We need to bring in the classes from advanced_activations if there are no custom objects specified. When no custom objects are specified, our module_objects/globals() in activations.deserialize() won't contain any advanced_activations.

tensorflow/python/keras/activations.py

@@ -26,6 +26,7 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import nn
 from tensorflow.python.util import dispatch
 from tensorflow.python.util.tf_export import keras_export
+from tensorflow.python.keras.layers import advanced_activations
 
 # b/123041942
 # In TF 2.x, if the `tf.nn.softmax` is used as an activation function in Keras
@@ -525,9 +526,18 @@ def deserialize(name, custom_objects=None):
       ValueError: `Unknown activation function` if the input string does not
       denote any defined Tensorflow activation function.
   """
+  globs = globals()
+
+  # only replace missing activations, when there are no custom objects
+  if custom_objects is None:
+    advanced_activations_globs = advanced_activations.get_globals()
+    for key,val in advanced_activations_globs.items():
+      if key not in globs:
+        globs[key] = val
+
   return deserialize_keras_object(
       name,
-      module_objects=globals(),
+      module_objects=globs,
       custom_objects=custom_objects,
       printable_module_name='activation function')
 

tensorflow/python/keras/activations_test.py

@@ -65,12 +65,19 @@ class KerasActivationsTest(test.TestCase, parameterized.TestCase):
     activation = advanced_activations.LeakyReLU(alpha=0.1)
     layer = core.Dense(3, activation=activation)
     config = serialization.serialize(layer)
+    # with custom objects
     deserialized_layer = serialization.deserialize(
         config, custom_objects={'LeakyReLU': activation})
     self.assertEqual(deserialized_layer.__class__.__name__,
                      layer.__class__.__name__)
     self.assertEqual(deserialized_layer.activation.__class__.__name__,
                      activation.__class__.__name__)
+    # without custom objects
+    deserialized_layer = serialization.deserialize(config)
+    self.assertEqual(deserialized_layer.__class__.__name__,
+                     layer.__class__.__name__)
+    self.assertEqual(deserialized_layer.activation.__class__.__name__,
+                     activation.__class__.__name__)
 
   def test_softmax(self):
     x = backend.placeholder(ndim=2)

tensorflow/python/keras/layers/advanced_activations.py

@@ -29,6 +29,8 @@ from tensorflow.python.keras.utils import tf_utils
 from tensorflow.python.ops import math_ops
 from tensorflow.python.util.tf_export import keras_export
 
+def get_globals():
+  return globals()
 
 @keras_export('keras.layers.LeakyReLU')
 class LeakyReLU(Layer):