From 7cef2272b7987f4b3432888435b925d0481adeb8 Mon Sep 17 00:00:00 2001 From: Aaraviitkgp Date: Sat, 26 Jul 2025 16:00:04 +0530 Subject: [PATCH 1/2] Fix: use add_weight instead of tf.Variable in training loop guide --- site/en/guide/basic_training_loops.ipynb | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/site/en/guide/basic_training_loops.ipynb b/site/en/guide/basic_training_loops.ipynb index a1558b1903e..ba0e92bbac0 100644 --- a/site/en/guide/basic_training_loops.ipynb +++ b/site/en/guide/basic_training_loops.ipynb @@ -212,8 +212,9 @@ " super().__init__(**kwargs)\n", " # Initialize the weights to `5.0` and the bias to `0.0`\n", " # In practice, these should be randomly initialized\n", - " self.w = tf.Variable(5.0)\n", - " self.b = tf.Variable(0.0)\n", + " self.w = self.add_weight(name='w', shape=(), initializer=tf.constant_initializer(5.0))\n", + " self.b = self.add_weight(name='b', shape=(), initializer=tf.constant_initializer(0.0))\n", + " # Use add_weight so Keras can track this as a trainable weight\n", "\n", " def __call__(self, x):\n", " return self.w * x + self.b\n", From 795b07712bdd7f1e6eb73aa1895fb986ab287475 Mon Sep 17 00:00:00 2001 From: Aaraviitkgp Date: Sat, 26 Jul 2025 16:03:35 +0530 Subject: [PATCH 2/2] Fix: use add_weight instead of tf.Variable in training loop guide --- site/en/guide/basic_training_loops.ipynb | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/site/en/guide/basic_training_loops.ipynb b/site/en/guide/basic_training_loops.ipynb index a1558b1903e..e0ef412e421 100644 --- a/site/en/guide/basic_training_loops.ipynb +++ b/site/en/guide/basic_training_loops.ipynb @@ -212,8 +212,10 @@ " super().__init__(**kwargs)\n", " # Initialize the weights to `5.0` and the bias to `0.0`\n", " # In practice, these should be randomly initialized\n", - " self.w = tf.Variable(5.0)\n", - " self.b = tf.Variable(0.0)\n", + " self.w = self.add_weight(name='w', shape=(), initializer=tf.constant_initializer(5.0))\n", + " self.b = self.add_weight(name='b', shape=(), initializer=tf.constant_initializer(0.0))\n", + "\n", + " # Use add_weight so Keras can track this as a trainable weight\n", "\n", " def __call__(self, x):\n", " return self.w * x + self.b\n",