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

PiperOrigin-RevId: 201652888

1 files changed, 29 insertions, 29 deletions

diff --git a/tensorflow/python/training/learning_rate_decay_test.py b/tensorflow/python/training/learning_rate_decay_test.py
index efcf47edda..4f3cf01822 100644
--- a/tensorflow/python/training/learning_rate_decay_test.py
+++ b/tensorflow/python/training/learning_rate_decay_test.py
@@ -31,7 +31,7 @@ from tensorflow.python.training import learning_rate_decay
 
 class LRDecayTest(test_util.TensorFlowTestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testContinuous(self):
     self.evaluate(variables.global_variables_initializer())
     step = 5
@@ -39,7 +39,7 @@ class LRDecayTest(test_util.TensorFlowTestCase):
     expected = .05 * 0.96**(5.0 / 10.0)
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testStaircase(self):
     if context.executing_eagerly():
       step = resource_variable_ops.ResourceVariable(0)
@@ -80,7 +80,7 @@ class LRDecayTest(test_util.TensorFlowTestCase):
       expected = .1 * 0.96 ** (100 // 3)
       self.assertAllClose(decayed_lr.eval(), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testPiecewiseConstant(self):
     x = resource_variable_ops.ResourceVariable(-999)
     decayed_lr = learning_rate_decay.piecewise_constant(
@@ -100,7 +100,7 @@ class LRDecayTest(test_util.TensorFlowTestCase):
     self.evaluate(x.assign(999))
     self.assertAllClose(self.evaluate(decayed_lr), 0.001, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testPiecewiseConstantEdgeCases(self):
     x_int = resource_variable_ops.ResourceVariable(
         0, dtype=variables.dtypes.int32)
@@ -147,7 +147,7 @@ class LRDecayTest(test_util.TensorFlowTestCase):
 
 class LinearDecayTest(test_util.TensorFlowTestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testHalfWay(self):
     step = 5
     lr = 0.05
@@ -156,7 +156,7 @@ class LinearDecayTest(test_util.TensorFlowTestCase):
     expected = lr * 0.5
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testEnd(self):
     step = 10
     lr = 0.05
@@ -165,7 +165,7 @@ class LinearDecayTest(test_util.TensorFlowTestCase):
     expected = end_lr
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testHalfWayWithEnd(self):
     step = 5
     lr = 0.05
@@ -174,7 +174,7 @@ class LinearDecayTest(test_util.TensorFlowTestCase):
     expected = (lr + end_lr) * 0.5
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testBeyondEnd(self):
     step = 15
     lr = 0.05
@@ -183,7 +183,7 @@ class LinearDecayTest(test_util.TensorFlowTestCase):
     expected = end_lr
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testBeyondEndWithCycle(self):
     step = 15
     lr = 0.05
@@ -196,7 +196,7 @@ class LinearDecayTest(test_util.TensorFlowTestCase):
 
 class SqrtDecayTest(test_util.TensorFlowTestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testHalfWay(self):
     step = 5
     lr = 0.05
@@ -207,7 +207,7 @@ class SqrtDecayTest(test_util.TensorFlowTestCase):
     expected = lr * 0.5**power
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testEnd(self):
     step = 10
     lr = 0.05
@@ -218,7 +218,7 @@ class SqrtDecayTest(test_util.TensorFlowTestCase):
     expected = end_lr
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testHalfWayWithEnd(self):
     step = 5
     lr = 0.05
@@ -229,7 +229,7 @@ class SqrtDecayTest(test_util.TensorFlowTestCase):
     expected = (lr - end_lr) * 0.5**power + end_lr
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testBeyondEnd(self):
     step = 15
     lr = 0.05
@@ -240,7 +240,7 @@ class SqrtDecayTest(test_util.TensorFlowTestCase):
     expected = end_lr
     self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testBeyondEndWithCycle(self):
     step = 15
     lr = 0.05
@@ -254,7 +254,7 @@ class SqrtDecayTest(test_util.TensorFlowTestCase):
 
 class PolynomialDecayTest(test_util.TensorFlowTestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testBeginWithCycle(self):
     lr = 0.001
     decay_steps = 10
@@ -267,7 +267,7 @@ class PolynomialDecayTest(test_util.TensorFlowTestCase):
 
 class ExponentialDecayTest(test_util.TensorFlowTestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDecay(self):
     initial_lr = 0.1
     k = 10
@@ -282,7 +282,7 @@ class ExponentialDecayTest(test_util.TensorFlowTestCase):
       self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
       self.evaluate(step.assign_add(1))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testStaircase(self):
     initial_lr = 0.1
     k = 10
@@ -300,7 +300,7 @@ class ExponentialDecayTest(test_util.TensorFlowTestCase):
 
 class InverseDecayTest(test_util.TensorFlowTestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDecay(self):
     initial_lr = 0.1
     k = 10
@@ -315,7 +315,7 @@ class InverseDecayTest(test_util.TensorFlowTestCase):
       self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
       self.evaluate(step.assign_add(1))
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testStaircase(self):
     initial_lr = 0.1
     k = 10
@@ -339,7 +339,7 @@ class CosineDecayTest(test_util.TensorFlowTestCase):
     decay = 0.5 * (1.0 + math.cos(math.pi * completed_fraction))
     return (1.0 - alpha) * decay + alpha
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDecay(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -349,7 +349,7 @@ class CosineDecayTest(test_util.TensorFlowTestCase):
       expected = self.np_cosine_decay(step, num_training_steps)
       self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testAlpha(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -375,7 +375,7 @@ class CosineDecayRestartsTest(test_util.TensorFlowTestCase):
     decay = fac * 0.5 * (1.0 + math.cos(math.pi * completed_fraction))
     return (1.0 - alpha) * decay + alpha
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDecay(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -385,7 +385,7 @@ class CosineDecayRestartsTest(test_util.TensorFlowTestCase):
       expected = self.np_cosine_decay_restarts(step, num_training_steps)
       self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testAlpha(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -397,7 +397,7 @@ class CosineDecayRestartsTest(test_util.TensorFlowTestCase):
           step, num_training_steps, alpha=alpha)
       self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testMMul(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -409,7 +409,7 @@ class CosineDecayRestartsTest(test_util.TensorFlowTestCase):
           step, num_training_steps, m_mul=m_mul)
       self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testTMul(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -436,7 +436,7 @@ class LinearCosineDecayTest(test_util.TensorFlowTestCase):
     cosine_decayed = 0.5 * (1.0 + math.cos(math.pi * fraction))
     return (alpha + linear_decayed) * cosine_decayed + beta
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDefaultDecay(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -446,7 +446,7 @@ class LinearCosineDecayTest(test_util.TensorFlowTestCase):
       expected = self.np_linear_cosine_decay(step, num_training_steps)
       self.assertAllClose(self.evaluate(decayed_lr), expected, 1e-6)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNonDefaultDecay(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -465,7 +465,7 @@ class LinearCosineDecayTest(test_util.TensorFlowTestCase):
 
 class NoisyLinearCosineDecayTest(test_util.TensorFlowTestCase):
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testDefaultNoisyLinearCosine(self):
     num_training_steps = 1000
     initial_lr = 1.0
@@ -476,7 +476,7 @@ class NoisyLinearCosineDecayTest(test_util.TensorFlowTestCase):
       # Cannot be deterministically tested
       self.evaluate(decayed_lr)
 
-  @test_util.run_in_graph_and_eager_modes()
+  @test_util.run_in_graph_and_eager_modes
   def testNonDefaultNoisyLinearCosine(self):
     num_training_steps = 1000
     initial_lr = 1.0