From a0233e5f6ace497b2551a8c87ea25d8261161c09 Mon Sep 17 00:00:00 2001
From: corentin <corentin.massala@gmail.com>
Date: Thu, 9 Nov 2023 22:27:11 +0100
Subject: [PATCH] comments

---
 mlp.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/mlp.py b/mlp.py
index c8822b9..1dde5c5 100644
--- a/mlp.py
+++ b/mlp.py
@@ -139,7 +139,7 @@ def run_mlp_training(data_train, labels_train, data_test, labels_test, d_h, lear
     d_in = data_train.shape[1]
     d_out = 10 #we can hard code it here or len(np.unique(label_train))
 
-    #Random initialisation of weights
+    #Random initialisation of weights Xavier initialisation
     w1 = np.random.randn(d_in, d_h) / np.sqrt(d_in)
     b1 = np.zeros((1, d_h))
     w2 = np.random.randn(d_h, d_out) / np.sqrt(d_h)
@@ -175,7 +175,7 @@ if __name__ == '__main__':
     X_train, X_test, y_train, y_test = read_cifar.split_dataset(data, labels, 0.9)
     d_in, d_h, d_out = 3072, 64, 10
     learning_rate = 0.1
-    num_epoch = 100
+    num_epoch = 300
 
     # #Initialisation 
     # w1 = np.random.randn(d_in, d_h) / np.sqrt(d_in)
-- 
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