diff --git a/python/paddle/fluid/tests/unittests/test_imperative_optimizer.py b/python/paddle/fluid/tests/unittests/test_imperative_optimizer.py index 214b6eb61aed796b6d0c5b81616bf9d039c5ad02..ab1490588088908abdc4938fce9a37577fdd3d26 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_optimizer.py +++ b/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() diff --git a/python/paddle/fluid/tests/unittests/test_imperative_optimizer_v2.py b/python/paddle/fluid/tests/unittests/test_imperative_optimizer_v2.py index f98e1f4d3badcc6c60b2ce5a65c25d774b0d374d..2246cc25a22285ce87162613f24c0c96fc0d49aa 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_optimizer_v2.py +++ b/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() diff --git a/python/paddle/fluid/tests/unittests/test_imperative_partitial_backward.py b/python/paddle/fluid/tests/unittests/test_imperative_partitial_backward.py index 714e27c66208789fe299980f64a2a80f666352e9..5b70a9205f7fff8ee2ee424989200bc93d205196 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_partitial_backward.py +++ b/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() diff --git a/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py b/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py index 6bbf0a70c2e34739abeebd38003d37c92becad06..b9b0115b83818625402db0cbe37cdab69fed052e 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py +++ b/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 diff --git a/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn_sorted_gradient.py b/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn_sorted_gradient.py index fd43a5e917716009e81d441240a426a2f64ad54e..01b1d18070e1480ae22f493ecad9ac0afa7373ff 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn_sorted_gradient.py +++ b/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() diff --git a/python/paddle/fluid/tests/unittests/test_imperative_recurrent_usage.py b/python/paddle/fluid/tests/unittests/test_imperative_recurrent_usage.py index 26364bf1c9841066dd7b1353c8c09eb5e3008d1d..393b0067afeb98d3457d3b0e9fe244c9848f5532 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_recurrent_usage.py +++ b/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(): diff --git a/python/paddle/fluid/tests/unittests/test_imperative_reinforcement.py b/python/paddle/fluid/tests/unittests/test_imperative_reinforcement.py index 06982a0fc3da9e5dd5037af717dc9c06d443d45d..75043ff30b169ea8be3d5227e9b4a232962cee1c 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_reinforcement.py +++ b/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) diff --git a/python/paddle/fluid/tests/unittests/test_imperative_resnet.py b/python/paddle/fluid/tests/unittests/test_imperative_resnet.py index fcff2fc7268aaa7fc36c03ec5c6c72033c9c6430..b20ceb091b017f9e55d8bf6aace2086831607d61 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_resnet.py +++ b/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() diff --git a/python/paddle/fluid/tests/unittests/test_imperative_resnet_sorted_gradient.py b/python/paddle/fluid/tests/unittests/test_imperative_resnet_sorted_gradient.py index f28631d0adab21e8e9293cdfca8f2ddb1e841f15..798890a4898e8aef61faaa0ba245f525d0d2f471 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_resnet_sorted_gradient.py +++ b/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()