From b21ac2367380b4549b0f243d2e12197911a4b1b0 Mon Sep 17 00:00:00 2001
From: julienChemillier <chemillier.julien@gmail.com>
Date: Fri, 4 Nov 2022 12:02:00 +0100
Subject: [PATCH] Add of the dropout feature

---
 src/cnn/cnn.c         | 17 +++++++++++++++++
 src/cnn/include/cnn.h |  5 +++++
 2 files changed, 22 insertions(+)

diff --git a/src/cnn/cnn.c b/src/cnn/cnn.c
index 19f7b35..ade10ea 100644
--- a/src/cnn/cnn.c
+++ b/src/cnn/cnn.c
@@ -57,6 +57,12 @@ void forward_propagation(Network* network) {
         output_width = network->width[i+1];
         activation = k_i->activation;
 
+        if (k_i->nn) {
+            drop_neurones(input, 1, 1, input_width, network->dropout);
+        } else {
+            drop_neurones(input, input_depth, input_width, input_width, network->dropout);
+        }
+
         if (k_i->cnn) { // Convolution
             make_convolution(k_i->cnn, input, output, output_width);
             copy_input_to_input_z(output, output_a, output_depth, output_width, output_width);
@@ -125,6 +131,17 @@ void backward_propagation(Network* network, float wanted_number) {
     free(wanted_output);
 }
 
+void drop_neurones(float*** input, int depth, int dim1, int dim2, int dropout) {
+    for (int i=0; i<depth; i++) {
+        for (int j=0; j<dim1; j++) {
+            for (int k=0; k<dim2; k++) {
+                if (will_be_drop(dropout))
+                    input[i][j][k] = 0;
+            }
+        }
+    }
+}
+
 void copy_input_to_input_z(float*** output, float*** output_a, int output_depth, int output_rows, int output_columns) {
     for (int i=0; i<output_depth; i++) {
         for (int j=0; j<output_rows; j++) {
diff --git a/src/cnn/include/cnn.h b/src/cnn/include/cnn.h
index 72b7f33..d7dfa08 100644
--- a/src/cnn/include/cnn.h
+++ b/src/cnn/include/cnn.h
@@ -24,6 +24,11 @@ void forward_propagation(Network* network);
 */
 void backward_propagation(Network* network, float wanted_number);
 
+/*
+* Met à 0 chaque valeur de l'input avec une probabilité de dropout %
+*/
+void drop_neurones(float*** input, int depth, int dim1, int dim2, int dropout);
+
 /*
 * Copie les données de output dans output_a (Sachant que les deux matrices ont les mêmes dimensions)
 */