if (k_i->cnn) { // Convolution
+            Kernel_cnn* cnn = k_i_1->cnn;
+            for (int a=0; a<output_depth; a++) {
+                for (int b=0; b<output_width; b++) {
+                    for (int c=0; c<output_width; c++) {
+                        cnn->bias[a][b][c] += cnn->d_bias[a][b][c];
+                        cnn->d_bias[a][b][c] = 0;
+                    }
+                }
+            }
+        } else if (k_i->nn) { // Full connection
+            Kernel_nn* nn = k_i_1->nn;
+            for (int a=0; a<output_width; a++) {
+                nn->bias[a] += nn->d_bias[a];
+                nn->d_bias[a] = 0;
+            }
+        } else { // Pooling
+            (void)0; // Ne rien faire pour la couche pooling
+        }
+    }
+}
+
+void reset_d_weights(Network* network) {
+    int n = network->size;
+    int input_depth, input_width, output_depth, output_width;
+    Kernel* k_i;
+    Kernel* k_i_1;
+    for (int i=0; i<(n-1); i++) {
+        k_i = network->kernel[i];
+        k_i_1 = network->kernel[i+1];
+        input_depth = network->depth[i];
+        input_width = network->width[i];
+        output_depth = network->depth[i+1];
+        output_width = network->width[i+1];
+
+        if (k_i->cnn) { // Convolution
+            Kernel_cnn* cnn = k_i_1->cnn;
+            int k_size = cnn->k_size;
+            for (int a=0; a<input_depth; a++) {
+                for (int b=0; b<output_depth; b++) {
+                    for (int c=0; c<k_size; c++) {
+                        for (int d=0; d<k_size; d++) {
+                            cnn->d_w[a][b][c][d] = 0;
+                        }
+                    }
+                }
+            }
+        } else if (k_i->nn) { // Full connection
+            if (input_depth==1) { // Vecteur -> Vecteur
+                Kernel_nn* nn = k_i_1->nn;
+                for (int a=0; a<input_width; a++) {
+                    for (int b=0; b<output_width; b++) {
+                        nn->d_weights[a][b] = 0;
+                    }
+                }
+            } else { // Matrice -> vecteur
+                Kernel_nn* nn = k_i_1->nn;
+                int input_size = input_width*input_width*input_depth;
+                for (int a=0; a<input_size; a++) {
+                    for (int b=0; b<output_width; b++) {
+                        nn->d_weights[a][b] = 0;
+                    }
+                }
+            }
+        } else { // Pooling
+            (void)0; // Ne rien faire pour la couche pooling
+        }
+    }
+}
+
+void reset_d_bias(Network* network) {
+    int n = network->size;
+    int output_width, output_depth;
+    Kernel* k_i;
+    Kernel* k_i_1;
+    for (int i=0; i<(n-1); i++) {
+        k_i = network->kernel[i];
+        k_i_1 = network->kernel[i+1];
+        output_width = network->width[i+1];
+        output_depth = network->depth[i+1];
+
+        if (k_i->cnn) { // Convolution
+            Kernel_cnn* cnn = k_i_1->cnn;
+            for (int a=0; a<output_depth; a++) {
+                for (int b=0; b<output_width; b++) {
+                    for (int c=0; c<output_width; c++) {
+                        cnn->d_bias[a][b][c] = 0;
+                    }
+                }
+            }
+        } else if (k_i->nn) { // Full connection
+            Kernel_nn* nn = k_i_1->nn;
+            for (int a=0; a<output_width; a++) {
+                nn->d_bias[a] = 0;
+            }
+        } else { // Pooling
+            (void)0; // Ne rien faire pour la couche pooling
+        }
+    }
+}
\ No newline at end of file