Fix: use add_weight instead of tf.Variable in training loop guide

Author: Aaraviitkgp

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",