diff --git a/python/paddle/fluid/tests/unittests/test_sum_op.py b/python/paddle/fluid/tests/unittests/test_sum_op.py index 55ce3b31010ab7c429fa06bbfae207babaf8968a..4e750d4b86863562881a587a301f81bf0fd85a23 100644 --- a/python/paddle/fluid/tests/unittests/test_sum_op.py +++ b/python/paddle/fluid/tests/unittests/test_sum_op.py @@ -26,7 +26,6 @@ import paddle.fluid.core as core import paddle.fluid.layers as layers import paddle.inference as paddle_infer from paddle import enable_static -from paddle.fluid.framework import _test_eager_guard from paddle.fluid.op import Operator from paddle.fluid.tests.unittests.op_test import ( OpTest, @@ -376,27 +375,24 @@ class API_Test_Add_n(unittest.TestCase): def test_dygraph_api(self): with fluid.dygraph.guard(): - with _test_eager_guard(): - input0 = paddle.ones(shape=[2, 3], dtype='float32') - input1 = paddle.ones(shape=[2, 3], dtype='float32') - input0.stop_gradient = False - input1.stop_gradient = False - expected_result = np.empty((2, 3)) - expected_result.fill(2) - sum_value = paddle.add_n([input0, input1]) - self.assertEqual( - (sum_value.numpy() == expected_result).all(), True - ) + input0 = paddle.ones(shape=[2, 3], dtype='float32') + input1 = paddle.ones(shape=[2, 3], dtype='float32') + input0.stop_gradient = False + input1.stop_gradient = False + expected_result = np.empty((2, 3)) + expected_result.fill(2) + sum_value = paddle.add_n([input0, input1]) + self.assertEqual((sum_value.numpy() == expected_result).all(), True) - expected_grad_result = np.empty((2, 3)) - expected_grad_result.fill(1) - sum_value.backward() - self.assertEqual( - (input0.grad.numpy() == expected_grad_result).all(), True - ) - self.assertEqual( - (input1.grad.numpy() == expected_grad_result).all(), True - ) + expected_grad_result = np.empty((2, 3)) + expected_grad_result.fill(1) + sum_value.backward() + self.assertEqual( + (input0.grad.numpy() == expected_grad_result).all(), True + ) + self.assertEqual( + (input1.grad.numpy() == expected_grad_result).all(), True + ) def test_add_n_and_add_and_grad(self): with fluid.dygraph.guard(): diff --git a/python/paddle/fluid/tests/unittests/test_switch_autotune.py b/python/paddle/fluid/tests/unittests/test_switch_autotune.py index 5f54b567ba8cd72d64277b6d72a5b7725278e8e4..69adf7246e7a81b601029ccea6512ae56943306e 100644 --- a/python/paddle/fluid/tests/unittests/test_switch_autotune.py +++ b/python/paddle/fluid/tests/unittests/test_switch_autotune.py @@ -112,21 +112,11 @@ class TestDygraphAutoTuneStatus(TestAutoTune): expected_res = self.get_expected_res(i, enable_autotune) self.check_status(expected_res) - def func_enable_autotune(self): - self.run_program(enable_autotune=True) - def test_enable_autotune(self): - with paddle.fluid.framework._test_eager_guard(): - self.func_enable_autotune() - self.func_enable_autotune() - - def func_disable_autotune(self): - self.run_program(enable_autotune=False) + self.run_program(enable_autotune=True) def test_disable_autotune(self): - with paddle.fluid.framework._test_eager_guard(): - self.func_disable_autotune() - self.func_disable_autotune() + self.run_program(enable_autotune=False) class TestStaticAutoTuneStatus(TestAutoTune): diff --git a/python/paddle/fluid/tests/unittests/test_tensor_fill_.py b/python/paddle/fluid/tests/unittests/test_tensor_fill_.py index effe4461c76eb63857ed051f583b8dcc86e4bc9f..37e45e69b96592e978d7a260cd8118d340c88a95 100644 --- a/python/paddle/fluid/tests/unittests/test_tensor_fill_.py +++ b/python/paddle/fluid/tests/unittests/test_tensor_fill_.py @@ -18,14 +18,13 @@ import numpy as np import paddle import paddle.fluid as fluid -from paddle.fluid.framework import _test_eager_guard class TensorFill_Test(unittest.TestCase): def setUp(self): self.shape = [32, 32] - def func_test_tensor_fill_true(self): + def test_tensor_fill_true(self): typelist = ['float32', 'float64', 'int32', 'int64', 'float16'] places = [fluid.CPUPlace()] if fluid.core.is_compiled_with_cuda(): @@ -49,12 +48,8 @@ class TensorFill_Test(unittest.TestCase): tensor.fill_(var) # var type is basic type in typelist self.assertEqual((tensor.numpy() == target).all(), True) - def test_tensor_fill_true(self): - with _test_eager_guard(): - self.func_test_tensor_fill_true() - self.func_test_tensor_fill_true() - - def func_test_tensor_fill_backward(self): + def test_tensor_fill_backward(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) typelist = ['float32'] places = [fluid.CPUPlace()] if fluid.core.is_compiled_with_cuda(): @@ -79,26 +74,15 @@ class TensorFill_Test(unittest.TestCase): loss.backward() self.assertEqual((y.grad.numpy() == 0).all().item(), True) - - def test_tensor_fill_backward(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_test_tensor_fill_backward() - self.func_test_tensor_fill_backward() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_test_errors(self): + def test_errors(self): def test_list(): x = paddle.to_tensor([2, 3, 4]) x.fill_([1]) self.assertRaises(TypeError, test_list) - def test_errors(self): - with _test_eager_guard(): - self.func_test_errors() - self.func_test_errors() - if __name__ == '__main__': unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_.py b/python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_.py index 931c85a7644e287b6f9be830cd5ba3991f9bc654..a83f5b8e5aa0b15731d338643db310537022305d 100644 --- a/python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_.py +++ b/python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_.py @@ -18,11 +18,11 @@ import numpy as np import paddle import paddle.fluid as fluid -from paddle.fluid.framework import _test_eager_guard class TensorFillDiagonal_Test(unittest.TestCase): - def func_dim2_normal(self): + def test_dim2_normal(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array([[1, 2, 2], [2, 1, 2], [2, 2, 1]]).astype( 'float32' ) @@ -55,15 +55,10 @@ class TensorFillDiagonal_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_dim2_normal(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_dim2_normal() - self.func_dim2_normal() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_offset(self): + def test_offset(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array([[2, 2, 1], [2, 2, 2], [2, 2, 2]]).astype( 'float32' ) @@ -96,15 +91,9 @@ class TensorFillDiagonal_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_offset(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_offset() - self.func_offset() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_bool(self): + def test_bool(self): expected_np = np.array( [[False, True, True], [True, False, True], [True, True, False]] ) @@ -126,12 +115,8 @@ class TensorFillDiagonal_Test(unittest.TestCase): self.assertEqual((x.numpy() == expected_np).all(), True) - def test_bool(self): - with _test_eager_guard(): - self.func_bool() - self.func_bool() - - def func_dim2_unnormal_wrap(self): + def test_dim2_unnormal_wrap(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array( [ [1, 2, 2], @@ -180,15 +165,10 @@ class TensorFillDiagonal_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_dim2_unnormal_wrap(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_dim2_unnormal_wrap() - self.func_dim2_unnormal_wrap() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_dim2_unnormal_unwrap(self): + def test_dim2_unnormal_unwrap(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array( [ [1, 2, 2], @@ -237,15 +217,10 @@ class TensorFillDiagonal_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_dim2_unnormal_unwrap(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_dim2_unnormal_unwrap() - self.func_dim2_unnormal_unwrap() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_dim_larger2_normal(self): + def test_dim_larger2_normal(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array( [ [[1, 2, 2], [2, 2, 2], [2, 2, 2]], @@ -286,12 +261,6 @@ class TensorFillDiagonal_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_dim_larger2_normal(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_dim_larger2_normal() - self.func_dim_larger2_normal() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) diff --git a/python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_tensor_.py b/python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_tensor_.py index 6c4531beee7ab60ca9ab853e60129fccafd26f36..d3c5fc15ed48e2bc028505978f26278fa15d7d0f 100644 --- a/python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_tensor_.py +++ b/python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_tensor_.py @@ -19,7 +19,6 @@ import numpy as np import paddle import paddle.fluid as fluid import paddle.nn.functional as F -from paddle.fluid.framework import _test_eager_guard class TensorFillDiagTensor_Test(unittest.TestCase): @@ -29,7 +28,8 @@ class TensorFillDiagTensor_Test(unittest.TestCase): if fluid.core.is_compiled_with_cuda(): self.places.append(fluid.CUDAPlace(0)) - def func_dim2(self): + def test_dim2(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array( [[1, 2, 2], [2, 1, 2], [2, 2, 1], [2, 2, 2]] ).astype('float32') @@ -59,15 +59,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_dim2(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_dim2() - self.func_dim2() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_dim2_offset_1(self): + def test_dim2_offset_1(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array( [[2, 2, 2], [1, 2, 2], [2, 1, 2], [2, 2, 1]] ).astype('float32') @@ -97,15 +92,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_dim2_offset_1(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_dim2_offset_1() - self.func_dim2_offset_1() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_dim2_offset1(self): + def test_dim2_offset1(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array( [[2, 1, 2], [2, 2, 1], [2, 2, 2], [2, 2, 2]] ).astype('float32') @@ -135,15 +125,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_dim2_offset1(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_dim2_offset1() - self.func_dim2_offset1() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_dim4(self): + def test_dim4(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) expected_np = np.array( [ [ @@ -201,15 +186,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase): (y.grad.numpy().astype('float32') == expected_grad).all(), True, ) - - def test_func_dim4(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_dim4() - self.func_dim4() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_largedim(self): + def test_largedim(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) # large dim only test on gpu because the cpu version is too slow for ci test, and the memory is limited if len(self.places) > 1: bsdim = 1024 @@ -233,12 +213,6 @@ class TensorFillDiagTensor_Test(unittest.TestCase): self.assertEqual((y == expected_pred).all(), True) self.assertEqual((y.grad == expected_grad).all(), True) - - def test_largedim(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_largedim() - self.func_largedim() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) diff --git a/python/paddle/fluid/tests/unittests/test_tensor_register_hook.py b/python/paddle/fluid/tests/unittests/test_tensor_register_hook.py index c557d4bc378a0d324c6c9ef0462fb96d13db9800..54dadeb9f873c56cfea88b705f98ae59a186024c 100644 --- a/python/paddle/fluid/tests/unittests/test_tensor_register_hook.py +++ b/python/paddle/fluid/tests/unittests/test_tensor_register_hook.py @@ -20,7 +20,6 @@ import paddle import paddle.fluid as fluid import paddle.fluid.core as core import paddle.nn as nn -from paddle.fluid.framework import _test_eager_guard class SimpleNet(nn.Layer): @@ -66,7 +65,9 @@ class TestTensorRegisterHook(unittest.TestCase): if paddle.is_compiled_with_cuda(): self.devices.append("gpu") - def func_hook_for_interior_var(self): + def test_hook_for_interior_var(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) + def run_double_hook_for_interior_var(double_hook, removed=False): for device in self.devices: paddle.set_device(device) @@ -155,15 +156,11 @@ class TestTensorRegisterHook(unittest.TestCase): run_print_hook_for_interior_var(print_hook) # register hook and removed run_print_hook_for_interior_var(print_hook, removed=True) + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def test_hook_for_interior_var(self): + def test_hook_for_leaf_var(self): fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_hook_for_interior_var() - self.func_hook_for_interior_var() - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_hook_for_leaf_var(self): def run_double_hook_for_leaf_var(double_hook, removed=False): for device in self.devices: paddle.set_device(device) @@ -201,15 +198,11 @@ class TestTensorRegisterHook(unittest.TestCase): run_double_hook_for_leaf_var(lambda grad: grad * 2) # register hook and removed run_double_hook_for_leaf_var(lambda grad: grad * 2, removed=True) + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def test_hook_for_leaf_var(self): + def test_hook_for_accumulated_grad_interior_var(self): fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_hook_for_leaf_var() - self.func_hook_for_leaf_var() - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_hook_for_accumulated_grad_interior_var(self): def run_double_hook_for_accumulated_grad_interior_var( double_hook, removed=False ): @@ -265,15 +258,11 @@ class TestTensorRegisterHook(unittest.TestCase): run_double_hook_for_accumulated_grad_interior_var( lambda grad: grad * 2, removed=True ) + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def test_hook_for_accumulated_grad_interior_var(self): + def test_hook_for_accumulated_grad_leaf_var(self): fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_hook_for_accumulated_grad_interior_var() - self.func_hook_for_accumulated_grad_interior_var() - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_hook_for_accumulated_grad_leaf_var(self): def run_double_hook_for_accumulated_grad_leaf_var( double_hook, removed=False ): @@ -315,13 +304,11 @@ class TestTensorRegisterHook(unittest.TestCase): run_double_hook_for_accumulated_grad_leaf_var( lambda grad: grad * 2, removed=True ) + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def test_hook_for_accumulated_grad_leaf_var(self): - with _test_eager_guard(): - self.func_hook_for_accumulated_grad_leaf_var() - self.func_hook_for_accumulated_grad_leaf_var() + def test_hook_in_model(self): + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - def func_hook_in_model(self): def run_double_hook_in_model( data, label, hook=None, register=False, remove=False ): @@ -378,15 +365,11 @@ class TestTensorRegisterHook(unittest.TestCase): np.testing.assert_array_equal(ret1_grad, ret1_grad_rm) np.testing.assert_array_equal(linear1_w_grad, linear1_w_grad_rm) np.testing.assert_array_equal(linear1_b_grad, linear1_b_grad_rm) + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def test_func_hook_in_model(self): + def test_multiple_hooks_for_interior_var(self): fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_hook_in_model() - self.func_hook_in_model() - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_multiple_hooks_for_interior_var(self): def run_multiple_hooks_for_interior_var( device, hooks, remove1=False, remove2=False, remove3=False ): @@ -466,15 +449,9 @@ class TestTensorRegisterHook(unittest.TestCase): np.testing.assert_array_equal(w_grad, z) np.testing.assert_array_equal(x_grad, z) np.testing.assert_array_equal(y_grad, z) - - def test_multiple_hooks_for_interior_var(self): - fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) - with _test_eager_guard(): - self.func_multiple_hooks_for_interior_var() - self.func_multiple_hooks_for_interior_var() fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False}) - def func_hook_in_double_grad(self): + def test_hook_in_double_grad(self): def double_print_hook(grad): grad = grad * 2 print(grad) @@ -510,12 +487,7 @@ class TestTensorRegisterHook(unittest.TestCase): z.backward() np.testing.assert_array_equal(x.grad.numpy(), np.array([8.0])) - def test_hook_in_double_grad(self): - with _test_eager_guard(): - self.func_hook_in_double_grad() - self.func_hook_in_double_grad() - - def func_remove_one_hook_multiple_times(self): + def test_remove_one_hook_multiple_times(self): for device in self.devices: paddle.set_device(device) @@ -526,12 +498,7 @@ class TestTensorRegisterHook(unittest.TestCase): self.assertTrue(h.remove()) self.assertFalse(h.remove()) - def test_remove_one_hook_multiple_times(self): - with _test_eager_guard(): - self.func_remove_one_hook_multiple_times() - self.func_remove_one_hook_multiple_times() - - def func_register_hook_for_stop_gradient_var(self): + def test_register_hook_for_stop_gradient_var(self): for device in self.devices: paddle.set_device(device) @@ -540,11 +507,6 @@ class TestTensorRegisterHook(unittest.TestCase): with self.assertRaises(RuntimeError): x.register_hook(lambda grad: grad * 2) - def test_register_hook_for_stop_gradient_var(self): - with _test_eager_guard(): - self.func_register_hook_for_stop_gradient_var() - self.func_register_hook_for_stop_gradient_var() - def test_register_hook_in_static_mode(self): paddle.enable_static() @@ -562,7 +524,7 @@ class TestTensorRegisterHook(unittest.TestCase): paddle.disable_static() - def func_register_hook_in_dy2static_mode(self): + def test_register_hook_in_dy2static_mode(self): net = SimpleNetForStatic(self.in_size, self.out_size) jit_net = paddle.jit.to_static( net, input_spec=[paddle.static.InputSpec([None, self.in_size])] @@ -576,11 +538,6 @@ class TestTensorRegisterHook(unittest.TestCase): with self.assertRaises(AssertionError): out = jit_net(data_t) - def test_register_hook_in_dy2static_mode(self): - with _test_eager_guard(): - self.func_register_hook_in_dy2static_mode() - self.func_register_hook_in_dy2static_mode() - HOOK_INIT_VALUE = 10 HOOK_IS_CALLED = False @@ -599,7 +556,7 @@ class TestTensorRegisterBackwardHook(unittest.TestCase): if paddle.is_compiled_with_cuda(): self.devices.append("gpu") - def func_register_backward_hook(self): + def test_register_backward_hook(self): global HOOK_INIT_VALUE global HOOK_IS_CALLED for device in self.devices: @@ -616,35 +573,20 @@ class TestTensorRegisterBackwardHook(unittest.TestCase): HOOK_INIT_VALUE = 10 HOOK_IS_CALLED = False - def test_register_backward_hook(self): - with _test_eager_guard(): - self.func_register_backward_hook() - self.func_register_backward_hook() - - def func_register_backward_hook_for_interior_var(self): + def test_register_backward_hook_for_interior_var(self): x = paddle.to_tensor(5.0, stop_gradient=False) y = paddle.pow(x, 4.0) with self.assertRaises(ValueError): y._register_backward_hook(global_void_hook) - def test_register_backward_hook_for_interior_var(self): - with _test_eager_guard(): - self.func_register_backward_hook_for_interior_var() - self.func_register_backward_hook_for_interior_var() - - def func_register_backward_hook_for_var_without_gradient(self): + def test_register_backward_hook_for_var_without_gradient(self): x = paddle.to_tensor(5.0) y = paddle.pow(x, 4.0) with self.assertRaises(ValueError): x._register_backward_hook(global_void_hook) - def test_register_backward_hook_for_var_without_gradient(self): - with _test_eager_guard(): - self.func_register_backward_hook_for_var_without_gradient() - self.func_register_backward_hook_for_var_without_gradient() - class TestRegsiterBackwardFinalHook(unittest.TestCase): def setUp(self): diff --git a/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_dynamic.py b/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_dynamic.py index 3a7aca28ac85345f408f1384cb38ef3bf0209091..2f6541f67968e96de33beef0e1f2c52208318553 100644 --- a/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_dynamic.py +++ b/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_dynamic.py @@ -17,7 +17,6 @@ import unittest import numpy as np import paddle -from paddle.fluid.framework import _test_eager_guard # Support types are ref from `paddle.tensor.math` # - Related paddle dtypes: @@ -50,7 +49,7 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): self.assertEqual(c_rlt.dtype, c.dtype) np.testing.assert_array_equal(c_rlt.numpy(), c.numpy()) - def func_tensor_add_scalar(self): + def test_tensor_add_scalar(self): # tensor(int64) + scalar(int) a = paddle.ones([2, 2, 2], dtype='int64') b = 1 @@ -81,12 +80,7 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], 2.5, dtype="float32") self.check_operation(a, b, c, '+') - def test_tensor_add_scalar(self): - with _test_eager_guard(): - self.func_tensor_add_scalar() - self.func_tensor_add_scalar() - - def func_tensor_sub_scalar(self): + def test_tensor_sub_scalar(self): # tensor(int64) - scalar(int) a = paddle.ones([2, 2, 2], dtype='int64') b = 1 @@ -117,12 +111,7 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], 0.5, dtype="float32") self.check_operation(a, b, c, '-') - def test_tensor_sub_scalar(self): - with _test_eager_guard(): - self.func_tensor_sub_scalar() - self.func_tensor_sub_scalar() - - def func_scalar_sub_tensor(self): + def test_scalar_sub_tensor(self): # scalar(int) - tensor(int64) a = 1 b = paddle.ones([2, 2, 2], dtype='int64') @@ -153,12 +142,7 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], -0.5, dtype="float32") self.check_operation(a, b, c, '-') - def test_scalar_sub_tensor(self): - with _test_eager_guard(): - self.func_scalar_sub_tensor() - self.func_scalar_sub_tensor() - - def func_tensor_mul_tensor(self): + def test_tensor_mul_tensor(self): # tensor(int64) * scalar(int) a = paddle.ones([2, 2, 2], dtype='int64') b = 1 @@ -189,12 +173,7 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], 1.5, dtype="float32") self.check_operation(a, b, c, '*') - def test_tensor_mul_tensor(self): - with _test_eager_guard(): - self.func_tensor_mul_tensor() - self.func_tensor_mul_tensor() - - def func_tensor_div_scalar(self): + def test_tensor_div_scalar(self): # tensor(int64) / scalar(int) a = paddle.ones([2, 2, 2], dtype='int64') b = 2 @@ -225,12 +204,7 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], 2, dtype="float32") self.check_operation(a, b, c, '/') - def test_tensor_div_scalar(self): - with _test_eager_guard(): - self.func_tensor_div_scalar() - self.func_tensor_div_scalar() - - def func_scalar_div_tensor(self): + def test_scalar_div_tensor(self): # scalar(int) / tensor(int64) a = 1 b = paddle.full([2, 2, 2], 2, dtype='int64') @@ -255,12 +229,7 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], 2, dtype="float32") self.check_operation(a, b, c, '/') - def test_scalar_div_tensor(self): - with _test_eager_guard(): - self.func_scalar_div_tensor() - self.func_scalar_div_tensor() - - def func_tensor_pow_scalar(self): + def test_tensor_pow_scalar(self): # tensor(int64) ** scalar(int) a = paddle.full([2, 2, 2], 2, dtype='int64') b = 3 @@ -285,12 +254,7 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], 8, dtype="float32") self.check_operation(a, b, c, '**') - def test_tensor_pow_scalar(self): - with _test_eager_guard(): - self.func_tensor_pow_scalar() - self.func_tensor_pow_scalar() - - def func_scalar_pow_tensor(self): + def test_scalar_pow_tensor(self): # scalar(int) ** tensor(int64) a = 3 b = paddle.full([2, 2, 2], 2, dtype='int64') @@ -315,25 +279,15 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], 9, dtype="float32") self.check_operation(a, b, c, '**') - def test_scalar_pow_tensor(self): - with _test_eager_guard(): - self.func_scalar_pow_tensor() - self.func_scalar_pow_tensor() - # TODO: floordiv op kernel doesn't support float - def func_tensor_floordiv_scalar(self): + def test_tensor_floordiv_scalar(self): # tensor(int64) // scalar(int) a = paddle.full([2, 2, 2], 3, dtype='int64') b = 2 c = paddle.full([2, 2, 2], 1, dtype="int64") self.check_operation(a, b, c, '//') - def test_tensor_floordiv_scalar(self): - with _test_eager_guard(): - self.func_tensor_floordiv_scalar() - self.func_tensor_floordiv_scalar() - - def func_tensor_mod_scalar(self): + def test_tensor_mod_scalar(self): # tensor(int64) % scalar(int) a = paddle.full([2, 2, 2], 3, dtype='int64') b = 2 @@ -358,11 +312,6 @@ class TestTensorScalarTypePromotionDynamic(unittest.TestCase): c = paddle.full([2, 2, 2], 1, dtype="float32") self.check_operation(a, b, c, '%') - def test_tensor_mod_scalar(self): - with _test_eager_guard(): - self.func_tensor_mod_scalar() - self.func_tensor_mod_scalar() - if __name__ == '__main__': unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_tensor_type_promotion.py b/python/paddle/fluid/tests/unittests/test_tensor_type_promotion.py index 811c2e583d701b894c2019e5252061f26fe0e04b..a4e3f76d7ee8bec12335a252597d3443dc7b831f 100644 --- a/python/paddle/fluid/tests/unittests/test_tensor_type_promotion.py +++ b/python/paddle/fluid/tests/unittests/test_tensor_type_promotion.py @@ -16,7 +16,6 @@ import unittest import warnings import paddle -from paddle.fluid.framework import _test_eager_guard class TestTensorTypePromotion(unittest.TestCase): @@ -28,42 +27,23 @@ class TestTensorTypePromotion(unittest.TestCase): with warnings.catch_warnings(record=True) as context: warnings.simplefilter("always") self.x + self.y - self.assertTrue( - "The dtype of left and right variables are not the same" - in str(context[-1].message) - ) def sub_operator(self): with warnings.catch_warnings(record=True) as context: warnings.simplefilter("always") self.x - self.y - self.assertTrue( - "The dtype of left and right variables are not the same" - in str(context[-1].message) - ) def mul_operator(self): with warnings.catch_warnings(record=True) as context: warnings.simplefilter("always") self.x * self.y - self.assertTrue( - "The dtype of left and right variables are not the same" - in str(context[-1].message) - ) def div_operator(self): with warnings.catch_warnings(record=True) as context: warnings.simplefilter("always") self.x / self.y - self.assertTrue( - "The dtype of left and right variables are not the same" - in str(context[-1].message) - ) def test_operator(self): - with _test_eager_guard(): - pass - # add / sub / mul / div has been sunk to cpp level, there is no warnings to catch by this test. self.setUp() self.add_operator() self.sub_operator() diff --git a/python/paddle/fluid/tests/unittests/test_tensor_uva.py b/python/paddle/fluid/tests/unittests/test_tensor_uva.py index ab4fd6ed432ec8c1d0eaa30546ecb3153b263a97..d23d5559da595db2e02b38506e42a1f4213e4908 100644 --- a/python/paddle/fluid/tests/unittests/test_tensor_uva.py +++ b/python/paddle/fluid/tests/unittests/test_tensor_uva.py @@ -18,11 +18,11 @@ import numpy as np import paddle from paddle.fluid import core -from paddle.fluid.framework import _in_legacy_dygraph, _test_eager_guard +from paddle.fluid.framework import _in_legacy_dygraph class TestTensorCopyFrom(unittest.TestCase): - def func_main(self): + def test_main(self): if paddle.fluid.core.is_compiled_with_cuda(): place = paddle.CPUPlace() np_value = np.random.random(size=[10, 30]).astype('float32') @@ -30,14 +30,9 @@ class TestTensorCopyFrom(unittest.TestCase): tensor._uva() self.assertTrue(tensor.place.is_gpu_place()) - def test_main(self): - with _test_eager_guard(): - self.func_main() - self.func_main() - class TestUVATensorFromNumpy(unittest.TestCase): - def func_uva_tensor_creation(self): + def test_uva_tensor_creation(self): if paddle.fluid.core.is_compiled_with_cuda(): dtype_list = [ "int32", @@ -74,11 +69,6 @@ class TestUVATensorFromNumpy(unittest.TestCase): tensor1.numpy(), tensor2.numpy(), rtol=1e-05 ) - def test_uva_tensor_creation(self): - with _test_eager_guard(): - self.func_uva_tensor_creation() - self.func_uva_tensor_creation() - if __name__ == "__main__": unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_tensor_zero_.py b/python/paddle/fluid/tests/unittests/test_tensor_zero_.py index e1337c8de60119403977ff6f1ad88dfdc0d5da44..b1fd992e0d5f8329999928328e63ead5611233b0 100644 --- a/python/paddle/fluid/tests/unittests/test_tensor_zero_.py +++ b/python/paddle/fluid/tests/unittests/test_tensor_zero_.py @@ -18,14 +18,13 @@ import numpy as np import paddle import paddle.fluid as fluid -from paddle.fluid.framework import _test_eager_guard class TensorFill_Test(unittest.TestCase): def setUp(self): self.shape = [32, 32] - def func_test_tensor_fill_true(self): + def test_tensor_fill_true(self): typelist = ['float32', 'float64', 'int32', 'int64', 'float16'] places = [fluid.CPUPlace()] if fluid.core.is_compiled_with_cuda(): @@ -44,11 +43,6 @@ class TensorFill_Test(unittest.TestCase): tensor.zero_() self.assertEqual((tensor.numpy() == target).all().item(), True) - def test_tensor_fill_true(self): - with _test_eager_guard(): - self.func_test_tensor_fill_true() - self.func_test_tensor_fill_true() - if __name__ == '__main__': unittest.main()