Replace unnecessary `()` in `run_in_graph_and_eager_modes()`.

PiperOrigin-RevId: 201652888

2 files changed, 13 insertions, 13 deletions

diff --git a/tensorflow/contrib/optimizer_v2/checkpointable_utils_test.py b/tensorflow/contrib/optimizer_v2/checkpointable_utils_test.py
index 64b95786b5..b6972a7a45 100644
--- a/tensorflow/contrib/optimizer_v2/checkpointable_utils_test.py
+++ b/tensorflow/contrib/optimizer_v2/checkpointable_utils_test.py
@@ -226,7 +226,7 @@ class CheckpointingTests(test.TestCase):
             optimizer_node.slot_variables[0]
             .slot_variable_node_id].attributes[0].checkpoint_key)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testSaveRestore(self):
     model = MyModel()
     optimizer = adam.AdamOptimizer(0.001)
@@ -347,7 +347,7 @@ class CheckpointingTests(test.TestCase):
             self.assertEqual(training_continuation + 1,
                              session.run(root.save_counter))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testAgnosticUsage(self):
     """Graph/eager agnostic usage."""
     # Does create garbage when executing eagerly due to ops.Graph() creation.
@@ -381,7 +381,7 @@ class CheckpointingTests(test.TestCase):
                          self.evaluate(root.save_counter))
 
   # pylint: disable=cell-var-from-loop
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testWithDefun(self):
     num_training_steps = 2
     checkpoint_directory = self.get_temp_dir()
@@ -453,7 +453,7 @@ class CheckpointingTests(test.TestCase):
         optimizer.apply_gradients(
             [(g, v) for g, v in zip(grad, model.vars)])
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDeferredSlotRestoration(self):
     checkpoint_directory = self.get_temp_dir()
 
@@ -616,7 +616,7 @@ class CheckpointingTests(test.TestCase):
 
 class TemplateTests(test.TestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def test_checkpointable_save_restore(self):
 
     def _templated():
@@ -712,7 +712,7 @@ class CheckpointCompatibilityTests(test.TestCase):
             sess=session, save_path=checkpoint_prefix,
             global_step=root.optimizer_step)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testLoadFromNameBasedSaver(self):
     """Save a name-based checkpoint, load it using the object-based API."""
     with test_util.device(use_gpu=True):
diff --git a/tensorflow/contrib/optimizer_v2/optimizer_v2_test.py b/tensorflow/contrib/optimizer_v2/optimizer_v2_test.py
index 8599af32f6..ec033c4a01 100644
--- a/tensorflow/contrib/optimizer_v2/optimizer_v2_test.py
+++ b/tensorflow/contrib/optimizer_v2/optimizer_v2_test.py
@@ -35,7 +35,7 @@ from tensorflow.python.platform import test
 
 class OptimizerTest(test.TestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testBasic(self):
     for i, dtype in enumerate([dtypes.half, dtypes.float32, dtypes.float64]):
       # Note that we name the variables uniquely here since the variables don't
@@ -113,7 +113,7 @@ class OptimizerTest(test.TestCase):
         self.assertAllClose([3.0 - 3 * 3 * 42.0, 4.0 - 3 * 3 * (-42.0)],
                             var1.eval())
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNoVariables(self):
     for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
       # pylint: disable=cell-var-from-loop
@@ -128,7 +128,7 @@ class OptimizerTest(test.TestCase):
       with self.assertRaisesRegexp(ValueError, 'No.*variables'):
         sgd_op.minimize(loss)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNoGradients(self):
     for i, dtype in enumerate([dtypes.half, dtypes.float32, dtypes.float64]):
       # Note that we name the variables uniquely here since the variables don't
@@ -146,7 +146,7 @@ class OptimizerTest(test.TestCase):
         # var1 has no gradient
         sgd_op.minimize(loss, var_list=[var1])
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNoGradientsForAnyVariables_Minimize(self):
     for i, dtype in enumerate([dtypes.half, dtypes.float32, dtypes.float64]):
       # Note that we name the variables uniquely here since the variables don't
@@ -162,7 +162,7 @@ class OptimizerTest(test.TestCase):
                                    'No gradients provided for any variable'):
         sgd_op.minimize(loss, var_list=[var0, var1])
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNoGradientsForAnyVariables_ApplyGradients(self):
     for i, dtype in enumerate([dtypes.half, dtypes.float32, dtypes.float64]):
       # Note that we name the variables uniquely here since the variables don't
@@ -176,7 +176,7 @@ class OptimizerTest(test.TestCase):
                                    'No gradients provided for any variable'):
         sgd_op.apply_gradients([(None, var0), (None, var1)])
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testGradientsAsVariables(self):
     for i, dtype in enumerate([dtypes.half, dtypes.float32, dtypes.float64]):
       # Note that we name the variables uniquely here since the variables don't
@@ -216,7 +216,7 @@ class OptimizerTest(test.TestCase):
       self.assertAllClose([-14., -13.], self.evaluate(var0))
       self.assertAllClose([-6., -5.], self.evaluate(var1))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testComputeGradientsWithTensors(self):
     x = ops.convert_to_tensor(1.0)
     def f():