[inductor][ut] unskip ut-pytorch-AtomGit

Mtest/_inductor/test_ceil.py+0-2

	@@ -2,7 +2,6 @@ import torch
2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests	2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests
3	from testutils import TestUtils	3	from testutils import TestUtils
4	import torch_npu	4	import torch_npu
5	-import unittest
6		5
7	class TestRelu(TestUtils):	6	class TestRelu(TestUtils):
8	def op_calc(self, first_element):	7	def op_calc(self, first_element):
	@@ -11,7 +10,6 @@ class TestRelu(TestUtils):
11		10
12	@parametrize('shape', TestUtils._pointwise_demo_shapes)	11	@parametrize('shape', TestUtils._pointwise_demo_shapes)
13	@parametrize('dtype', ['float32', 'float16', 'bfloat16'])	12	@parametrize('dtype', ['float32', 'float16', 'bfloat16'])
14	- @unittest.skip("CI failed")
15	def test_pointwise_cases(self, shape, dtype):	13	def test_pointwise_cases(self, shape, dtype):
16	first_element = self._generate_tensor(shape, dtype)	14	first_element = self._generate_tensor(shape, dtype)
17		15

Mtest/_inductor/test_clamp.py+0-6

	@@ -2,7 +2,6 @@ import torch
2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests	2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests
3	from testutils import TestUtils	3	from testutils import TestUtils
4	import torch_npu	4	import torch_npu
5	-import unittest
6		5
7	class TestClamp(TestUtils):	6	class TestClamp(TestUtils):
8		7
	@@ -11,7 +10,6 @@ class TestClamp(TestUtils):
11		10
12	@parametrize('shape', TestUtils._pointwise_demo_shapes)	11	@parametrize('shape', TestUtils._pointwise_demo_shapes)
13	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])	12	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])
14	- @unittest.skip("CI failed")
15	def test_pointwise_cases_minmax_is_tensor(self, shape, dtype):	13	def test_pointwise_cases_minmax_is_tensor(self, shape, dtype):
16	min_0 = self._generate_tensor(shape, dtype)	14	min_0 = self._generate_tensor(shape, dtype)
17	max_0 = self._generate_tensor(shape, dtype)	15	max_0 = self._generate_tensor(shape, dtype)
	@@ -27,7 +25,6 @@ class TestClamp(TestUtils):
27		25
28	@parametrize('shape', [(1,)])	26	@parametrize('shape', [(1,)])
29	@parametrize('dtype', ['float32'])	27	@parametrize('dtype', ['float32'])
30	- @unittest.skip("CI failed")
31	def test_pointwise_cases_single_scalar(self, shape, dtype):	28	def test_pointwise_cases_single_scalar(self, shape, dtype):
32	min_numel = 0	29	min_numel = 0
33	max_numel = 100	30	max_numel = 100
	@@ -42,7 +39,6 @@ class TestClamp(TestUtils):
42		39
43	@parametrize('shape', [(1024, 32)])	40	@parametrize('shape', [(1024, 32)])
44	@parametrize('dtype', ['int32'])	41	@parametrize('dtype', ['int32'])
45	- @unittest.skip("CI failed")
46	def test_pointwise_cases_minmax_is_number(self, shape, dtype):	42	def test_pointwise_cases_minmax_is_number(self, shape, dtype):
47	min_numel = 0	43	min_numel = 0
48	max_numel = 100	44	max_numel = 100
	@@ -58,7 +54,6 @@ class TestClamp(TestUtils):
58		54
59	@parametrize('shape', TestUtils._pointwise_demo_shapes)	55	@parametrize('shape', TestUtils._pointwise_demo_shapes)
60	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])	56	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])
61	- @unittest.skip("CI failed")
62	def test_pointwise_cases_max_only(self, shape, dtype):	57	def test_pointwise_cases_max_only(self, shape, dtype):
63	max_numel = 100	58	max_numel = 100
64		59
	@@ -73,7 +68,6 @@ class TestClamp(TestUtils):
73		68
74	@parametrize('shape', TestUtils._pointwise_demo_shapes)	69	@parametrize('shape', TestUtils._pointwise_demo_shapes)
75	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])	70	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])
76	- @unittest.skip("CI failed")
77	def test_pointwise_cases_min_only(self, shape, dtype):	71	def test_pointwise_cases_min_only(self, shape, dtype):
78	min_numel = 0	72	min_numel = 0
79		73

Mtest/_inductor/test_div.py+0-2

	@@ -2,7 +2,6 @@ import torch
2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests	2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests
3	from testutils import TestUtils	3	from testutils import TestUtils
4	import torch_npu	4	import torch_npu
5	-import unittest
6		5
7	class TestDiv(TestUtils):	6	class TestDiv(TestUtils):
8	def op_calc(self, first_element, second_element):	7	def op_calc(self, first_element, second_element):
	@@ -11,7 +10,6 @@ class TestDiv(TestUtils):
11		10
12	@parametrize('shape', TestUtils._pointwise_demo_shapes)	11	@parametrize('shape', TestUtils._pointwise_demo_shapes)
13	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])	12	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])
14	- @unittest.skip("CI failed")
15	def test_pointwise_cases(self, shape, dtype):	13	def test_pointwise_cases(self, shape, dtype):
16	first_element = self._generate_tensor(shape, dtype)	14	first_element = self._generate_tensor(shape, dtype)
17	second_element = self._generate_tensor(shape, dtype)	15	second_element = self._generate_tensor(shape, dtype)

Mtest/_inductor/test_exp.py+0-2

	@@ -2,7 +2,6 @@ import torch
2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests	2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests
3	from testutils import TestUtils	3	from testutils import TestUtils
4	import torch_npu	4	import torch_npu
5	-import unittest
6		5
7	class TestExp(TestUtils):	6	class TestExp(TestUtils):
8	def op_calc(self, first_element):	7	def op_calc(self, first_element):
	@@ -11,7 +10,6 @@ class TestExp(TestUtils):
11		10
12	@parametrize('shape', TestUtils._pointwise_demo_shapes)	11	@parametrize('shape', TestUtils._pointwise_demo_shapes)
13	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int64'])	12	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int64'])
14	- @unittest.skip("CI failed")
15	def test_pointwise_cases(self, shape, dtype):	13	def test_pointwise_cases(self, shape, dtype):
16	first_element = self._generate_tensor(shape, dtype)	14	first_element = self._generate_tensor(shape, dtype)
17		15

Mtest/_inductor/test_relu.py+0-2

	@@ -2,7 +2,6 @@ import torch
2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests	2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests
3	from testutils import TestUtils	3	from testutils import TestUtils
4	import torch_npu	4	import torch_npu
5	-import unittest
6		5
7		6
8	class TestRelu(TestUtils):	7	class TestRelu(TestUtils):
	@@ -12,7 +11,6 @@ class TestRelu(TestUtils):
12		11
13	@parametrize('shape', TestUtils._pointwise_demo_shapes)	12	@parametrize('shape', TestUtils._pointwise_demo_shapes)
14	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])	13	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])
15	- @unittest.skip("CI failed")
16	def test_pointwise_cases(self, shape, dtype):	14	def test_pointwise_cases(self, shape, dtype):
17	first_element = self._generate_tensor(shape, dtype)	15	first_element = self._generate_tensor(shape, dtype)
18		16

Mtest/_inductor/test_sqrt.py+0-2

	@@ -2,7 +2,6 @@ import torch
2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests	2	from torch.testing._internal.common_utils import run_tests, parametrize, instantiate_parametrized_tests
3	from testutils import TestUtils	3	from testutils import TestUtils
4	import torch_npu	4	import torch_npu
5	-import unittest
6		5
7		6
8	class TestSqrt(TestUtils):	7	class TestSqrt(TestUtils):
	@@ -12,7 +11,6 @@ class TestSqrt(TestUtils):
12		11
13	@parametrize('shape', TestUtils._pointwise_demo_shapes)	12	@parametrize('shape', TestUtils._pointwise_demo_shapes)
14	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])	13	@parametrize('dtype', ['float16', 'float32', 'bfloat16', 'int32', 'int64'])
15	- @unittest.skip("CI failed")
16	def test_pointwise_cases(self, shape, dtype):	14	def test_pointwise_cases(self, shape, dtype):
17	first_element = self._generate_tensor(shape, dtype, 1)	15	first_element = self._generate_tensor(shape, dtype, 1)
18		16