Reverted changes

Author: ashutosh1919

tensorflow_addons/optimizers/conditional_gradient.py

@@ -86,7 +86,6 @@ def __init__(
                 compatibility, recommended to use `learning_rate` instead.
         """
         super().__init__(name=name, **kwargs)
-        self.__name__ = name
         self._set_hyper("learning_rate", kwargs.get("lr", learning_rate))
         self._set_hyper("lambda_", lambda_)
         self.epsilon = epsilon or tf.keras.backend.epsilon()

tensorflow_addons/optimizers/tests/conditional_gradient_test.py

@@ -21,7 +21,6 @@
 import tensorflow as tf
 from tensorflow_addons.utils import test_utils
 from tensorflow_addons.optimizers import conditional_gradient as cg_lib
-from tensorflow_addons.testing import serialization
 
 
 def _dtypes_to_test(use_gpu):
@@ -1469,4 +1468,4 @@ def test_serialization():
     )
     config = tf.keras.optimizers.serialize(optimizer)
     new_optimizer = tf.keras.optimizers.deserialize(config)
-    serialization.check_config(new_optimizer.get_config(), optimizer, False)
+    assert optimizer.get_config() == new_optimizer.get_config()

tensorflow_addons/testing/serialization.py

@@ -76,7 +76,7 @@ def check_config(config, class_, strict):
                     class_.__name__
                 )
             )
-        if parameter_name != "kwargs" and parameter_name not in config:
+        if parameter_name not in config:
             raise KeyError(
                 "The constructor parameter {} is not present in the config dict "
                 "obtained with `.get_config()` of {}. All parameters should be set to "