diff --git a/tensorflow/python/keras/engine/training.py b/tensorflow/python/keras/engine/training.py
index 5567e1733a7..682c0272da5 100644
--- a/tensorflow/python/keras/engine/training.py
+++ b/tensorflow/python/keras/engine/training.py
@@ -324,10 +324,10 @@ class Model(base_layer.Layer, version_utils.ModelVersionSelector):
       super(Model, self).__setattr__(name, value)
       return
 
-    if all(
-        isinstance(v, (base_layer.Layer,
-                       data_structures.TrackableDataStructure)) or
-        trackable_layer_utils.has_weights(v) for v in nest.flatten(value)):
+    if any(
+        isinstance(v, (base_layer.Layer, data_structures.TrackableDataStructure
+                      )) or trackable_layer_utils.has_weights(v)
+        for v in nest.flatten(value)):
       try:
         self._base_model_initialized
       except AttributeError:
diff --git a/tensorflow/python/keras/engine/training_test.py b/tensorflow/python/keras/engine/training_test.py
index 5cf15926bfb..63943f4f720 100644
--- a/tensorflow/python/keras/engine/training_test.py
+++ b/tensorflow/python/keras/engine/training_test.py
@@ -3383,6 +3383,18 @@ class TestTrainingWithMetrics(keras_parameterized.TestCase):
     self.assertEqual([m.name for m in outer_model.metrics],
                      ['loss', 'acc2', 'mean', 'mean1', 'mean2'])
 
+  def test_subclassed_model_with_empty_list_attr(self):
+
+    class ModelSubclass(training_module.Model):
+
+      def __init__(self):
+        self.empty_list = []
+        inputs = layers_module.Input(shape=())
+        outputs = inputs + 1
+        super(ModelSubclass, self).__init__(inputs, outputs)
+
+    ModelSubclass()  # empty_list attr assignment should not raise
+
 
 class BareUpdateLayer(layers_module.Layer):