diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_add_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_add_op.py index 3bf2b7cdcd703583e2cf0e00a9542b6130acef22..502ca504c1b8ebbe8cd3e4cc34cb62d64510bc85 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_add_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_add_op.py @@ -15,15 +15,18 @@ import unittest import numpy as np +from eager_op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci import paddle import paddle.fluid as fluid import paddle.fluid.core as core -from paddle.fluid.tests.unittests.op_test import ( - OpTest, - convert_float_to_uint16, - skip_check_grad_ci, -) + + +def broadcast_wrapper(shape=[1, 10, 12, 1]): + def add_wrapper(x, y, axis=-1): + return x + y.reshape(shape) + + return add_wrapper class TestElementwiseAddOp(OpTest): @@ -45,14 +48,13 @@ class TestElementwiseAddOp(OpTest): self.attrs = {'axis': self.axis, 'use_mkldnn': self.use_mkldnn} self.outputs = {'Out': self.out} - def check_eager(self): + def check_dygraph(self): return not self.use_mkldnn and self.axis == -1 def test_check_output(self): # TODO(wangzhongpu): support mkldnn op in dygraph mode self.check_output( - check_dygraph=(not self.use_mkldnn), - check_eager=self.check_eager(), + check_dygraph=self.check_dygraph(), ) def test_check_grad_normal(self): @@ -62,8 +64,7 @@ class TestElementwiseAddOp(OpTest): self.check_grad( ['X', 'Y'], 'Out', - check_dygraph=(not self.use_mkldnn), - check_eager=self.check_eager(), + check_dygraph=self.check_dygraph(), ) def test_check_grad_ingore_x(self): @@ -74,8 +75,7 @@ class TestElementwiseAddOp(OpTest): ['Y'], 'Out', no_grad_set=set("X"), - check_dygraph=(not self.use_mkldnn), - check_eager=self.check_eager(), + check_dygraph=self.check_dygraph(), ) def test_check_grad_ingore_y(self): @@ -86,8 +86,7 @@ class TestElementwiseAddOp(OpTest): ['X'], 'Out', no_grad_set=set('Y'), - check_dygraph=(not self.use_mkldnn), - check_eager=self.check_eager(), + check_dygraph=self.check_dygraph(), ) def init_input_output(self): @@ -136,7 +135,8 @@ class TestFP16ElementwiseAddOp(TestElementwiseAddOp): place = core.CUDAPlace(0) if core.is_float16_supported(place): self.check_output_with_place( - place, atol=1e-3, check_dygraph=(not self.use_mkldnn) + place, + atol=1e-3, ) @@ -149,6 +149,7 @@ class TestFP16ElementwiseAddOp(TestElementwiseAddOp): class TestBF16ElementwiseAddOp(OpTest): def setUp(self): self.op_type = "elementwise_add" + self.python_api = paddle.add self.dtype = np.uint16 self.x = np.random.uniform(0.1, 1, [13, 17]).astype(np.float32) @@ -170,23 +171,19 @@ class TestBF16ElementwiseAddOp(OpTest): def test_check_output(self): place = core.CUDAPlace(0) - self.check_output_with_place(place, check_eager=False) + self.check_output_with_place(place) def test_check_grad_normal(self): place = core.CUDAPlace(0) - self.check_grad_with_place(place, ['X', 'Y'], 'Out', check_eager=False) + self.check_grad_with_place(place, ['X', 'Y'], 'Out') def test_check_grad_ingore_x(self): place = core.CUDAPlace(0) - self.check_grad_with_place( - place, ['Y'], 'Out', no_grad_set=set("X"), check_eager=False - ) + self.check_grad_with_place(place, ['Y'], 'Out', no_grad_set=set("X")) def test_check_grad_ingore_y(self): place = core.CUDAPlace(0) - self.check_grad_with_place( - place, ['X'], 'Out', no_grad_set=set('Y'), check_eager=False - ) + self.check_grad_with_place(place, ['X'], 'Out', no_grad_set=set('Y')) @skip_check_grad_ci( @@ -248,6 +245,7 @@ class TestElementwiseAddOp_broadcast_0(TestElementwiseAddOp): self.x = np.random.rand(100, 2, 3).astype(self.dtype) self.y = np.random.rand(100).astype(self.dtype) self.out = self.x + self.y.reshape(100, 1, 1) + self.python_api = broadcast_wrapper(shape=[100, 1, 1]) def init_axis(self): self.axis = 0 @@ -258,6 +256,7 @@ class TestFP16ElementwiseAddOp_broadcast_0(TestFP16ElementwiseAddOp): self.x = np.random.rand(100, 2, 3).astype(self.dtype) self.y = np.random.rand(100).astype(self.dtype) self.out = self.x + self.y.reshape(100, 1, 1) + self.python_api = broadcast_wrapper(shape=[100, 1, 1]) def init_axis(self): self.axis = 0 @@ -268,6 +267,7 @@ class TestElementwiseAddOp_broadcast_1(TestElementwiseAddOp): self.x = np.random.rand(2, 100, 3).astype(self.dtype) self.y = np.random.rand(100).astype(self.dtype) self.out = self.x + self.y.reshape(1, 100, 1) + self.python_api = broadcast_wrapper(shape=[1, 100, 1]) def init_axis(self): self.axis = 1 @@ -278,6 +278,7 @@ class TestFP16ElementwiseAddOp_broadcast_1(TestFP16ElementwiseAddOp): self.x = np.random.rand(2, 100, 3).astype(self.dtype) self.y = np.random.rand(100).astype(self.dtype) self.out = self.x + self.y.reshape(1, 100, 1) + self.python_api = broadcast_wrapper(shape=[1, 100, 1]) def init_axis(self): self.axis = 1 @@ -288,6 +289,7 @@ class TestElementwiseAddOp_broadcast_2(TestElementwiseAddOp): self.x = np.random.rand(2, 3, 100).astype(self.dtype) self.y = np.random.rand(100).astype(self.dtype) self.out = self.x + self.y.reshape(1, 1, 100) + self.python_api = broadcast_wrapper(shape=[1, 1, 100]) class TestFP16ElementwiseAddOp_broadcast_2(TestFP16ElementwiseAddOp): @@ -295,6 +297,7 @@ class TestFP16ElementwiseAddOp_broadcast_2(TestFP16ElementwiseAddOp): self.x = np.random.rand(2, 3, 100).astype(self.dtype) self.y = np.random.rand(100).astype(self.dtype) self.out = self.x + self.y.reshape(1, 1, 100) + self.python_api = broadcast_wrapper(shape=[1, 1, 100]) class TestElementwiseAddOp_broadcast_3(TestElementwiseAddOp): @@ -302,6 +305,7 @@ class TestElementwiseAddOp_broadcast_3(TestElementwiseAddOp): self.x = np.random.rand(2, 10, 12, 1).astype(self.dtype) self.y = np.random.rand(10, 12).astype(self.dtype) self.out = self.x + self.y.reshape(1, 10, 12, 1) + self.python_api = broadcast_wrapper(shape=[1, 10, 12, 1]) def init_axis(self): self.axis = 1 @@ -312,6 +316,7 @@ class TestFP16ElementwiseAddOp_broadcast_3(TestFP16ElementwiseAddOp): self.x = np.random.rand(2, 10, 12, 3).astype(self.dtype) self.y = np.random.rand(10, 12).astype(self.dtype) self.out = self.x + self.y.reshape(1, 10, 12, 1) + self.python_api = broadcast_wrapper(shape=[1, 10, 12, 1]) def init_axis(self): self.axis = 1 @@ -322,6 +327,7 @@ class TestElementwiseAddOp_broadcast_4(TestElementwiseAddOp): self.x = np.random.rand(100, 2, 1, 2).astype(self.dtype) self.y = np.random.rand(100, 1).astype(self.dtype) self.out = self.x + self.y.reshape(100, 1, 1, 1) + self.python_api = broadcast_wrapper(shape=[100, 1, 1, 1]) def init_axis(self): self.axis = 0 @@ -332,6 +338,7 @@ class TestFP16ElementwiseAddOp_broadcast_4(TestFP16ElementwiseAddOp): self.x = np.random.rand(100, 2, 1, 2).astype(self.dtype) self.y = np.random.rand(100, 1).astype(self.dtype) self.out = self.x + self.y.reshape(100, 1, 1, 1) + self.python_api = broadcast_wrapper(shape=[100, 1, 1, 1]) def init_axis(self): self.axis = 0 @@ -597,6 +604,7 @@ class TestAddInplaceBroadcastError3(TestAddInplaceBroadcastError): class TestComplexElementwiseAddOp(OpTest): def setUp(self): self.op_type = "elementwise_add" + self.python_api = paddle.add self.dtype = np.float64 self.shape = (2, 3, 4, 5) self.init_input_output() @@ -629,7 +637,7 @@ class TestComplexElementwiseAddOp(OpTest): self.grad_y = self.grad_out def test_check_output(self): - self.check_output(check_eager=False) + self.check_output() def test_check_grad_normal(self): self.check_grad( diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_div_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_div_op.py index 943486827237d9f36e5fb23e6ce8566ed1a14d2b..c17a41b0bfad58e80f438da5ec7aacddf2bac5f1 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_div_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_div_op.py @@ -15,13 +15,20 @@ import unittest import numpy as np -from op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci +from eager_op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci import paddle from paddle import fluid from paddle.fluid import core +def broadcast_wrapper(shape=[1, 10, 12, 1]): + def div_wrapper(x, y, axis=-1): + return paddle.divide(x, y.reshape(shape)) + + return div_wrapper + + class ElementwiseDivOp(OpTest): def setUp(self): self.op_type = "elementwise_div" @@ -193,6 +200,7 @@ class TestElementwiseDivOpBroadcast0(ElementwiseDivOp): self.x_shape = [100, 3, 4] self.y_shape = [100] self.attrs = {'axis': 0} + self.python_api = broadcast_wrapper(shape=[100, 1, 1]) def compute_output(self, x, y): return x / y.reshape(100, 1, 1) @@ -209,6 +217,7 @@ class TestElementwiseDivOpBroadcast1(ElementwiseDivOp): self.x_shape = [2, 100, 4] self.y_shape = [100] self.attrs = {'axis': 1} + self.python_api = broadcast_wrapper(shape=[1, 100, 1]) def compute_output(self, x, y): return x / y.reshape(1, 100, 1) @@ -224,6 +233,7 @@ class TestElementwiseDivOpBroadcast2(ElementwiseDivOp): def init_shape(self): self.x_shape = [2, 3, 100] self.y_shape = [100] + self.python_api = broadcast_wrapper(shape=[1, 1, 100]) def compute_output(self, x, y): return x / y.reshape(1, 1, 100) @@ -240,6 +250,7 @@ class TestElementwiseDivOpBroadcast3(ElementwiseDivOp): self.x_shape = [2, 10, 12, 5] self.y_shape = [10, 12] self.attrs = {'axis': 1} + self.python_api = broadcast_wrapper(shape=[1, 10, 12, 1]) def compute_output(self, x, y): return x / y.reshape(1, 10, 12, 1) @@ -393,7 +404,7 @@ class TestComplexElementwiseDivOp(OpTest): self.grad_y = -self.grad_out * np.conj(self.x / self.y / self.y) def test_check_output(self): - self.check_output(check_eager=False) + self.check_output() def test_check_grad_normal(self): self.check_grad( diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_min_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_min_op.py index c9835b5cb1566f671154a191f34ac9912bc20b50..02f1d1dd6d275b89e10261dab6e60e3af1261668 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_min_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_min_op.py @@ -15,7 +15,7 @@ import unittest import numpy as np -from op_test import OpTest, skip_check_grad_ci +from eager_op_test import OpTest, skip_check_grad_ci import paddle import paddle.fluid as fluid @@ -25,6 +25,13 @@ from paddle import _legacy_C_ops paddle.enable_static() +def broadcast_wrapper(shape=[1, 10, 12, 1]): + def min_wrapper(x, y, axis=-1): + return paddle.minimum(x, y.reshape(shape)) + + return min_wrapper + + class TestElementwiseOp(OpTest): def setUp(self): self.op_type = "elementwise_min" @@ -39,16 +46,10 @@ class TestElementwiseOp(OpTest): self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} def test_check_output(self): - if hasattr(self, 'attrs'): - self.check_output(check_eager=False) - else: - self.check_output(check_eager=True) + self.check_output() def test_check_grad_normal(self): - if hasattr(self, 'attrs'): - self.check_grad(['X', 'Y'], 'Out', check_eager=False) - else: - self.check_grad(['X', 'Y'], 'Out', check_eager=True) + self.check_grad(['X', 'Y'], 'Out') def test_check_grad_ingore_x(self): self.check_grad( @@ -118,7 +119,7 @@ class TestElementwiseMinOp_Vector(TestElementwiseOp): class TestElementwiseMinOp_broadcast_0(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - self.python_api = paddle.minimum + self.python_api = broadcast_wrapper(shape=[100, 1, 1]) x = np.random.uniform(0.5, 1, (100, 3, 2)).astype(np.float64) sgn = np.random.choice([-1, 1], (100,)).astype(np.float64) y = x[:, 0, 0] + sgn * np.random.uniform(1, 2, (100,)).astype( @@ -137,7 +138,7 @@ class TestElementwiseMinOp_broadcast_0(TestElementwiseOp): class TestElementwiseMinOp_broadcast_1(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - self.python_api = paddle.minimum + self.python_api = broadcast_wrapper(shape=[1, 100, 1]) x = np.random.uniform(0.5, 1, (2, 100, 3)).astype(np.float64) sgn = np.random.choice([-1, 1], (100,)).astype(np.float64) y = x[0, :, 0] + sgn * np.random.uniform(1, 2, (100,)).astype( @@ -156,7 +157,7 @@ class TestElementwiseMinOp_broadcast_1(TestElementwiseOp): class TestElementwiseMinOp_broadcast_2(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - self.python_api = paddle.minimum + self.python_api = broadcast_wrapper(shape=[1, 1, 100]) x = np.random.uniform(0.5, 1, (2, 3, 100)).astype(np.float64) sgn = np.random.choice([-1, 1], (100,)).astype(np.float64) y = x[0, 0, :] + sgn * np.random.uniform(1, 2, (100,)).astype( @@ -174,7 +175,7 @@ class TestElementwiseMinOp_broadcast_2(TestElementwiseOp): class TestElementwiseMinOp_broadcast_3(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - self.python_api = paddle.minimum + self.python_api = broadcast_wrapper(shape=[1, 25, 4, 1]) x = np.random.uniform(0.5, 1, (2, 25, 4, 1)).astype(np.float64) sgn = np.random.choice([-1, 1], (25, 4)).astype(np.float64) y = x[0, :, :, 0] + sgn * np.random.uniform(1, 2, (25, 4)).astype( diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_mul_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_mul_op.py index e34d9d0dfd32bf7c594b189736bfb22caae22d4f..4fe6a15ef8efc15f78946c248a1ea155a4e896e0 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_mul_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_mul_op.py @@ -15,14 +15,24 @@ import unittest import numpy as np +from eager_op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci import paddle import paddle.fluid.core as core -from paddle.fluid.tests.unittests.op_test import ( - OpTest, - convert_float_to_uint16, - skip_check_grad_ci, -) + + +def mul(x, y, axis=-1, use_mkldnn=False): + return x * y + + +setattr(paddle, "mul", mul) + + +def broadcast_wrapper(shape=[1, 10, 12, 1]): + def mul_wrapper(x, y, axis=-1): + return x * y.reshape(shape) + + return mul_wrapper class ElementwiseMulOp(OpTest): @@ -31,6 +41,7 @@ class ElementwiseMulOp(OpTest): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.dtype = np.float64 self.axis = -1 self.init_dtype() @@ -107,6 +118,7 @@ class TestElementwiseMulOp_ZeroDim3(ElementwiseMulOp): class TestBF16ElementwiseMulOp(OpTest): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.dtype = np.uint16 self.x = np.random.uniform(0.1, 1, [13, 17]).astype(np.float32) @@ -145,6 +157,7 @@ class TestBF16ElementwiseMulOp(OpTest): class TestElementwiseMulOp_scalar(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.inputs = { 'X': np.random.rand(10, 3, 4).astype(np.float64), 'Y': np.random.rand(1).astype(np.float64), @@ -156,6 +169,7 @@ class TestElementwiseMulOp_scalar(ElementwiseMulOp): class TestElementwiseMulOp_Vector(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.inputs = { 'X': np.random.random((100,)).astype("float64"), 'Y': np.random.random((100,)).astype("float64"), @@ -168,6 +182,7 @@ class TestElementwiseMulOp_broadcast_0(ElementwiseMulOp): def init_input_output(self): self.x = np.random.rand(100, 2, 3).astype(self.dtype) self.y = np.random.rand(100).astype(self.dtype) + self.python_api = broadcast_wrapper(shape=[100, 1, 1]) self.out = self.x * self.y.reshape(100, 1, 1) def init_axis(self): @@ -177,6 +192,7 @@ class TestElementwiseMulOp_broadcast_0(ElementwiseMulOp): class TestElementwiseMulOp_broadcast_1(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = broadcast_wrapper(shape=[1, 100, 1]) self.inputs = { 'X': np.random.rand(2, 100, 3).astype(np.float64), 'Y': np.random.rand(100).astype(np.float64), @@ -192,6 +208,7 @@ class TestElementwiseMulOp_broadcast_1(ElementwiseMulOp): class TestElementwiseMulOp_broadcast_2(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = broadcast_wrapper(shape=[1, 1, 100]) self.inputs = { 'X': np.random.rand(2, 3, 100).astype(np.float64), 'Y': np.random.rand(100).astype(np.float64), @@ -206,6 +223,7 @@ class TestElementwiseMulOp_broadcast_2(ElementwiseMulOp): class TestElementwiseMulOp_broadcast_3(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = broadcast_wrapper(shape=[1, 10, 12, 1]) self.inputs = { 'X': np.random.rand(2, 10, 12, 3).astype(np.float64), 'Y': np.random.rand(10, 12).astype(np.float64), @@ -221,6 +239,7 @@ class TestElementwiseMulOp_broadcast_3(ElementwiseMulOp): class TestElementwiseMulOp_broadcast_4(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.inputs = { 'X': np.random.rand(10, 2, 11).astype(np.float64), 'Y': np.random.rand(10, 1, 11).astype(np.float64), @@ -232,6 +251,7 @@ class TestElementwiseMulOp_broadcast_4(ElementwiseMulOp): class TestElementwiseMulOp_broadcast_5(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.inputs = { 'X': np.random.rand(10, 4, 2, 3).astype(np.float64), 'Y': np.random.rand(10, 4, 1, 3).astype(np.float64), @@ -251,6 +271,7 @@ class TestElementwiseMulOpFp16(ElementwiseMulOp): class TestElementwiseMulOp_commonuse_1(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.inputs = { 'X': np.random.rand(2, 3, 100).astype(np.float64), 'Y': np.random.rand(1, 1, 100).astype(np.float64), @@ -262,6 +283,7 @@ class TestElementwiseMulOp_commonuse_1(ElementwiseMulOp): class TestElementwiseMulOp_commonuse_2(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.inputs = { 'X': np.random.rand(30, 3, 1, 5).astype(np.float64), 'Y': np.random.rand(30, 1, 4, 1).astype(np.float64), @@ -273,6 +295,7 @@ class TestElementwiseMulOp_commonuse_2(ElementwiseMulOp): class TestElementwiseMulOp_xsize_lessthan_ysize(ElementwiseMulOp): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.inputs = { 'X': np.random.rand(10, 10).astype(np.float64), 'Y': np.random.rand(2, 2, 10, 10).astype(np.float64), @@ -289,6 +312,7 @@ class TestElementwiseMulOp_xsize_lessthan_ysize(ElementwiseMulOp): class TestComplexElementwiseMulOp(OpTest): def setUp(self): self.op_type = "elementwise_mul" + self.python_api = paddle.mul self.init_base_dtype() self.init_input_output() self.init_grad_input_output() diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py index 398ef711e2feaa0c162a3ad7a76fbdb93d9bed8d..1391dd2e9da5eb7e8d49007ff24a75defb15f58f 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_sub_op.py @@ -15,15 +15,26 @@ import unittest import numpy as np -from op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci +from eager_op_test import OpTest, convert_float_to_uint16, skip_check_grad_ci import paddle import paddle.fluid as fluid +def sub_wrapper(shape=None): + def inner_wrapper(x, y, axis=-1): + if shape is None: + return x - y + else: + return x - y.reshape(shape) + + return inner_wrapper + + class TestElementwiseOp(OpTest): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), 'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), @@ -50,6 +61,7 @@ class TestElementwiseOp(OpTest): class TestElementwiseSubOp_ZeroDim1(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.uniform(0.1, 1, []).astype("float64"), 'Y': np.random.uniform(0.1, 1, []).astype("float64"), @@ -60,6 +72,7 @@ class TestElementwiseSubOp_ZeroDim1(TestElementwiseOp): class TestElementwiseSubOp_ZeroDim2(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), 'Y': np.random.uniform(0.1, 1, []).astype("float64"), @@ -70,6 +83,7 @@ class TestElementwiseSubOp_ZeroDim2(TestElementwiseOp): class TestElementwiseSubOp_ZeroDim3(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.uniform(0.1, 1, []).astype("float64"), 'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), @@ -80,6 +94,7 @@ class TestElementwiseSubOp_ZeroDim3(TestElementwiseOp): class TestBF16ElementwiseOp(OpTest): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.dtype = np.uint16 x = np.random.uniform(0.1, 1, [13, 17]).astype(np.float32) y = np.random.uniform(0.1, 1, [13, 17]).astype(np.float32) @@ -110,6 +125,7 @@ class TestBF16ElementwiseOp(OpTest): class TestElementwiseSubOp_scalar(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.rand(10, 3, 4).astype(np.float64), 'Y': np.random.rand(1).astype(np.float64), @@ -120,6 +136,7 @@ class TestElementwiseSubOp_scalar(TestElementwiseOp): class TestElementwiseSubOp_Vector(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.random((100,)).astype("float64"), 'Y': np.random.random((100,)).astype("float64"), @@ -130,6 +147,7 @@ class TestElementwiseSubOp_Vector(TestElementwiseOp): class TestElementwiseSubOp_broadcast_0(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper(shape=[100, 1, 1]) self.inputs = { 'X': np.random.rand(100, 3, 2).astype(np.float64), 'Y': np.random.rand(100).astype(np.float64), @@ -144,6 +162,7 @@ class TestElementwiseSubOp_broadcast_0(TestElementwiseOp): class TestElementwiseSubOp_broadcast_1(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper(shape=[1, 100, 1]) self.inputs = { 'X': np.random.rand(2, 100, 3).astype(np.float64), 'Y': np.random.rand(100).astype(np.float64), @@ -158,6 +177,7 @@ class TestElementwiseSubOp_broadcast_1(TestElementwiseOp): class TestElementwiseSubOp_broadcast_2(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper(shape=[1, 1, 100]) self.inputs = { 'X': np.random.rand(2, 3, 100).astype(np.float64), 'Y': np.random.rand(100).astype(np.float64), @@ -171,6 +191,7 @@ class TestElementwiseSubOp_broadcast_2(TestElementwiseOp): class TestElementwiseSubOp_broadcast_3(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper(shape=[1, 10, 12, 1]) self.inputs = { 'X': np.random.rand(2, 10, 12, 3).astype(np.float64), 'Y': np.random.rand(10, 12).astype(np.float64), @@ -185,6 +206,7 @@ class TestElementwiseSubOp_broadcast_3(TestElementwiseOp): class TestElementwiseSubOp_broadcast_4(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.rand(2, 5, 3, 12).astype(np.float64), 'Y': np.random.rand(2, 5, 1, 12).astype(np.float64), @@ -195,6 +217,7 @@ class TestElementwiseSubOp_broadcast_4(TestElementwiseOp): class TestElementwiseSubOp_commonuse_1(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.rand(2, 3, 100).astype(np.float64), 'Y': np.random.rand(1, 1, 100).astype(np.float64), @@ -205,6 +228,7 @@ class TestElementwiseSubOp_commonuse_1(TestElementwiseOp): class TestElementwiseSubOp_commonuse_2(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.inputs = { 'X': np.random.rand(10, 3, 1, 4).astype(np.float64), 'Y': np.random.rand(10, 1, 12, 1).astype(np.float64), @@ -215,6 +239,11 @@ class TestElementwiseSubOp_commonuse_2(TestElementwiseOp): class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_sub" + + def sub_func(x, y, axis=2): + return x.reshape([1, 1, 10, 12]) - y + + self.python_api = sub_func self.inputs = { 'X': np.random.rand(10, 12).astype(np.float64), 'Y': np.random.rand(2, 3, 10, 12).astype(np.float64), @@ -230,6 +259,7 @@ class TestElementwiseSubOp_xsize_lessthan_ysize(TestElementwiseOp): class TestComplexElementwiseSubOp(OpTest): def setUp(self): self.op_type = "elementwise_sub" + self.python_api = sub_wrapper() self.dtype = np.float64 self.shape = (2, 3, 4, 5) self.init_input_output() diff --git a/python/paddle/fluid/tests/unittests/test_pixel_shuffle.py b/python/paddle/fluid/tests/unittests/test_pixel_shuffle.py index 9600f5a872c56a7734826b457f8a6eb5b916cc92..0ef6b3e77824ba8402d7add0b7c0adb4c5bed6f8 100644 --- a/python/paddle/fluid/tests/unittests/test_pixel_shuffle.py +++ b/python/paddle/fluid/tests/unittests/test_pixel_shuffle.py @@ -15,7 +15,7 @@ import unittest import numpy as np -from op_test import OpTest +from eager_op_test import OpTest import paddle import paddle.fluid as fluid @@ -85,10 +85,13 @@ class TestPixelShuffleOp(OpTest): self.format = "NCHW" def test_check_output(self): - self.check_output(check_eager=True) + self.check_output() def test_check_grad(self): - self.check_grad(['X'], 'Out', check_eager=True) + self.check_grad( + ['X'], + 'Out', + ) class TestChannelLast(TestPixelShuffleOp): diff --git a/python/paddle/fluid/tests/unittests/test_poisson_op.py b/python/paddle/fluid/tests/unittests/test_poisson_op.py index e2720edb013130de8aaeab38d06c6effd43276cd..ee66d578014c70395ec3525f8118d2780886458c 100644 --- a/python/paddle/fluid/tests/unittests/test_poisson_op.py +++ b/python/paddle/fluid/tests/unittests/test_poisson_op.py @@ -16,7 +16,7 @@ import math import unittest import numpy as np -from op_test import OpTest +from eager_op_test import OpTest import paddle @@ -41,6 +41,7 @@ def output_hist(out, lam, a, b): class TestPoissonOp1(OpTest): def setUp(self): self.op_type = "poisson" + self.python_api = paddle.tensor.poisson self.config() self.attrs = {} diff --git a/python/paddle/fluid/tests/unittests/test_put_along_axis_op.py b/python/paddle/fluid/tests/unittests/test_put_along_axis_op.py index 3b2cf82fbfd391e9218b641944e8f0c9e7b3388d..7470dae1846ab353e31b6a113e93addc4481e0c3 100644 --- a/python/paddle/fluid/tests/unittests/test_put_along_axis_op.py +++ b/python/paddle/fluid/tests/unittests/test_put_along_axis_op.py @@ -16,7 +16,7 @@ import copy import unittest import numpy as np -from op_test import OpTest +from eager_op_test import OpTest import paddle from paddle.framework import core @@ -30,6 +30,7 @@ class TestPutAlongAxisOp(OpTest): self.reduce_op = "assign" self.dtype = 'float64' self.op_type = "put_along_axis" + self.python_api = paddle.tensor.put_along_axis self.xnp = np.random.random(self.x_shape).astype(self.x_type) # numpy put_along_axis is an inplace opearion. self.xnp_result = copy.deepcopy(self.xnp) diff --git a/python/paddle/fluid/tests/unittests/test_size_op.py b/python/paddle/fluid/tests/unittests/test_size_op.py index b3ae19b8ef20eb5528b81dbc478cc564c1e87e0c..edea44abf089057ac068bc4dd635b673d3e3b3f2 100644 --- a/python/paddle/fluid/tests/unittests/test_size_op.py +++ b/python/paddle/fluid/tests/unittests/test_size_op.py @@ -15,15 +15,20 @@ import unittest import numpy as np -from op_test import OpTest +from eager_op_test import OpTest import paddle import paddle.fluid as fluid +def size_wrapper(input): + return paddle.numel(paddle.to_tensor(input)) + + class TestSizeOp(OpTest): def setUp(self): self.op_type = "size" + self.python_api = size_wrapper self.shape = [] self.config() input = np.zeros(self.shape, dtype='bool') diff --git a/python/paddle/fluid/tests/unittests/test_softmax_op.py b/python/paddle/fluid/tests/unittests/test_softmax_op.py index 290d72b2485b2ede9967f99c5b3e58464f4b75ad..8696cc532820f7946c03a2e3fcf34c3ae520b302 100644 --- a/python/paddle/fluid/tests/unittests/test_softmax_op.py +++ b/python/paddle/fluid/tests/unittests/test_softmax_op.py @@ -15,7 +15,7 @@ import unittest import numpy as np -from op_test import OpTest, convert_float_to_uint16 +from eager_op_test import OpTest, convert_float_to_uint16 import paddle import paddle.fluid as fluid @@ -43,6 +43,12 @@ def ref_softmax(x, axis=None, dtype=None): return np.apply_along_axis(stable_softmax, axis, x_t) +def softmax_wrapper( + x, axis=-1, dtype=None, name=None, use_cudnn=False, use_mkldnn=False +): + return paddle.nn.functional.softmax(x, axis=axis, dtype=dtype) + + class TestSoftmaxOp(OpTest): def get_x_shape(self): return [10, 10] @@ -52,6 +58,7 @@ class TestSoftmaxOp(OpTest): def setUp(self): self.op_type = "softmax" + self.python_api = softmax_wrapper self.use_cudnn = False self.use_mkldnn = False # explicilty use float32 for ROCm, as MIOpen does not yet support float64 @@ -109,6 +116,7 @@ class TestSoftmaxOp(OpTest): class TestSoftmaxOp_ZeroDim1(TestSoftmaxOp): def setUp(self): self.op_type = "softmax" + self.python_api = softmax_wrapper self.use_cudnn = False self.use_mkldnn = False # explicilty use float32 for ROCm, as MIOpen does not yet support float64 @@ -133,6 +141,7 @@ class TestSoftmaxOp_ZeroDim1(TestSoftmaxOp): class TestSoftmaxOp_ZeroDim2(TestSoftmaxOp): def setUp(self): self.op_type = "softmax" + self.python_api = softmax_wrapper self.use_cudnn = True self.use_mkldnn = False # explicilty use float32 for ROCm, as MIOpen does not yet support float64 @@ -366,6 +375,7 @@ class TestSoftmaxFP16CUDNNOp2(TestSoftmaxFP16CUDNNOp): class TestSoftmaxBF16Op(OpTest): def setUp(self): self.op_type = "softmax" + self.python_api = softmax_wrapper self.use_cudnn = self.init_cudnn() self.use_mkldnn = False self.dtype = np.uint16 diff --git a/python/paddle/fluid/tests/unittests/test_spectral_norm_op.py b/python/paddle/fluid/tests/unittests/test_spectral_norm_op.py index 033ee7908866d7468e773e68befe519f560cd68b..c60780f90c49bcf0569eb5802837c7b9589be247 100644 --- a/python/paddle/fluid/tests/unittests/test_spectral_norm_op.py +++ b/python/paddle/fluid/tests/unittests/test_spectral_norm_op.py @@ -15,9 +15,10 @@ import unittest import numpy as np -from op_test import OpTest, skip_check_grad_ci +from eager_op_test import OpTest, skip_check_grad_ci import paddle +from paddle import _C_ops from paddle.fluid.framework import Program, program_guard paddle.enable_static() @@ -47,6 +48,10 @@ def spectral_norm(weight, u, v, dim, power_iters, eps): return weight / sigma +def spectral_norm_wrapper(weight, u, v, dim, power_iters, eps): + return _C_ops.spectral_norm(weight, u, v, dim, power_iters, eps) + + @skip_check_grad_ci( reason="Spectral norm do not check grad when power_iters > 0 " "because grad is not calculated in power iterations, " @@ -56,6 +61,7 @@ class TestSpectralNormOpNoGrad(OpTest): def setUp(self): self.initTestCase() self.op_type = 'spectral_norm' + self.python_api = spectral_norm_wrapper weight = np.random.random(self.weight_shape).astype('float64') u = np.random.normal(0.0, 1.0, self.u_shape).astype('float64') v = np.random.normal(0.0, 1.0, self.v_shape).astype('float64') diff --git a/python/paddle/fluid/tests/unittests/test_split_op.py b/python/paddle/fluid/tests/unittests/test_split_op.py index 40e7bff55e0bcc85f97c4f658bf91433ed083e07..d250302165bcbdc936a6e87627586c72f4eae3f5 100644 --- a/python/paddle/fluid/tests/unittests/test_split_op.py +++ b/python/paddle/fluid/tests/unittests/test_split_op.py @@ -15,7 +15,7 @@ import unittest import numpy as np -from op_test import OpTest, convert_float_to_uint16 +from eager_op_test import OpTest, convert_float_to_uint16 import paddle import paddle.fluid as fluid @@ -24,6 +24,8 @@ from paddle.fluid import Program, core, program_guard class TestSplitOp(OpTest): def setUp(self): + self.python_api = paddle.split + self.python_out_sig = ['out0', 'out1', 'out2'] self._set_op_type() self.dtype = self.get_dtype() axis = 1 @@ -62,6 +64,8 @@ class TestSplitOp(OpTest): # test with attr(num) class TestSplitOp_2(OpTest): def setUp(self): + self.python_api = paddle.split + self.python_out_sig = ['out0', 'out1', 'out2'] self._set_op_type() self.dtype = self.get_dtype() self.init_data() @@ -98,6 +102,8 @@ class TestSplitOp_2(OpTest): # attr(axis) is Tensor class TestSplitOp_AxisTensor(OpTest): def setUp(self): + self.python_api = paddle.split + self.python_out_sig = ['out0', 'out1', 'out2'] self._set_op_type() self.dtype = self.get_dtype() self.init_data() @@ -133,6 +139,8 @@ class TestSplitOp_AxisTensor(OpTest): # attr(sections) is list containing Tensor class TestSplitOp_SectionsTensor(OpTest): def setUp(self): + self.python_api = paddle.split + self.python_out_sig = ['out0', 'out1', 'out2'] self._set_op_type() self.dtype = self.get_dtype() self.init_data() @@ -178,6 +186,8 @@ class TestSplitOp_SectionsTensor(OpTest): class TestSplitOp_unk_section(OpTest): def setUp(self): + self.python_api = paddle.split + self.python_out_sig = ['out0', 'out1', 'out2'] self._set_op_type() self.dtype = self.get_dtype() self.init_data() diff --git a/python/paddle/fluid/tests/unittests/test_sum_op.py b/python/paddle/fluid/tests/unittests/test_sum_op.py index 6e9ff86cb8b7f83ad52c747375dd285ae989b2bc..b712b0bb161f6133f12282a8ee244f579096789e 100644 --- a/python/paddle/fluid/tests/unittests/test_sum_op.py +++ b/python/paddle/fluid/tests/unittests/test_sum_op.py @@ -19,6 +19,11 @@ import unittest import gradient_checker import numpy as np from decorator_helper import prog_scope +from eager_op_test import ( + OpTest, + convert_float_to_uint16, + convert_uint16_to_float, +) import paddle import paddle.fluid as fluid @@ -26,16 +31,19 @@ import paddle.fluid.core as core import paddle.inference as paddle_infer from paddle import enable_static from paddle.fluid.op import Operator -from paddle.fluid.tests.unittests.op_test import ( - OpTest, - convert_float_to_uint16, - convert_uint16_to_float, -) + + +def sum_wrapper(X, use_mkldnn=False): + res = 0 + for x in X: + res += x + return res class TestSumOp(OpTest): def setUp(self): self.op_type = "sum" + self.python_api = sum_wrapper self.init_kernel_type() self.use_mkldnn = False self.init_kernel_type() @@ -341,10 +349,14 @@ class TestSumBF16Op(OpTest): self.dtype = np.uint16 def test_check_output(self): - self.check_output() + # new dynamic graph mode does not support unit16 type + self.check_output(check_dygraph=False) def test_check_grad(self): - self.check_grad(['x0'], 'Out', numeric_grad_delta=0.5) + # new dynamic graph mode does not support unit16 type + self.check_grad( + ['x0'], 'Out', numeric_grad_delta=0.5, check_dygraph=False + ) class API_Test_Add_n(unittest.TestCase): diff --git a/python/paddle/fluid/tests/unittests/test_take_along_axis_op.py b/python/paddle/fluid/tests/unittests/test_take_along_axis_op.py index da3fa64417fe609f51c59790f962abd8100faccd..7abd86d19f676ae7abab5e7cbc5dbaa6051572ef 100644 --- a/python/paddle/fluid/tests/unittests/test_take_along_axis_op.py +++ b/python/paddle/fluid/tests/unittests/test_take_along_axis_op.py @@ -15,7 +15,7 @@ import unittest import numpy as np -from op_test import OpTest +from eager_op_test import OpTest import paddle from paddle.framework import core @@ -27,6 +27,7 @@ class TestTakeAlongAxisOp(OpTest): def setUp(self): self.init_data() self.op_type = "take_along_axis" + self.python_api = paddle.tensor.take_along_axis self.xnp = np.random.random(self.x_shape).astype(self.x_type) self.target = np.take_along_axis(self.xnp, self.index, self.axis) broadcast_shape_list = list(self.x_shape)