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

PiperOrigin-RevId: 201652888

2 files changed, 26 insertions, 26 deletions

diff --git a/tensorflow/python/layers/base_test.py b/tensorflow/python/layers/base_test.py
index fcacc8d603..298e96e711 100644
--- a/tensorflow/python/layers/base_test.py
+++ b/tensorflow/python/layers/base_test.py
@@ -39,7 +39,7 @@ from tensorflow.python.platform import test
 
 class BaseLayerTest(test.TestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testLayerProperties(self):
     layer = base_layers.Layer(name='my_layer')
     self.assertEqual(layer.variables, [])
@@ -53,13 +53,13 @@ class BaseLayerTest(test.TestCase):
     layer = base_layers.Layer(name='my_layer', trainable=False)
     self.assertEqual(layer.trainable, False)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testInt64Layer(self):
     layer = base_layers.Layer(name='my_layer', dtype='int64')
     layer.add_variable('my_var', [2, 2])
     self.assertEqual(layer.name, 'my_layer')
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testAddWeight(self):
     layer = base_layers.Layer(name='my_layer')
 
@@ -116,7 +116,7 @@ class BaseLayerTest(test.TestCase):
       with self.assertRaisesRegexp(ValueError, 'activity_regularizer'):
         core_layers.Dense(1, activity_regularizer=lambda *args, **kwargs: 0.)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testCall(self):
 
     class MyLayer(base_layers.Layer):
@@ -132,7 +132,7 @@ class BaseLayerTest(test.TestCase):
       # op is only supported in GRAPH mode
       self.assertEqual(outputs.op.name, 'my_layer/Square')
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDeepCopy(self):
 
     class MyLayer(base_layers.Layer):
@@ -155,7 +155,7 @@ class BaseLayerTest(test.TestCase):
     self.assertEqual(layer_copy._graph, layer._graph)
     self.assertEqual(layer_copy._private_tensor, layer._private_tensor)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testScopeNaming(self):
 
     class PrivateLayer(base_layers.Layer):
@@ -203,7 +203,7 @@ class BaseLayerTest(test.TestCase):
       my_layer_scoped1.apply(inputs)
       self.assertEqual(my_layer_scoped1._scope.name, 'var_scope/my_layer_1')
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testInputSpecNdimCheck(self):
 
     class CustomerLayer(base_layers.Layer):
@@ -230,7 +230,7 @@ class BaseLayerTest(test.TestCase):
     layer = CustomerLayer()
     layer.apply(constant_op.constant([[1], [2]]))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testInputSpecMinNdimCheck(self):
 
     class CustomerLayer(base_layers.Layer):
@@ -258,7 +258,7 @@ class BaseLayerTest(test.TestCase):
     layer = CustomerLayer()
     layer.apply(constant_op.constant([[[1], [2]]]))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testInputSpecMaxNdimCheck(self):
 
     class CustomerLayer(base_layers.Layer):
@@ -286,7 +286,7 @@ class BaseLayerTest(test.TestCase):
     layer = CustomerLayer()
     layer.apply(constant_op.constant([[1], [2]]))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testInputSpecDtypeCheck(self):
 
     class CustomerLayer(base_layers.Layer):
@@ -306,7 +306,7 @@ class BaseLayerTest(test.TestCase):
     layer = CustomerLayer()
     layer.apply(constant_op.constant(1.0, dtype=dtypes.float32))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testInputSpecAxesCheck(self):
 
     class CustomerLayer(base_layers.Layer):
@@ -328,7 +328,7 @@ class BaseLayerTest(test.TestCase):
     layer = CustomerLayer()
     layer.apply(constant_op.constant([[1, 2], [3, 4], [5, 6]]))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testInputSpecShapeCheck(self):
 
     class CustomerLayer(base_layers.Layer):
@@ -348,7 +348,7 @@ class BaseLayerTest(test.TestCase):
     layer = CustomerLayer()
     layer.apply(constant_op.constant([[1, 2, 3], [4, 5, 6]]))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNoInputSpec(self):
 
     class CustomerLayer(base_layers.Layer):
@@ -369,7 +369,7 @@ class BaseLayerTest(test.TestCase):
       layer.apply(array_ops.placeholder('int32'))
       layer.apply(array_ops.placeholder('int32', shape=(2, 3)))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def test_count_params(self):
     dense = core_layers.Dense(16)
     dense.build((None, 4))
@@ -379,7 +379,7 @@ class BaseLayerTest(test.TestCase):
     with self.assertRaises(ValueError):
       dense.count_params()
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDictInputOutput(self):
 
     class DictLayer(base_layers.Layer):
diff --git a/tensorflow/python/layers/core_test.py b/tensorflow/python/layers/core_test.py
index cf45b07637..040c1cddc0 100644
--- a/tensorflow/python/layers/core_test.py
+++ b/tensorflow/python/layers/core_test.py
@@ -41,7 +41,7 @@ from tensorflow.python.platform import test
 
 class DenseTest(test.TestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDenseProperties(self):
     dense = core_layers.Dense(2, activation=nn_ops.relu, name='my_dense')
     self.assertEqual(dense.units, 2)
@@ -91,14 +91,14 @@ class DenseTest(test.TestCase):
     core_layers.Dense(5)(inputs)
     core_layers.Dense(2, activation=nn_ops.relu, name='my_dense')(inputs)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testCallTensorDot(self):
     dense = core_layers.Dense(2, activation=nn_ops.relu, name='my_dense')
     inputs = random_ops.random_uniform((5, 4, 3), seed=1)
     outputs = dense(inputs)
     self.assertListEqual([5, 4, 2], outputs.get_shape().as_list())
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNoBias(self):
     dense = core_layers.Dense(2, use_bias=False, name='my_dense')
     inputs = random_ops.random_uniform((5, 2), seed=1)
@@ -112,7 +112,7 @@ class DenseTest(test.TestCase):
     self.assertEqual(dense.kernel.name, 'my_dense/kernel:0')
     self.assertEqual(dense.bias, None)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNonTrainable(self):
     dense = core_layers.Dense(2, trainable=False, name='my_dense')
     inputs = random_ops.random_uniform((5, 2), seed=1)
@@ -125,7 +125,7 @@ class DenseTest(test.TestCase):
       self.assertEqual(
           len(ops.get_collection(ops.GraphKeys.TRAINABLE_VARIABLES)), 0)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testOutputShape(self):
     dense = core_layers.Dense(7, activation=nn_ops.relu, name='my_dense')
     inputs = random_ops.random_uniform((5, 3), seed=1)
@@ -165,7 +165,7 @@ class DenseTest(test.TestCase):
     dense = core_layers.Dense(4, name='my_dense')
     dense(inputs)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testActivation(self):
     dense = core_layers.Dense(2, activation=nn_ops.relu, name='dense1')
     inputs = random_ops.random_uniform((5, 3), seed=1)
@@ -325,7 +325,7 @@ class DenseTest(test.TestCase):
         var_key = 'test2/dense/kernel'
         self.assertEqual(var_dict[var_key].name, '%s:0' % var_key)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testComputeOutputShape(self):
     dense = core_layers.Dense(2, activation=nn_ops.relu, name='dense1')
     ts = tensor_shape.TensorShape
@@ -347,7 +347,7 @@ class DenseTest(test.TestCase):
         dense.compute_output_shape(ts([None, 4, 3])).as_list())
     # pylint: enable=protected-access
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testConstraints(self):
     k_constraint = lambda x: x / math_ops.reduce_sum(x)
     b_constraint = lambda x: x / math_ops.reduce_max(x)
@@ -369,7 +369,7 @@ def _get_variable_dict_from_varstore():
 
 class DropoutTest(test.TestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDropoutProperties(self):
     dp = core_layers.Dropout(0.5, name='dropout')
     self.assertEqual(dp.rate, 0.5)
@@ -377,7 +377,7 @@ class DropoutTest(test.TestCase):
     dp.apply(array_ops.ones(()))
     self.assertEqual(dp.name, 'dropout')
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testBooleanLearningPhase(self):
     dp = core_layers.Dropout(0.5)
     inputs = array_ops.ones((5, 3))
@@ -402,7 +402,7 @@ class DropoutTest(test.TestCase):
       np_output = sess.run(dropped, feed_dict={training: False})
       self.assertAllClose(np.ones((5, 5)), np_output)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDynamicNoiseShape(self):
     inputs = array_ops.ones((5, 3, 2))
     noise_shape = [None, 1, None]