rm unittests eager guard tests part12 imperative_optimizer2resnet (#48833)

python/paddle/fluid/tests/unittests/test_imperative_optimizer.py

@@ -22,7 +22,6 @@ import paddle
 import paddle.fluid as fluid
 from paddle.distributed.fleet.meta_optimizers import DGCMomentumOptimizer
 from paddle.fluid import core
-from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.optimizer import (
     AdadeltaOptimizer,
     AdagradOptimizer,
@@ -268,13 +267,8 @@ class TestImperativeOptimizerPiecewiseDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerNaturalExpDecay(TestImperativeOptimizerBase):
@@ -301,13 +295,8 @@ class TestImperativeOptimizerNaturalExpDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerExponentialDecay(TestImperativeOptimizerBase):
@@ -334,13 +323,8 @@ class TestImperativeOptimizerExponentialDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerInverseTimeDecay(TestImperativeOptimizerBase):
@@ -367,13 +351,8 @@ class TestImperativeOptimizerInverseTimeDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_adam(self):
-        self._check_mlp()
-
     def test_adam(self):
-        with _test_eager_guard():
-            self.func_test_adam()
-        self.func_test_adam()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerPolynomialDecay(TestImperativeOptimizerBase):
@@ -394,24 +373,14 @@ class TestImperativeOptimizerPolynomialDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd_cycle(self):
+    def test_sgd_cycle(self):
         self.cycle = True
         self._check_mlp()
 
-    def test_sgd_cycle(self):
-        with _test_eager_guard():
-            self.func_test_sgd_cycle()
-        self.func_test_sgd_cycle()
-
-    def func_test_sgd(self):
+    def test_sgd(self):
         self.cycle = False
         self._check_mlp()
 
-    def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
-
 
 class TestImperativeOptimizerCosineDecay(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -431,13 +400,8 @@ class TestImperativeOptimizerCosineDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerNoamDecay(TestImperativeOptimizerBase):
@@ -458,17 +422,12 @@ class TestImperativeOptimizerNoamDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestOptimizerLearningRate(unittest.TestCase):
-    def func_test_constant_lr(self):
+    def test_constant_lr(self):
         with fluid.dygraph.guard():
             a = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
 
@@ -494,12 +453,7 @@ class TestOptimizerLearningRate(unittest.TestCase):
 
                 np.testing.assert_allclose(lr, 0.001, rtol=1e-06, atol=0.0)
 
-    def test_constant_lr(self):
-        with _test_eager_guard():
-            self.func_test_constant_lr()
-        self.func_test_constant_lr()
-
-    def func_test_lr_decay(self):
+    def test_lr_decay(self):
         with fluid.dygraph.guard():
             a = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
 
@@ -530,12 +484,7 @@ class TestOptimizerLearningRate(unittest.TestCase):
 
                 np.testing.assert_allclose(lr, ret[i], rtol=1e-06, atol=0.0)
 
-    def test_lr_decay(self):
-        with _test_eager_guard():
-            self.func_test_lr_decay()
-        self.func_test_lr_decay()
-
-    def func_test_lr_decay_natural_exp(self):
+    def test_lr_decay_natural_exp(self):
         with fluid.dygraph.guard():
             a = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
 
@@ -569,12 +518,7 @@ class TestOptimizerLearningRate(unittest.TestCase):
 
                 np.testing.assert_allclose(lr, ret[i], rtol=1e-06, atol=0.0)
 
-    def test_lr_decay_natural_exp(self):
-        with _test_eager_guard():
-            self.func_test_lr_decay_natural_exp()
-        self.func_test_lr_decay_natural_exp()
-
-    def func_test_set_lr(self):
+    def test_set_lr(self):
         with fluid.dygraph.guard():
             a = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
 
@@ -615,11 +559,6 @@ class TestOptimizerLearningRate(unittest.TestCase):
                 )
                 adam.set_lr(0.01)
 
-    def test_set_lr(self):
-        with _test_eager_guard():
-            self.func_test_set_lr()
-        self.func_test_set_lr()
-
 
 class TestImperativeMomentumOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -632,13 +571,8 @@ class TestImperativeMomentumOptimizer(TestImperativeOptimizerBase):
         optimizer = MomentumOptimizer(learning_rate=0.001, momentum=0.9)
         return optimizer
 
-    def func_test_momentum(self):
-        self._check_mlp()
-
     def test_momentum(self):
-        with _test_eager_guard():
-            self.func_test_momentum()
-        self.func_test_momentum()
+        self._check_mlp()
 
 
 class TestImperativeLarsMomentumOptimizer(TestImperativeOptimizerBase):
@@ -652,13 +586,8 @@ class TestImperativeLarsMomentumOptimizer(TestImperativeOptimizerBase):
         optimizer = LarsMomentumOptimizer(learning_rate=0.001, momentum=0.9)
         return optimizer
 
-    def func_test_larsmomentum(self):
-        self._check_mlp()
-
     def test_larsmomentum(self):
-        with _test_eager_guard():
-            self.func_test_larsmomentum()
-        self.func_test_larsmomentum()
+        self._check_mlp()
 
 
 class TestImperativeAdagradOptimizer(TestImperativeOptimizerBase):
@@ -672,13 +601,8 @@ class TestImperativeAdagradOptimizer(TestImperativeOptimizerBase):
         optimizer = AdagradOptimizer(learning_rate=0.2)
         return optimizer
 
-    def func_test_adagrad(self):
-        self._check_mlp()
-
     def test_adagrad(self):
-        with _test_eager_guard():
-            self.func_test_adagrad()
-        self.func_test_adagrad()
+        self._check_mlp()
 
 
 class TestImperativeAdamaxOptimizer(TestImperativeOptimizerBase):
@@ -692,13 +616,8 @@ class TestImperativeAdamaxOptimizer(TestImperativeOptimizerBase):
         optimizer = AdamaxOptimizer(learning_rate=0.2)
         return optimizer
 
-    def func_test_adamax(self):
-        self._check_mlp()
-
     def test_adamax(self):
-        with _test_eager_guard():
-            self.func_test_adamax()
-        self.func_test_adamax()
+        self._check_mlp()
 
 
 class TestImperativeDpsgdOptimizer(TestImperativeOptimizerBase):
@@ -720,13 +639,8 @@ class TestImperativeDpsgdOptimizer(TestImperativeOptimizerBase):
         optimizer._seed = 100
         return optimizer
 
-    def func_test_dpsgd(self):
-        self._check_mlp(place=fluid.CPUPlace())
-
     def test_dpsgd(self):
-        with _test_eager_guard():
-            self.func_test_dpsgd()
-        self.func_test_dpsgd()
+        self._check_mlp(place=fluid.CPUPlace())
 
 
 class TestImperativeDecayedAdagradOptimizer(TestImperativeOptimizerBase):
@@ -740,13 +654,8 @@ class TestImperativeDecayedAdagradOptimizer(TestImperativeOptimizerBase):
         optimizer = DecayedAdagradOptimizer(learning_rate=0.2)
         return optimizer
 
-    def func_test_decayadagrad(self):
-        self._check_mlp()
-
     def test_decayadagrad(self):
-        with _test_eager_guard():
-            self.func_test_decayadagrad()
-        self.func_test_decayadagrad()
+        self._check_mlp()
 
 
 class TestImperativeAdadeltaOptimizer(TestImperativeOptimizerBase):
@@ -765,13 +674,8 @@ class TestImperativeAdadeltaOptimizer(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_adadelta(self):
-        self._check_mlp()
-
     def test_adadelta(self):
-        with _test_eager_guard():
-            self.func_test_adadelta()
-        self.func_test_adadelta()
+        self._check_mlp()
 
 
 class TestImperativeRMSPropOptimizer(TestImperativeOptimizerBase):
@@ -785,13 +689,8 @@ class TestImperativeRMSPropOptimizer(TestImperativeOptimizerBase):
         optimizer = RMSPropOptimizer(learning_rate=0.1)
         return optimizer
 
-    def func_test_rmsprop(self):
-        self._check_mlp()
-
     def test_rmsprop(self):
-        with _test_eager_guard():
-            self.func_test_rmsprop()
-        self.func_test_rmsprop()
+        self._check_mlp()
 
 
 class TestImperativeFtrlOptimizer(TestImperativeOptimizerBase):
@@ -805,13 +704,8 @@ class TestImperativeFtrlOptimizer(TestImperativeOptimizerBase):
         optimizer = FtrlOptimizer(learning_rate=0.1)
         return optimizer
 
-    def func_test_ftrl(self):
-        self._check_mlp()
-
     def test_ftrl(self):
-        with _test_eager_guard():
-            self.func_test_ftrl()
-        self.func_test_ftrl()
+        self._check_mlp()
 
 
 def exclude_fn(param):
@@ -845,15 +739,10 @@ class TestImperativeModelAverage(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_modelaverage(self):
+    def test_modelaverage(self):
         exception_message = "In dygraph, don't support ModelAverage."
         self._check_exception(exception_message)
 
-    def test_modelaverage(self):
-        with _test_eager_guard():
-            self.func_test_modelaverage()
-        self.func_test_modelaverage()
-
 
 class TestImperativeDGCMomentumOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -866,32 +755,22 @@ class TestImperativeDGCMomentumOptimizer(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_dgcmomentum(self):
+    def test_dgcmomentum(self):
         exception_message = "In dygraph, don't support DGCMomentumOptimizer."
         self._check_exception(exception_message)
 
-    def test_dgcmomentum(self):
-        with _test_eager_guard():
-            self.func_test_dgcmomentum()
-        self.func_test_dgcmomentum()
-
 
 class TestImperativeExponentialMovingAverage(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
         optimizer = ExponentialMovingAverage(0.999)
         return optimizer
 
-    def func_test_exponentialmoving(self):
+    def test_exponentialmoving(self):
         exception_message = (
             "In dygraph, don't support ExponentialMovingAverage."
         )
         self._check_exception(exception_message)
 
-    def test_exponentialmoving(self):
-        with _test_eager_guard():
-            self.func_test_exponentialmoving()
-        self.func_test_exponentialmoving()
-
 
 class TestImperativePipelineOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -901,15 +780,10 @@ class TestImperativePipelineOptimizer(TestImperativeOptimizerBase):
         optimizer = PipelineOptimizer(optimizer)
         return optimizer
 
-    def func_test_pipline(self):
+    def test_pipline(self):
         exception_message = "In dygraph, don't support PipelineOptimizer."
         self._check_exception(exception_message)
 
-    def test_pipline(self):
-        with _test_eager_guard():
-            self.func_test_pipline()
-        self.func_test_pipline()
-
 
 class TestImperativeLookaheadOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -919,15 +793,10 @@ class TestImperativeLookaheadOptimizer(TestImperativeOptimizerBase):
         optimizer = LookaheadOptimizer(optimizer, alpha=0.5, k=5)
         return optimizer
 
-    def func_test_lookahead(self):
+    def test_lookahead(self):
         exception_message = "In dygraph, don't support LookaheadOptimizer."
         self._check_exception(exception_message)
 
-    def test_lookahead(self):
-        with _test_eager_guard():
-            self.func_test_lookahead()
-        self.func_test_lookahead()
-
 
 class TestImperativeRecomputeOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -937,18 +806,13 @@ class TestImperativeRecomputeOptimizer(TestImperativeOptimizerBase):
         optimizer = RecomputeOptimizer(optimizer)
         return optimizer
 
-    def func_test_recompute(self):
+    def test_recompute(self):
         exception_message = "In dygraph, don't support RecomputeOptimizer."
         self._check_exception(exception_message)
 
-    def test_recompute(self):
-        with _test_eager_guard():
-            self.func_test_recompute()
-        self.func_test_recompute()
-
 
 class TestImperativeOptimizerList(unittest.TestCase):
-    def func_test_parameter_list(self):
+    def test_parameter_list(self):
         with fluid.dygraph.guard():
             linear_1 = paddle.nn.Linear(10, 10)
             linear_2 = paddle.nn.Linear(10, 10)
@@ -974,11 +838,6 @@ class TestImperativeOptimizerList(unittest.TestCase):
                 == len(linear_1.parameters() + linear_2.parameters())
             )
 
-    def test_parameter_list(self):
-        with _test_eager_guard():
-            self.func_test_parameter_list()
-        self.func_test_parameter_list()
-
 
 if __name__ == '__main__':
     unittest.main()

python/paddle/fluid/tests/unittests/test_imperative_optimizer_v2.py

@@ -22,7 +22,6 @@ import paddle
 import paddle.fluid as fluid
 from paddle.distributed.fleet.meta_optimizers import DGCMomentumOptimizer
 from paddle.fluid import core
-from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.optimizer import (
     AdadeltaOptimizer,
     AdagradOptimizer,
@@ -287,13 +286,8 @@ class TestImperativeOptimizerPiecewiseDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerNaturalExpDecay(TestImperativeOptimizerBase):
@@ -314,13 +308,8 @@ class TestImperativeOptimizerNaturalExpDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerExponentialDecay(TestImperativeOptimizerBase):
@@ -341,13 +330,8 @@ class TestImperativeOptimizerExponentialDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerInverseTimeDecay(TestImperativeOptimizerBase):
@@ -368,13 +352,8 @@ class TestImperativeOptimizerInverseTimeDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_adam(self):
-        self._check_mlp()
-
     def test_adam(self):
-        with _test_eager_guard():
-            self.func_test_adam()
-        self.func_test_adam()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerPolynomialDecay(TestImperativeOptimizerBase):
@@ -395,24 +374,14 @@ class TestImperativeOptimizerPolynomialDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd_cycle(self):
+    def test_sgd_cycle(self):
         self.cycle = True
         self._check_mlp()
 
-    def test_sgd_cycle(self):
-        with _test_eager_guard():
-            self.func_test_sgd_cycle()
-        self.func_test_sgd_cycle()
-
-    def func_test_sgd(self):
+    def test_sgd(self):
         self.cycle = False
         self._check_mlp()
 
-    def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
-
 
 class TestImperativeOptimizerCosineAnnealingDecay(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -432,13 +401,8 @@ class TestImperativeOptimizerCosineAnnealingDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerNoamDecay(TestImperativeOptimizerBase):
@@ -459,13 +423,8 @@ class TestImperativeOptimizerNoamDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerLambdaDecay(TestImperativeOptimizerBase):
@@ -486,13 +445,8 @@ class TestImperativeOptimizerLambdaDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerLinearWarmup(TestImperativeOptimizerBase):
@@ -517,13 +471,8 @@ class TestImperativeOptimizerLinearWarmup(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerMultiStepDecay(TestImperativeOptimizerBase):
@@ -544,13 +493,8 @@ class TestImperativeOptimizerMultiStepDecay(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerStepLR(TestImperativeOptimizerBase):
@@ -571,13 +515,8 @@ class TestImperativeOptimizerStepLR(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestImperativeOptimizerReduceOnPlateau(TestImperativeOptimizerBase):
@@ -596,17 +535,12 @@ class TestImperativeOptimizerReduceOnPlateau(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_sgd(self):
-        self._check_mlp()
-
     def test_sgd(self):
-        with _test_eager_guard():
-            self.func_test_sgd()
-        self.func_test_sgd()
+        self._check_mlp()
 
 
 class TestOptimizerLearningRate(unittest.TestCase):
-    def func_test_constant_lr(self):
+    def test_constant_lr(self):
         with fluid.dygraph.guard():
             a = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
 
@@ -630,12 +564,7 @@ class TestOptimizerLearningRate(unittest.TestCase):
 
                 np.testing.assert_allclose(lr, 0.001, rtol=1e-06, atol=0.0)
 
-    def test_constant_lr(self):
-        with _test_eager_guard():
-            self.func_test_constant_lr()
-        self.func_test_constant_lr()
-
-    def func_test_lr_decay(self):
+    def test_lr_decay(self):
         with fluid.dygraph.guard():
             a = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
 
@@ -664,12 +593,7 @@ class TestOptimizerLearningRate(unittest.TestCase):
                 np.testing.assert_allclose(lr, ret[i], rtol=1e-06, atol=0.0)
                 scheduler.step()
 
-    def test_lr_decay(self):
-        with _test_eager_guard():
-            self.func_test_lr_decay()
-        self.func_test_lr_decay()
-
-    def func_test_lr_scheduler_natural_exp(self):
+    def test_lr_scheduler_natural_exp(self):
         with fluid.dygraph.guard():
             a = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
 
@@ -694,12 +618,7 @@ class TestOptimizerLearningRate(unittest.TestCase):
                 np.testing.assert_allclose(lr, ret[i], rtol=1e-06, atol=0.0)
                 scheduler.step()
 
-    def test_lr_scheduler_natural_exp(self):
-        with _test_eager_guard():
-            self.func_test_lr_scheduler_natural_exp()
-        self.func_test_lr_scheduler_natural_exp()
-
-    def func_test_set_lr(self):
+    def test_set_lr(self):
         with fluid.dygraph.guard():
             a = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
 
@@ -735,11 +654,6 @@ class TestOptimizerLearningRate(unittest.TestCase):
                 )
                 adam.set_lr(0.01)
 
-    def test_set_lr(self):
-        with _test_eager_guard():
-            self.func_test_set_lr()
-        self.func_test_set_lr()
-
 
 class TestImperativeMomentumOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -752,13 +666,8 @@ class TestImperativeMomentumOptimizer(TestImperativeOptimizerBase):
         optimizer = MomentumOptimizer(learning_rate=0.001, momentum=0.9)
         return optimizer
 
-    def func_test_momentum(self):
-        self._check_mlp()
-
     def test_momentum(self):
-        with _test_eager_guard():
-            self.func_test_momentum()
-        self.func_test_momentum()
+        self._check_mlp()
 
 
 class TestImperativeLarsMomentumOptimizer(TestImperativeOptimizerBase):
@@ -772,13 +681,8 @@ class TestImperativeLarsMomentumOptimizer(TestImperativeOptimizerBase):
         optimizer = LarsMomentumOptimizer(learning_rate=0.001, momentum=0.9)
         return optimizer
 
-    def func_test_larsmomentum(self):
-        self._check_mlp()
-
     def test_larsmomentum(self):
-        with _test_eager_guard():
-            self.func_test_larsmomentum()
-        self.func_test_larsmomentum()
+        self._check_mlp()
 
 
 class TestImperativeAdagradOptimizer(TestImperativeOptimizerBase):
@@ -792,13 +696,8 @@ class TestImperativeAdagradOptimizer(TestImperativeOptimizerBase):
         optimizer = AdagradOptimizer(learning_rate=0.2)
         return optimizer
 
-    def func_test_adagrad(self):
-        self._check_mlp()
-
     def test_adagrad(self):
-        with _test_eager_guard():
-            self.func_test_adagrad()
-        self.func_test_adagrad()
+        self._check_mlp()
 
 
 class TestImperativeAdamaxOptimizer(TestImperativeOptimizerBase):
@@ -812,13 +711,8 @@ class TestImperativeAdamaxOptimizer(TestImperativeOptimizerBase):
         optimizer = AdamaxOptimizer(learning_rate=0.2)
         return optimizer
 
-    def func_test_adamax(self):
-        self._check_mlp()
-
     def test_adamax(self):
-        with _test_eager_guard():
-            self.func_test_adamax()
-        self.func_test_adamax()
+        self._check_mlp()
 
 
 class TestImperativeDpsgdOptimizer(TestImperativeOptimizerBase):
@@ -840,13 +734,8 @@ class TestImperativeDpsgdOptimizer(TestImperativeOptimizerBase):
         optimizer._seed = 100
         return optimizer
 
-    def func_test_dpsgd(self):
-        self._check_mlp(place=fluid.CPUPlace())
-
     def test_dpsgd(self):
-        with _test_eager_guard():
-            self.func_test_dpsgd()
-        self.func_test_dpsgd()
+        self._check_mlp(place=fluid.CPUPlace())
 
 
 class TestImperativeDecayedAdagradOptimizer(TestImperativeOptimizerBase):
@@ -860,13 +749,8 @@ class TestImperativeDecayedAdagradOptimizer(TestImperativeOptimizerBase):
         optimizer = DecayedAdagradOptimizer(learning_rate=0.2)
         return optimizer
 
-    def func_test_decayadagrad(self):
-        self._check_mlp()
-
     def test_decayadagrad(self):
-        with _test_eager_guard():
-            self.func_test_decayadagrad()
-        self.func_test_decayadagrad()
+        self._check_mlp()
 
 
 class TestImperativeAdadeltaOptimizer(TestImperativeOptimizerBase):
@@ -885,13 +769,8 @@ class TestImperativeAdadeltaOptimizer(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_adadelta(self):
-        self._check_mlp()
-
     def test_adadelta(self):
-        with _test_eager_guard():
-            self.func_test_adadelta()
-        self.func_test_adadelta()
+        self._check_mlp()
 
 
 class TestImperativeRMSPropOptimizer(TestImperativeOptimizerBase):
@@ -905,13 +784,8 @@ class TestImperativeRMSPropOptimizer(TestImperativeOptimizerBase):
         optimizer = RMSPropOptimizer(learning_rate=0.1)
         return optimizer
 
-    def func_test_rmsprop(self):
-        self._check_mlp()
-
     def test_rmsprop(self):
-        with _test_eager_guard():
-            self.func_test_rmsprop()
-        self.func_test_rmsprop()
+        self._check_mlp()
 
 
 class TestImperativeFtrlOptimizer(TestImperativeOptimizerBase):
@@ -925,13 +799,8 @@ class TestImperativeFtrlOptimizer(TestImperativeOptimizerBase):
         optimizer = FtrlOptimizer(learning_rate=0.1)
         return optimizer
 
-    def func_test_ftrl(self):
-        self._check_mlp()
-
     def test_ftrl(self):
-        with _test_eager_guard():
-            self.func_test_ftrl()
-        self.func_test_ftrl()
+        self._check_mlp()
 
 
 def exclude_fn(param):
@@ -965,15 +834,10 @@ class TestImperativeModelAverage(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_modelaverage(self):
+    def test_modelaverage(self):
         exception_message = "In dygraph, don't support ModelAverage."
         self._check_exception(exception_message)
 
-    def test_modelaverage(self):
-        with _test_eager_guard():
-            self.func_test_modelaverage()
-        self.func_test_modelaverage()
-
 
 class TestImperativeDGCMomentumOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -986,32 +850,22 @@ class TestImperativeDGCMomentumOptimizer(TestImperativeOptimizerBase):
         )
         return optimizer
 
-    def func_test_dgcmomentum(self):
+    def test_dgcmomentum(self):
         exception_message = "In dygraph, don't support DGCMomentumOptimizer."
         self._check_exception(exception_message)
 
-    def test_dgcmomentum(self):
-        with _test_eager_guard():
-            self.func_test_dgcmomentum()
-        self.func_test_dgcmomentum()
-
 
 class TestImperativeExponentialMovingAverage(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
         optimizer = ExponentialMovingAverage(0.999)
         return optimizer
 
-    def func_test_exponentialmoving(self):
+    def test_exponentialmoving(self):
         exception_message = (
             "In dygraph, don't support ExponentialMovingAverage."
         )
         self._check_exception(exception_message)
 
-    def test_exponentialmoving(self):
-        with _test_eager_guard():
-            self.func_test_exponentialmoving()
-        self.func_test_exponentialmoving()
-
 
 class TestImperativePipelineOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -1021,15 +875,10 @@ class TestImperativePipelineOptimizer(TestImperativeOptimizerBase):
         optimizer = PipelineOptimizer(optimizer)
         return optimizer
 
-    def func_test_pipline(self):
+    def test_pipline(self):
         exception_message = "In dygraph, don't support PipelineOptimizer."
         self._check_exception(exception_message)
 
-    def test_pipline(self):
-        with _test_eager_guard():
-            self.func_test_pipline()
-        self.func_test_pipline()
-
 
 class TestImperativeLookaheadOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -1039,15 +888,10 @@ class TestImperativeLookaheadOptimizer(TestImperativeOptimizerBase):
         optimizer = LookaheadOptimizer(optimizer, alpha=0.5, k=5)
         return optimizer
 
-    def func_test_lookahead(self):
+    def test_lookahead(self):
         exception_message = "In dygraph, don't support LookaheadOptimizer."
         self._check_exception(exception_message)
 
-    def test_lookahead(self):
-        with _test_eager_guard():
-            self.func_test_lookahead()
-        self.func_test_lookahead()
-
 
 class TestImperativeRecomputeOptimizer(TestImperativeOptimizerBase):
     def get_optimizer_dygraph(self, parameter_list):
@@ -1057,18 +901,13 @@ class TestImperativeRecomputeOptimizer(TestImperativeOptimizerBase):
         optimizer = RecomputeOptimizer(optimizer)
         return optimizer
 
-    def func_test_recompute(self):
+    def test_recompute(self):
         exception_message = "In dygraph, don't support RecomputeOptimizer."
         self._check_exception(exception_message)
 
-    def test_recompute(self):
-        with _test_eager_guard():
-            self.func_test_recompute()
-        self.func_test_recompute()
-
 
 class TestImperativeOptimizerList(unittest.TestCase):
-    def func_test_parameter_list(self):
+    def test_parameter_list(self):
         with fluid.dygraph.guard():
             linear_1 = paddle.nn.Linear(10, 10)
             linear_2 = paddle.nn.Linear(10, 10)
@@ -1094,11 +933,6 @@ class TestImperativeOptimizerList(unittest.TestCase):
                 == len(linear_1.parameters() + linear_2.parameters())
             )
 
-    def test_parameter_list(self):
-        with _test_eager_guard():
-            self.func_test_parameter_list()
-        self.func_test_parameter_list()
-
 
 if __name__ == '__main__':
     unittest.main()

python/paddle/fluid/tests/unittests/test_imperative_partitial_backward.py

@@ -18,11 +18,10 @@ import numpy as np
 
 import paddle
 import paddle.fluid as fluid
-from paddle.fluid.framework import _test_eager_guard
 
 
 class TestImperativePartitialBackward(unittest.TestCase):
-    def func_partitial_backward(self):
+    def test_partitial_backward(self):
         with fluid.dygraph.guard():
             x = np.random.randn(2, 4, 5).astype("float32")
             x = fluid.dygraph.to_variable(x)
@@ -53,11 +52,6 @@ class TestImperativePartitialBackward(unittest.TestCase):
             linear1.clear_gradients()
             linear2.clear_gradients()
 
-    def test_partitial_backward(self):
-        with _test_eager_guard():
-            self.func_partitial_backward()
-        self.func_partitial_backward()
-
 
 if __name__ == '__main__':
     unittest.main()

python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py

@@ -23,7 +23,6 @@ import paddle.fluid as fluid
 import paddle.fluid.core as core
 import paddle.fluid.framework as framework
 from paddle.fluid.dygraph.base import to_variable
-from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.optimizer import SGDOptimizer
 from paddle.nn import Embedding
 
@@ -238,15 +237,10 @@ class PtbModel(fluid.Layer):
 
 
 class TestDygraphPtbRnn(unittest.TestCase):
-    def func_test_ptb_rnn(self):
+    def test_ptb_rnn(self):
         for is_sparse in [True, False]:
             self.ptb_rnn_cpu_float32(is_sparse)
 
-    def test_ptb_rnn(self):
-        with _test_eager_guard():
-            self.func_test_ptb_rnn()
-        self.func_test_ptb_rnn()
-
     def ptb_rnn_cpu_float32(self, is_sparse):
         seed = 90
         hidden_size = 10

python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn_sorted_gradient.py

@@ -23,12 +23,11 @@ import paddle.fluid as fluid
 import paddle.fluid.core as core
 import paddle.fluid.framework as framework
 from paddle.fluid.dygraph.base import to_variable
-from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.optimizer import SGDOptimizer
 
 
 class TestDygraphPtbRnnSortGradient(unittest.TestCase):
-    def func_ptb_rnn_sort_gradient(self):
+    def test_ptb_rnn_sort_gradient(self):
         for is_sparse in [True, False]:
             self.ptb_rnn_sort_gradient_cpu_float32(is_sparse)
 
@@ -192,11 +191,6 @@ class TestDygraphPtbRnnSortGradient(unittest.TestCase):
         for key, value in static_param_updated.items():
             np.testing.assert_array_equal(value, dy_param_updated[key])
 
-    def test_ptb_rnn_sort_gradient(self):
-        with _test_eager_guard():
-            self.func_ptb_rnn_sort_gradient()
-        self.func_ptb_rnn_sort_gradient()
-
 
 if __name__ == '__main__':
     unittest.main()

python/paddle/fluid/tests/unittests/test_imperative_recurrent_usage.py

@@ -21,7 +21,6 @@ import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 from paddle.fluid.dygraph.base import to_variable
-from paddle.fluid.framework import _test_eager_guard
 
 
 class RecurrentTest(fluid.Layer):
@@ -62,23 +61,22 @@ class TestRecurrentFeed(unittest.TestCase):
 
         with fluid.dygraph.guard():
             fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
-            with _test_eager_guard():
-                fluid.default_startup_program().random_seed = seed
-                fluid.default_main_program().random_seed = seed
-                original_in1 = to_variable(original_np1)
-                original_in2 = to_variable(original_np2)
-                original_in1.stop_gradient = False
-                original_in2.stop_gradient = False
-                rt = RecurrentTest("RecurrentTest")
-
-                for i in range(3):
-                    sum_out, out = rt(original_in1, original_in2)
-                    original_in1 = out
-                    eager_sum_out_value = sum_out.numpy()
-                    sum_out.backward()
-                    eager_dyout = out.gradient()
-                    original_in1.stop_gradient = True
-                    rt.clear_gradients()
+            fluid.default_startup_program().random_seed = seed
+            fluid.default_main_program().random_seed = seed
+            original_in1 = to_variable(original_np1)
+            original_in2 = to_variable(original_np2)
+            original_in1.stop_gradient = False
+            original_in2.stop_gradient = False
+            rt = RecurrentTest("RecurrentTest")
+
+            for i in range(3):
+                sum_out, out = rt(original_in1, original_in2)
+                original_in1 = out
+                eager_sum_out_value = sum_out.numpy()
+                sum_out.backward()
+                eager_dyout = out.gradient()
+                original_in1.stop_gradient = True
+                rt.clear_gradients()
             fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
 
         with new_program_scope():

python/paddle/fluid/tests/unittests/test_imperative_reinforcement.py

@@ -20,7 +20,6 @@ from test_imperative_base import new_program_scope
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid import core
-from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.optimizer import SGDOptimizer
 
 
@@ -106,12 +105,11 @@ class TestImperativeMnist(unittest.TestCase):
             dy_out, dy_param_init_value, dy_param_value = run_dygraph()
 
         with fluid.dygraph.guard():
-            with _test_eager_guard():
-                (
-                    eager_out,
-                    eager_param_init_value,
-                    eager_param_value,
-                ) = run_dygraph()
+            (
+                eager_out,
+                eager_param_init_value,
+                eager_param_value,
+            ) = run_dygraph()
 
         with new_program_scope():
             paddle.seed(seed)

python/paddle/fluid/tests/unittests/test_imperative_resnet.py

@@ -22,7 +22,6 @@ import paddle
 import paddle.fluid as fluid
 from paddle.fluid import core
 from paddle.fluid.dygraph.base import to_variable
-from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.layer_helper import LayerHelper
 from paddle.nn import BatchNorm
 
@@ -253,7 +252,7 @@ class TestDygraphResnet(unittest.TestCase):
 
         return _reader_imple
 
-    def func_test_resnet_float32(self):
+    def test_resnet_float32(self):
         seed = 90
 
         batch_size = train_parameters["batch_size"]
@@ -462,11 +461,6 @@ class TestDygraphResnet(unittest.TestCase):
             self.assertTrue(np.isfinite(value.all()))
             self.assertFalse(np.isnan(value.any()))
 
-    def test_resnet_float32(self):
-        with _test_eager_guard():
-            self.func_test_resnet_float32()
-        self.func_test_resnet_float32()
-
 
 if __name__ == '__main__':
     paddle.enable_static()

python/paddle/fluid/tests/unittests/test_imperative_resnet_sorted_gradient.py

@@ -22,7 +22,6 @@ import paddle
 import paddle.fluid as fluid
 from paddle.fluid import core
 from paddle.fluid.dygraph.base import to_variable
-from paddle.fluid.framework import _test_eager_guard
 
 batch_size = 8
 train_parameters = {
@@ -73,7 +72,7 @@ def optimizer_setting(params, parameter_list=None):
 
 
 class TestDygraphResnetSortGradient(unittest.TestCase):
-    def func_test_resnet_sort_gradient_float32(self):
+    def test_resnet_sort_gradient_float32(self):
         seed = 90
 
         batch_size = train_parameters["batch_size"]
@@ -266,11 +265,6 @@ class TestDygraphResnetSortGradient(unittest.TestCase):
             self.assertTrue(np.isfinite(value.all()))
             self.assertFalse(np.isnan(value.any()))
 
-    def test_resnet_sort_gradient_float32(self):
-        with _test_eager_guard():
-            self.func_test_resnet_sort_gradient_float32()
-        self.func_test_resnet_sort_gradient_float32()
-
 
 if __name__ == '__main__':
     unittest.main()