Try a different initializer

src/gentun/models/tensorflow.py

@@ -166,13 +166,13 @@ def build_model(
         return Model(inputs=x_input, outputs=x, name=f"{self.name}")
 
     def reset_weights(self):
-        """Initialize model weights."""
+        """Initialize model weights using Xavier initializer."""
+        initializer = tf.keras.initializers.GlorotUniform()
         for layer in self.model.layers:
-            if hasattr(layer, "kernel_initializer") and hasattr(layer, "bias_initializer"):
-                layer.kernel.assign(layer.kernel_initializer(tf.shape(layer.kernel)))
-                layer.bias.assign(layer.bias_initializer(tf.shape(layer.bias)))
-            elif hasattr(layer, "kernel_initializer"):
-                layer.kernel.assign(layer.kernel_initializer(tf.shape(layer.kernel)))
+            if hasattr(layer, "kernel"):
+                layer.kernel.assign(initializer(tf.shape(layer.kernel)))
+            if hasattr(layer, "bias"):
+                layer.bias.assign(tf.zeros(tf.shape(layer.bias)))
 
     def create_train_evaluate(
         self, x_train: np.ndarray, y_train: np.ndarray, x_test: np.ndarray, y_test: np.ndarray