diff --git a/tensorflow/python/keras/engine/base_layer.py b/tensorflow/python/keras/engine/base_layer.py
index 4a43b0526f6..0eb6954d2a8 100644
--- a/tensorflow/python/keras/engine/base_layer.py
+++ b/tensorflow/python/keras/engine/base_layer.py
@@ -873,11 +873,6 @@ class Layer(module.Module, version_utils.LayerVersionSelector):
       # Priority 3a: `learning_phase()` has been set.
       elif backend.global_learning_phase_is_set():
         training_value = backend.learning_phase()
-      # Priority 3b: Pass the `learning_phase()` if in the Keras FuncGraph.
-      elif build_graph:
-        with backend.get_graph().as_default():
-          if base_layer_utils.is_in_keras_graph():
-            training_value = backend.learning_phase()
 
       if self._expects_training_arg and training_value is not None:
         # Force the training_value to be bool type which matches to the contract
@@ -1491,7 +1486,9 @@ class Layer(module.Module, version_utils.LayerVersionSelector):
           self._metrics.append(metric_obj)
         else:
           from tensorflow.python.keras import metrics as metrics_mod  # pylint:disable=g-import-not-at-top
-          metric_obj = metrics_mod.Mean(name=name, dtype=value.dtype)
+          # Build the metric object with the value's dtype if it defines one
+          metric_obj = metrics_mod.Mean(
+              name=name, dtype=getattr(value, 'dtype', None))
           self._metrics.append(metric_obj)
 
       if should_update_state: