diff --git a/tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py b/tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py
index 646fcd9..fe89728 100644
--- a/tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py
+++ b/tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py
@@ -319,6 +319,8 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
   )
   def testNoneGradients(self, cls, num_microbatches, expected_answer):
     """Tests that optimizers can handle variables whose gradients are None."""
+    del expected_answer  # Unused.
+
     with self.cached_session() as sess:
       var0 = tf.Variable([1.0, 2.0])
       data0 = tf.Variable([[3.0, 4.0], [5.0, 6.0], [7.0, 8.0], [-1.0, 0.0]])
@@ -338,7 +340,7 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
           loss=self._loss(data0, var0), var_list=[var0, extra_variable])
       sess.run(minimize_op)
 
-  def _testWriteOutAndReload(self, optimizer_cls):
+  def _test_write_out_and_reload(self, optimizer_cls):
     optimizer = optimizer_cls(
         l2_norm_clip=1.0, noise_multiplier=0.01, num_microbatches=1)
 
@@ -365,12 +367,12 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
   def testWriteOutAndReloadAdam(self):
     optimizer_class = dp_optimizer.make_gaussian_optimizer_class(
         tf.keras.optimizers.Adam)
-    self._testWriteOutAndReload(optimizer_class)
+    self._test_write_out_and_reload(optimizer_class)
 
   def testWriteOutAndReloadSGD(self):
     optimizer_class = dp_optimizer.make_gaussian_optimizer_class(
         tf.keras.optimizers.SGD)
-    self._testWriteOutAndReload(optimizer_class)
+    self._test_write_out_and_reload(optimizer_class)
 
 
 if __name__ == '__main__':