diff --git a/python/paddle/fluid/tests/unittests/test_pool2d_api.py b/python/paddle/fluid/tests/unittests/test_pool2d_api.py index b7dcbaf9b5d887aa0b28e9f41b1a556f2d1ec590..44ef18605ed2aed1f9d48a37d77b51e109cb0095 100644 --- a/python/paddle/fluid/tests/unittests/test_pool2d_api.py +++ b/python/paddle/fluid/tests/unittests/test_pool2d_api.py @@ -24,7 +24,6 @@ from test_pool2d_op import ( import paddle import paddle.fluid as fluid import paddle.fluid.core as core -from paddle.fluid.framework import _test_eager_guard from paddle.nn.functional import avg_pool2d, max_pool2d @@ -372,10 +371,6 @@ class TestPool2D_API(unittest.TestCase): self.check_max_dygraph_ceilmode_results(place) self.check_max_dygraph_nhwc_results(place) - def test_dygraph_api(self): - with _test_eager_guard(): - self.test_pool2d() - class TestPool2DError_API(unittest.TestCase): def test_error_api(self): @@ -602,10 +597,6 @@ class TestPool2DError_API(unittest.TestCase): self.assertRaises(ValueError, run_stride_out_of_range) - def test_dygraph_api(self): - with _test_eager_guard(): - self.test_error_api() - if __name__ == '__main__': unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_pool3d_api.py b/python/paddle/fluid/tests/unittests/test_pool3d_api.py index 09fb7210f87c846e067c218450b1aea96227ff45..961f0b5c569f043f42705dd10719838229c89e02 100644 --- a/python/paddle/fluid/tests/unittests/test_pool3d_api.py +++ b/python/paddle/fluid/tests/unittests/test_pool3d_api.py @@ -24,7 +24,6 @@ from test_pool3d_op import ( import paddle import paddle.fluid as fluid import paddle.fluid.core as core -from paddle.fluid.framework import _test_eager_guard from paddle.nn.functional import avg_pool3d, max_pool3d @@ -367,10 +366,6 @@ class TestPool3D_API(unittest.TestCase): self.check_max_dygraph_ndhwc_results(place) self.check_max_dygraph_ceilmode_results(place) - def test_dygraph_api(self): - with _test_eager_guard(): - self.test_pool3d() - class TestPool3DError_API(unittest.TestCase): def test_error_api(self): @@ -568,10 +563,6 @@ class TestPool3DError_API(unittest.TestCase): self.assertRaises(ValueError, run_size_out_of_range) - def test_dygraph_api(self): - with _test_eager_guard(): - self.test_error_api() - if __name__ == '__main__': unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_prelu_op.py b/python/paddle/fluid/tests/unittests/test_prelu_op.py index 50b703bc27c7252485b03f9b8a5c4122941609c4..9c95d5b946ce49508b190ab00be1747efed2798b 100644 --- a/python/paddle/fluid/tests/unittests/test_prelu_op.py +++ b/python/paddle/fluid/tests/unittests/test_prelu_op.py @@ -22,7 +22,6 @@ import paddle.fluid as fluid import paddle.fluid.core as core import paddle.nn.functional as F from paddle.fluid import Program -from paddle.fluid.framework import _test_eager_guard def ref_prelu(x, weight): @@ -79,10 +78,6 @@ class TestFunctionalPReluAPI(unittest.TestCase): self.dygraph_check(self.weight_np_0) self.dygraph_check(self.weight_np_1) - def test_dygraph_api_eager(self): - with _test_eager_guard(): - self.test_dygraph_api() - def test_error(self): with paddle.static.program_guard(paddle.static.Program()): weight_fp32 = paddle.fluid.data( diff --git a/python/paddle/fluid/tests/unittests/test_prune_gate_by_capacity_op.py b/python/paddle/fluid/tests/unittests/test_prune_gate_by_capacity_op.py index 62d9a4ea1cb7f92c76ba909ff7e8ec5a37376144..e52d67185e374a2567b4729307076f09886cdd4b 100644 --- a/python/paddle/fluid/tests/unittests/test_prune_gate_by_capacity_op.py +++ b/python/paddle/fluid/tests/unittests/test_prune_gate_by_capacity_op.py @@ -19,7 +19,6 @@ import numpy as np import paddle from paddle.distributed.models.moe import utils from paddle.fluid import core -from paddle.fluid.framework import _test_eager_guard def count(x, upper_num): @@ -115,7 +114,7 @@ class TestPruneGateByCapacityAPI1(unittest.TestCase): ) assert_allclose(res[0], self.out, self.n_expert) - def func_dygraph_api(self): + def test_dygraph_api(self): paddle.disable_static(self.place) gate_idx_tensor = paddle.to_tensor(self.gate_idx) expert_count_tensor = paddle.to_tensor(self.expert_count) @@ -124,11 +123,6 @@ class TestPruneGateByCapacityAPI1(unittest.TestCase): ) assert_allclose(out.numpy(), self.out, self.n_expert) - def test_dygraph_api(self): - with _test_eager_guard(): - self.func_dygraph_api() - self.func_dygraph_api() - @unittest.skipIf( not core.is_compiled_with_cuda(), "core is not compiled with CUDA" diff --git a/python/paddle/fluid/tests/unittests/test_pylayer_op.py b/python/paddle/fluid/tests/unittests/test_pylayer_op.py index 5e78a40097f9629a067ed2660b47fa11de7c4001..c44d83df70dff116345b6e2c8c9032ca269afa5b 100644 --- a/python/paddle/fluid/tests/unittests/test_pylayer_op.py +++ b/python/paddle/fluid/tests/unittests/test_pylayer_op.py @@ -18,7 +18,7 @@ import numpy as np import paddle from paddle.autograd.py_layer import EagerPyLayer, LegacyPyLayer -from paddle.fluid.framework import _test_eager_guard, in_dygraph_mode +from paddle.fluid.framework import in_dygraph_mode class FakeTensor(paddle.fluid.core.VarBase): @@ -27,7 +27,7 @@ class FakeTensor(paddle.fluid.core.VarBase): class TestPyLayer(unittest.TestCase): - def func_test_simple_pylayer_multiple_output(self): + def test_simple_pylayer_multiple_output(self): class tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, x1, x2, func1, func2=paddle.square): @@ -59,12 +59,7 @@ class TestPyLayer(unittest.TestCase): np.max(np.abs((input1.grad.numpy() - input2.grad.numpy()))) < 1e-10 ) - def test_simple_pylayer_multiple_output(self): - with _test_eager_guard(): - self.func_test_simple_pylayer_multiple_output() - self.func_test_simple_pylayer_multiple_output() - - def func_test_simple_pylayer_return_none_with_no_grad(self): + def test_simple_pylayer_return_none_with_no_grad(self): class tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, x1, x2, func1, func2=paddle.square): @@ -100,12 +95,7 @@ class TestPyLayer(unittest.TestCase): np.max(np.abs((input1.grad.numpy() - input2.grad.numpy()))) < 1e-10 ) - def test_simple_pylayer_return_none_with_no_grad(self): - with _test_eager_guard(): - self.func_test_simple_pylayer_return_none_with_no_grad() - self.func_test_simple_pylayer_return_none_with_no_grad() - - def func_test_simple_pylayer_single_output(self): + def test_simple_pylayer_single_output(self): class tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, x1, func1, func2=paddle.square): @@ -133,12 +123,7 @@ class TestPyLayer(unittest.TestCase): np.max(np.abs((input1.grad.numpy() - input2.grad.numpy()))) < 1e-10 ) - def test_simple_pylayer_single_output(self): - with _test_eager_guard(): - self.func_test_simple_pylayer_single_output() - self.func_test_simple_pylayer_single_output() - - def func_test_pylayer_num_output_match(self): + def test_pylayer_num_output_match(self): class tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward( @@ -160,12 +145,7 @@ class TestPyLayer(unittest.TestCase): with self.assertRaises(ValueError): z.mean().backward() - def test_pylayer_num_output_match(self): - with _test_eager_guard(): - self.func_test_pylayer_num_output_match() - self.func_test_pylayer_num_output_match() - - def func_test_pylayer_dtype(self): + def test_pylayer_dtype(self): class tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, x, dtype): @@ -195,12 +175,7 @@ class TestPyLayer(unittest.TestCase): z.sum().backward() self.assertIsNotNone(input1.grad) - def test_pylayer_dtype(self): - with _test_eager_guard(): - self.func_test_pylayer_dtype() - self.func_test_pylayer_dtype() - - def func_test_pylayer_Exception_forward(self): + def test_pylayer_Exception_forward(self): class Layer_None1(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, *args): @@ -263,12 +238,7 @@ class TestPyLayer(unittest.TestCase): with self.assertRaises(NotImplementedError): z = Layer_no_fw.apply(input1) - def test_pylayer_Exception_forward(self): - with _test_eager_guard(): - self.func_test_pylayer_Exception_forward() - self.func_test_pylayer_Exception_forward() - - def func_test_pylayer_nograd(self): + def test_pylayer_nograd(self): class tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, x1, func1, func2=paddle.square, xx=None): @@ -286,12 +256,7 @@ class TestPyLayer(unittest.TestCase): z.mean().backward() self.assertIsNone(z.grad) - def test_pylayer_nograd(self): - with _test_eager_guard(): - self.func_test_pylayer_nograd() - self.func_test_pylayer_nograd() - - def func_test_pylayer_Exception_bk(self): + def test_pylayer_Exception_bk(self): class Layer_bk_none1( EagerPyLayer if in_dygraph_mode() else LegacyPyLayer ): @@ -396,12 +361,7 @@ class TestPyLayer(unittest.TestCase): z = z[0] + z[1] z.mean().backward() - def test_pylayer_Exception_bk(self): - with _test_eager_guard(): - self.func_test_pylayer_Exception_bk() - self.func_test_pylayer_Exception_bk() - - def func_test_pylayer_bk_return_none(self): + def test_pylayer_bk_return_none(self): class Layer_bk_none1( EagerPyLayer if in_dygraph_mode() else LegacyPyLayer ): @@ -442,12 +402,7 @@ class TestPyLayer(unittest.TestCase): with self.assertRaises(ValueError): z.mean().backward() - def test_pylayer_bk_return_none(self): - with _test_eager_guard(): - self.func_test_pylayer_bk_return_none() - self.func_test_pylayer_bk_return_none() - - def func_test_pylayer_inplace(self): + def test_pylayer_inplace(self): class cus_tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, x): @@ -475,115 +430,98 @@ class TestPyLayer(unittest.TestCase): z.backward() self.assertIsNotNone(data.grad) - def test_pylayer_inplace(self): - with _test_eager_guard(): - self.func_test_pylayer_inplace() - self.func_test_pylayer_inplace() - def test_pylayer_inplace_backward_error(self): - with _test_eager_guard(): + class cus_tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): + @staticmethod + def forward(ctx, x): + return x - class cus_tanh( - EagerPyLayer if in_dygraph_mode() else LegacyPyLayer - ): - @staticmethod - def forward(ctx, x): - return x - - @staticmethod - def backward(ctx, dy): - return dy - - class Layer(paddle.nn.Layer): - def __init__(self): - super().__init__() - - def forward(self, data): - var_b = data**2 - var_c = var_b**2 - z = cus_tanh.apply(var_b) - loss = paddle.nn.functional.relu(var_c) - return loss - - data = paddle.ones([2, 3], dtype="float64") + @staticmethod + def backward(ctx, dy): + return dy + + class Layer(paddle.nn.Layer): + def __init__(self): + super().__init__() + + def forward(self, data): + var_b = data**2 + var_c = var_b**2 + z = cus_tanh.apply(var_b) + loss = paddle.nn.functional.relu(var_c) + return loss + + data = paddle.ones([2, 3], dtype="float64") + data.stop_gradient = False + layer = Layer() + z = layer(data) + with self.assertRaisesRegexp( + RuntimeError, + "received tensor_version:{} != wrapper_version_snapshot:{}".format( + 1, 0 + ), + ): + z.backward() + + def test_pylayer_inplace_backward_success_1(self): + class cus_tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): + @staticmethod + def forward(ctx, x): + return x + + @staticmethod + def backward(ctx, dy): + return dy + + class Layer(paddle.nn.Layer): + def __init__(self): + super().__init__() + + def forward(self, data): + var_b = data**2 + var_c = cus_tanh.apply(var_b) + var_d = var_c**2 + loss = var_d.sum() + return loss + + for i in range(2): + data = paddle.ones([2, 3], dtype="float64") / (i + 1) data.stop_gradient = False layer = Layer() z = layer(data) - with self.assertRaisesRegexp( - RuntimeError, - "received tensor_version:{} != wrapper_version_snapshot:{}".format( - 1, 0 - ), - ): - z.backward() + z.backward() + self.assertIsNotNone(data.grad) - def test_pylayer_inplace_backward_success_1(self): - with _test_eager_guard(): + def test_pylayer_inplace_backward_success_2(self): + class cus_tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): + @staticmethod + def forward(ctx, x): + return x - class cus_tanh( - EagerPyLayer if in_dygraph_mode() else LegacyPyLayer - ): - @staticmethod - def forward(ctx, x): - return x - - @staticmethod - def backward(ctx, dy): - return dy - - class Layer(paddle.nn.Layer): - def __init__(self): - super().__init__() - - def forward(self, data): - var_b = data**2 - var_c = cus_tanh.apply(var_b) - var_d = var_c**2 - loss = var_d.sum() - return loss - - for i in range(2): - data = paddle.ones([2, 3], dtype="float64") / (i + 1) - data.stop_gradient = False - layer = Layer() - z = layer(data) - z.backward() - self.assertIsNotNone(data.grad) + @staticmethod + def backward(ctx, dy): + return dy - def test_pylayer_inplace_backward_success_2(self): - with _test_eager_guard(): + class Layer(paddle.nn.Layer): + def __init__(self): + super().__init__() - class cus_tanh( - EagerPyLayer if in_dygraph_mode() else LegacyPyLayer - ): - @staticmethod - def forward(ctx, x): - return x - - @staticmethod - def backward(ctx, dy): - return dy - - class Layer(paddle.nn.Layer): - def __init__(self): - super().__init__() - - def forward(self, data): - var_b = data**2 - var_c = cus_tanh.apply(var_b) - var_d = var_c + var_c - loss = var_d.sum() - return loss - - for i in range(2): - data = paddle.ones([2, 3], dtype="float64") / (i + 1) - data.stop_gradient = False - layer = Layer() - z = layer(data) - z.backward() - self.assertIsNotNone(data.grad) + def forward(self, data): + var_b = data**2 + var_c = cus_tanh.apply(var_b) + var_d = var_c + var_c + loss = var_d.sum() + return loss - def func_test_pylayer_inplace_and_leaf_exception(self): + for i in range(2): + data = paddle.ones([2, 3], dtype="float64") / (i + 1) + data.stop_gradient = False + layer = Layer() + z = layer(data) + z.backward() + self.assertIsNotNone(data.grad) + + def test_pylayer_inplace_and_leaf_exception(self): class cus_pylayer_op( EagerPyLayer if in_dygraph_mode() else LegacyPyLayer ): @@ -611,12 +549,7 @@ class TestPyLayer(unittest.TestCase): with self.assertRaises(ValueError): z = layer(data) - def test_pylayer_inplace_and_leaf_exception(self): - with _test_eager_guard(): - self.func_test_pylayer_inplace_and_leaf_exception() - self.func_test_pylayer_inplace_and_leaf_exception() - - def func_test_backward_in_backward(self): + def test_backward_in_backward(self): class cus_tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, x): @@ -641,12 +574,7 @@ class TestPyLayer(unittest.TestCase): z = paddle.tanh(data) z = cus_tanh.apply(data) - def test_backward_in_backward(self): - with _test_eager_guard(): - self.func_test_backward_in_backward() - self.func_test_backward_in_backward() - - def func_test_return_to_tensor(self): + def test_return_to_tensor(self): class Tanh(EagerPyLayer if in_dygraph_mode() else LegacyPyLayer): @staticmethod def forward(ctx, x1): @@ -668,90 +596,77 @@ class TestPyLayer(unittest.TestCase): z, number, none_item, string_item, tensor1 = Tanh.apply(x1=input1) z.mean().backward() - def test_return_to_tensor(self): - with _test_eager_guard(): - self.func_test_return_to_tensor() - self.func_test_return_to_tensor() - def test_materialize_grads(self): - with _test_eager_guard(): - - class Tanh(EagerPyLayer): - @staticmethod - def forward(ctx, x): - ctx.mark_not_inplace(x) - return x, x + x + class Tanh(EagerPyLayer): + @staticmethod + def forward(ctx, x): + ctx.mark_not_inplace(x) + return x, x + x - @staticmethod - def backward(ctx, grad, grad2): - self.assertEqual(grad2, paddle.zeros([1])) - return grad + @staticmethod + def backward(ctx, grad, grad2): + self.assertEqual(grad2, paddle.zeros([1])) + return grad - x = paddle.ones([1], dtype="float64") - x.stop_gradient = False - Tanh.apply(x)[0].backward() + x = paddle.ones([1], dtype="float64") + x.stop_gradient = False + Tanh.apply(x)[0].backward() def test_dont_materialize_grads(self): - with _test_eager_guard(): - - class Tanh(EagerPyLayer): - @staticmethod - def forward(ctx, x): - ctx.mark_not_inplace(x) - ctx.set_materialize_grads(False) - return x, x + x + class Tanh(EagerPyLayer): + @staticmethod + def forward(ctx, x): + ctx.mark_not_inplace(x) + ctx.set_materialize_grads(False) + return x, x + x - @staticmethod - def backward(ctx, grad, grad2): - self.assertIsNone(grad2) - return grad + @staticmethod + def backward(ctx, grad, grad2): + self.assertIsNone(grad2) + return grad - x = paddle.ones([1], dtype="float64") - x.stop_gradient = False - Tanh.apply(x)[0].backward() + x = paddle.ones([1], dtype="float64") + x.stop_gradient = False + Tanh.apply(x)[0].backward() def test_mark_non_differentiable(self): - with _test_eager_guard(): - - class Tanh(EagerPyLayer): - @staticmethod - def forward(ctx, x): - a = x + x - ctx.mark_non_differentiable(a) - return a + class Tanh(EagerPyLayer): + @staticmethod + def forward(ctx, x): + a = x + x + ctx.mark_non_differentiable(a) + return a - @staticmethod - def backward(ctx, grad): - self.assertTrue(False) # should not be call - return paddle.ones([1], dtype="float64") + @staticmethod + def backward(ctx, grad): + self.assertTrue(False) # should not be call + return paddle.ones([1], dtype="float64") - x = paddle.ones([1], dtype="float64") - x.stop_gradient = False - y = Tanh.apply(x) - y.sum().backward() + x = paddle.ones([1], dtype="float64") + x.stop_gradient = False + y = Tanh.apply(x) + y.sum().backward() def test_mark_non_differentiable2(self): - with _test_eager_guard(): - - class Tanh(EagerPyLayer): - @staticmethod - def forward(ctx, x): - a = x + x - b = x + x + x - ctx.mark_non_differentiable(a) - return a, b + class Tanh(EagerPyLayer): + @staticmethod + def forward(ctx, x): + a = x + x + b = x + x + x + ctx.mark_non_differentiable(a) + return a, b - @staticmethod - def backward(ctx, grad_a, grad_b): - self.assertEqual(grad_a, paddle.zeros([1])) - self.assertEqual(grad_b, paddle.ones([1], dtype="float64")) - return grad_b + @staticmethod + def backward(ctx, grad_a, grad_b): + self.assertEqual(grad_a, paddle.zeros([1])) + self.assertEqual(grad_b, paddle.ones([1], dtype="float64")) + return grad_b - x = paddle.ones([1], dtype="float64") - x.stop_gradient = False - a, b = Tanh.apply(x) - b.sum().backward() - self.assertEqual(x.grad, paddle.ones([1], dtype="float64")) + x = paddle.ones([1], dtype="float64") + x.stop_gradient = False + a, b = Tanh.apply(x) + b.sum().backward() + self.assertEqual(x.grad, paddle.ones([1], dtype="float64")) class TestPyLayerReturnType(unittest.TestCase): @@ -832,9 +747,9 @@ class TestPyLayerReturnType(unittest.TestCase): input1 = paddle.randn([3, 2]) input1.stop_gradient = False - y, _ = Tanh.apply(input1, 1 + input1) with self.assertRaises(ValueError): + y, _ = Tanh.apply(input1, 1 + input1) y.mean().backward() def test_backward_return_fake_tensor(self): @@ -849,9 +764,9 @@ class TestPyLayerReturnType(unittest.TestCase): input1 = paddle.randn([3, 2]) input1.stop_gradient = False - y, _ = Tanh.apply(input1) with self.assertRaises(ValueError): + y, _ = Tanh.apply(input1) y.mean().backward() diff --git a/python/paddle/fluid/tests/unittests/test_randint_op.py b/python/paddle/fluid/tests/unittests/test_randint_op.py index 6289d814367340090236229fb0173eb6e78caa37..9cf21bcee7c6974c58afc71f0b327f1f9ce7e18e 100644 --- a/python/paddle/fluid/tests/unittests/test_randint_op.py +++ b/python/paddle/fluid/tests/unittests/test_randint_op.py @@ -20,7 +20,6 @@ from op_test import OpTest import paddle import paddle.fluid as fluid from paddle.fluid import core -from paddle.fluid.framework import _test_eager_guard from paddle.static import Program, program_guard paddle.enable_static() @@ -52,10 +51,6 @@ class TestRandintOp(OpTest): hist, prob = self.output_hist(np.array(outs[0])) np.testing.assert_allclose(hist, prob, rtol=0, atol=0.001) - def test_check_output_eager(self): - with _test_eager_guard(): - self.test_check_output() - class TestRandintOpError(unittest.TestCase): def test_errors(self): @@ -71,10 +66,6 @@ class TestRandintOpError(unittest.TestCase): TypeError, paddle.randint, 5, shape=[shape_tensor] ) - def test_errors_eager(self): - with _test_eager_guard(): - self.test_errors() - class TestRandintOp_attr_tensorlist(OpTest): def setUp(self): @@ -100,10 +91,6 @@ class TestRandintOp_attr_tensorlist(OpTest): hist, prob = self.output_hist(np.array(outs[0])) np.testing.assert_allclose(hist, prob, rtol=0, atol=0.001) - def test_check_output_eager(self): - with _test_eager_guard(): - self.test_check_output() - class TestRandint_attr_tensor(OpTest): def setUp(self): @@ -123,10 +110,6 @@ class TestRandint_attr_tensor(OpTest): hist, prob = self.output_hist(np.array(outs[0])) np.testing.assert_allclose(hist, prob, rtol=0, atol=0.001) - def test_check_output_eager(self): - with _test_eager_guard(): - self.test_check_output() - # Test python API class TestRandintAPI(unittest.TestCase): @@ -167,23 +150,10 @@ class TestRandintAPI(unittest.TestCase): fetch_list=[out1, out2, out3, out4, out5], ) - def test_api_eager(self): - with _test_eager_guard(): - self.test_api() - class TestRandintImperative(unittest.TestCase): - def test_api(self): + def test_case(self): paddle.disable_static() - - self.run_test_case() - - with _test_eager_guard(): - self.run_test_case() - - paddle.enable_static() - - def run_test_case(self): n = 10 x1 = paddle.randint(n, shape=[10], dtype="int32") x2 = paddle.tensor.randint(n) @@ -191,6 +161,7 @@ class TestRandintImperative(unittest.TestCase): for i in [x1, x2, x3]: for j in i.numpy().tolist(): self.assertTrue((j >= 0 and j < n)) + paddle.enable_static() class TestRandomValue(unittest.TestCase): @@ -208,9 +179,6 @@ class TestRandomValue(unittest.TestCase): self.run_test_case() - with _test_eager_guard(): - self.run_test_case() - paddle.enable_static() def run_test_case(self): diff --git a/python/paddle/fluid/tests/unittests/test_random_routing_op.py b/python/paddle/fluid/tests/unittests/test_random_routing_op.py index e9320e5fa72b84546c1fd066376cf31f13219f5c..953e3ccff63c052790419e122510fb8b8204c1b1 100644 --- a/python/paddle/fluid/tests/unittests/test_random_routing_op.py +++ b/python/paddle/fluid/tests/unittests/test_random_routing_op.py @@ -19,7 +19,6 @@ import numpy as np import paddle import paddle.fluid.core as core from paddle.distributed.models.moe import utils -from paddle.fluid.framework import _test_eager_guard def random_routing(topk_idx, topk_value, prob, topk=2): @@ -54,7 +53,7 @@ class TestNumberCountAPIFp32(unittest.TestCase): ) self.place = paddle.CUDAPlace(0) - def func_api_dygraph(self): + def test_api_dygraph(self): paddle.disable_static() x = paddle.to_tensor(self.x) value = paddle.to_tensor(self.topk_value) @@ -62,11 +61,6 @@ class TestNumberCountAPIFp32(unittest.TestCase): out = utils._random_routing(x, value, prob) assert np.allclose(out.numpy(), self.out) - def test_api_dygraph(self): - with _test_eager_guard(): - self.func_api_dygraph() - self.func_api_dygraph() - @unittest.skipIf( not core.is_compiled_with_cuda(), "core is not compiled with CUDA" diff --git a/python/paddle/fluid/tests/unittests/test_randperm_op.py b/python/paddle/fluid/tests/unittests/test_randperm_op.py index 307541cb897a48fecd8bee4dc4f47c6773ea3762..70e628879edbae4751e226f94a97c69354bbca89 100644 --- a/python/paddle/fluid/tests/unittests/test_randperm_op.py +++ b/python/paddle/fluid/tests/unittests/test_randperm_op.py @@ -19,7 +19,6 @@ from op_test import OpTest import paddle import paddle.fluid.core as core -from paddle.fluid.framework import _test_eager_guard from paddle.static import Program, program_guard @@ -83,10 +82,6 @@ class TestRandpermOp(OpTest): check_randperm_out(self.n, out_np), msg=error_msg(out_np) ) - def test_eager(self): - with _test_eager_guard(): - self.test_check_output() - class TestRandpermOpN(TestRandpermOp): def init_attrs(self): @@ -153,13 +148,12 @@ class TestRandpermEager(unittest.TestCase): def test_out(self): paddle.disable_static() n = 10 - with _test_eager_guard(): - for dtype in ['int32', np.int64, 'float32', 'float64']: - data_p = paddle.randperm(n, dtype) - data_np = data_p.numpy() - self.assertTrue( - check_randperm_out(n, data_np), msg=error_msg(data_np) - ) + for dtype in ['int32', np.int64, 'float32', 'float64']: + data_p = paddle.randperm(n, dtype) + data_np = data_p.numpy() + self.assertTrue( + check_randperm_out(n, data_np), msg=error_msg(data_np) + ) paddle.enable_static() diff --git a/python/paddle/fluid/tests/unittests/test_reset_grad_inplace_version.py b/python/paddle/fluid/tests/unittests/test_reset_grad_inplace_version.py index 24cfe0a51df20449574987989deaf74b0b776f82..4e86e3e0c378a079764493a2c1214e8627b3c40f 100644 --- a/python/paddle/fluid/tests/unittests/test_reset_grad_inplace_version.py +++ b/python/paddle/fluid/tests/unittests/test_reset_grad_inplace_version.py @@ -17,7 +17,6 @@ import numpy as np import paddle from paddle import _legacy_C_ops -from paddle.fluid.framework import _test_eager_guard paddle.set_device('cpu') @@ -34,7 +33,7 @@ def clear_grad_test_0(w, a): class TestInplaceAndClearGradient(unittest.TestCase): - def func_test(self): + def test_inplace_n_clear_grad(self): input_data = np.ones([1, 1]) w = paddle.to_tensor(input_data, 'float32', stop_gradient=False) @@ -49,11 +48,6 @@ class TestInplaceAndClearGradient(unittest.TestCase): out.backward() assert w.grad[0] == 0.15 - def test(self): - with _test_eager_guard(): - self.func_test() - self.func_test() - # Test 2 class Counter: @@ -76,7 +70,7 @@ def clear_grad_test_1(w, c): class TestInplaceClearGradAccumulation(unittest.TestCase): - def func_test(self): + def test_inplace_clear_grad_accum(self): input_data = np.ones([1, 1]) w = paddle.to_tensor(input_data, 'float32', stop_gradient=False) c = Counter() @@ -98,14 +92,9 @@ class TestInplaceClearGradAccumulation(unittest.TestCase): assert c.num_calls == 1 c.num_calls = 0 - def test(self): - with _test_eager_guard(): - self.func_test() - self.func_test() - class TestInplaceClearGradAccumulationAlt(unittest.TestCase): - def func_test(self): + def test_inplace_clear_grad_accum(self): input_data = np.ones([1, 1]) w = paddle.to_tensor(input_data, 'float32', stop_gradient=False) out = _legacy_C_ops.scale(w, 'scale', 0.1) @@ -116,11 +105,6 @@ class TestInplaceClearGradAccumulationAlt(unittest.TestCase): assert w.grad._inplace_version() == 1 - def test(self): - with _test_eager_guard(): - self.func_test() - self.func_test() - if __name__ == '__main__': unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_retain_graph.py b/python/paddle/fluid/tests/unittests/test_retain_graph.py index ad9739f1986ed027cdbe33fdbbe8532600925110..eb6ab6c1e2487d4e1e8a7f30b302e52c7f9b36ee 100644 --- a/python/paddle/fluid/tests/unittests/test_retain_graph.py +++ b/python/paddle/fluid/tests/unittests/test_retain_graph.py @@ -150,16 +150,11 @@ class TestRetainGraph(unittest.TestCase): loss_g.backward() optim_g.minimize(loss_g) - def func_retain(self): + def test_retain(self): self.run_retain(need_retain=True) if not fluid.framework.in_dygraph_mode(): self.assertRaises(RuntimeError, self.run_retain, need_retain=False) - def test_retain(self): - with fluid.framework._test_eager_guard(): - self.func_retain() - self.func_retain() - if __name__ == '__main__': unittest.main()