Automated rollback of commit 209c7da. Revert tensorflow#22478.

PiperOrigin-RevId: 222489301

tensorflow/python/keras/integration_test.py

@@ -26,7 +26,6 @@
 from tensorflow.python.layers import core as tf_core_layers
 from tensorflow.python.ops import nn
 from tensorflow.python.ops import rnn_cell
-from tensorflow.python.ops import variable_scope
 from tensorflow.python.platform import test
 
 
@@ -313,15 +312,6 @@ def test_using_tf_layers_in_keras_functional_model(self):
                           verbose=0)
       self.assertGreater(history.history['val_acc'][-1], 0.7)
 
-  def test_regularizers_with_get_variable(self):
-    # Test case for GitHub issue 22470.
-    with self.cached_session():
-      v = variable_scope.get_variable(
-          'v',
-          shape=[4, 4],
-          initializer=keras.initializers.glorot_uniform(),
-          regularizer=keras.regularizers.l2(0.))
-
 
 if __name__ == '__main__':
   test.main()

tensorflow/python/keras/regularizers.py

@@ -20,7 +20,6 @@
 
 import six
 
-from tensorflow.python.framework import ops
 from tensorflow.python.keras import backend as K
 from tensorflow.python.keras.utils.generic_utils import deserialize_keras_object
 from tensorflow.python.keras.utils.generic_utils import serialize_keras_object
@@ -55,14 +54,12 @@ def __init__(self, l1=0., l2=0.):  # pylint: disable=redefined-outer-name
     self.l2 = K.cast_to_floatx(l2)
 
   def __call__(self, x):
-    if self.l1 or self.l2:
-      regularization = ops.convert_to_tensor(0., dtype=K.floatx())
-      if self.l1:
-        regularization += math_ops.reduce_sum(self.l1 * math_ops.abs(x))
-      if self.l2:
-        regularization += math_ops.reduce_sum(self.l2 * math_ops.square(x))
-      return regularization
-    return None
+    regularization = 0.
+    if self.l1:
+      regularization += math_ops.reduce_sum(self.l1 * math_ops.abs(x))
+    if self.l2:
+      regularization += math_ops.reduce_sum(self.l2 * math_ops.square(x))
+    return regularization
 
   def get_config(self):
     return {'l1': float(self.l1), 'l2': float(self.l2)}