[Fix] Enable UT for isin.Tensor_Tensor.-pytorch-AtomGit

已合并

[Fix] Enable UT for isin.Tensor_Tensor. #13576

liu-jiaweikf创建于 2024年8月7日从refs/pull/13576/head 合入到 master

[Fix] Enable UT for isin.Tensor_Tensor. #13576

已合并

liu-jiaweikf创建于 2024年8月7日

从refs/pull/13576/head合入到master

共 2 个文件变更+17-22

Mtest/test_sort_and_select.py+16-12

	@@ -6,16 +6,19 @@ import numpy as np
6	import torch	6	import torch
7	from torch import nan	7	from torch import nan
8	from torch.testing import make_tensor	8	from torch.testing import make_tensor
9	-	9	+from torch.testing._internal.common_dtype import (all_types, all_types_and, floating_types_and,
10	-from torch.testing._internal.common_dtype import all_types, all_types_and, floating_types_and, integral_types	10	+ integral_types, _dispatch_dtypes)
11	from torch.testing._internal.common_utils import (TestCase, run_tests, slowTest, skipIfTorchDynamo)	11	from torch.testing._internal.common_utils import (TestCase, run_tests, slowTest, skipIfTorchDynamo)
12	-import torch_npu
13	-import torch_npu.testing
14	from torch.testing._internal.common_device_type import \	12	from torch.testing._internal.common_device_type import \
15	(instantiate_device_type_tests, dtypes, onlyNativeDeviceTypes,	13	(instantiate_device_type_tests, dtypes, onlyNativeDeviceTypes,
16	onlyPRIVATEUSE1, dtypesIfPRIVATEUSE1, dtypesIfCPU, onlyCPU, largeTensorTest)	14	onlyPRIVATEUSE1, dtypesIfPRIVATEUSE1, dtypesIfCPU, onlyCPU, largeTensorTest)
17		15
		16	+import torch_npu
		17	+import torch_npu.testing
		18	+
18	SIZE = 100	19	SIZE = 100
		20	+all_types_without_double = _dispatch_dtypes((torch.half, torch.float32, torch.uint8,
		21	+ torch.int8, torch.int16, torch.int32, torch.int64))
19		22
20		23
21	class TestSortAndSelect(TestCase):	24	class TestSortAndSelect(TestCase):
	@@ -1014,6 +1017,7 @@ class TestSortAndSelect(TestCase):
1014	self.assertEqual(res[0], ref[0].squeeze())	1017	self.assertEqual(res[0], ref[0].squeeze())
1015	self.assertEqual(res[1], ref[1].squeeze())	1018	self.assertEqual(res[1], ref[1].squeeze())
1016		1019
		1020	+ # isin.Tensor_Tensor do not support float64 currently.
1017	@dtypes(*all_types())	1021	@dtypes(*all_types())
1018	@dtypesIfPRIVATEUSE1(*all_types_and(torch.half))	1022	@dtypesIfPRIVATEUSE1(*all_types_and(torch.half))
1019	def test_isin(self, device, dtype):	1023	def test_isin(self, device, dtype):
	@@ -1026,7 +1030,7 @@ class TestSortAndSelect(TestCase):
1026	self.assertEqual(x, y)	1030	self.assertEqual(x, y)
1027		1031
1028	# multi-dim tensor, multi-dim tensor	1032	# multi-dim tensor, multi-dim tensor
1029	- a = torch.arange(24, device=device, dtype=dtype).reshape([2, 3, 4])	1033	+ a = torch.tensor(np.arange(24)).to(dtype).to(device).reshape([2, 3, 4])
1030	b = torch.tensor([[10, 20, 30], [0, 1, 3], [11, 22, 33]], device=device, dtype=dtype)	1034	b = torch.tensor([[10, 20, 30], [0, 1, 3], [11, 22, 33]], device=device, dtype=dtype)
1031	assert_isin_equal(a, b)	1035	assert_isin_equal(a, b)
1032		1036
	@@ -1104,14 +1108,14 @@ class TestSortAndSelect(TestCase):
1104		1108
1105	# multi-dimensional input case using sort-based algo	1109	# multi-dimensional input case using sort-based algo
1106	for assume_unique in [False, True]:	1110	for assume_unique in [False, True]:
1107	- a = torch.arange(6, device=device, dtype=dtype).reshape([2, 3])	1111	+ a = torch.tensor(np.arange(6)).to(dtype).to(device).reshape([2, 3])
1108	- b = torch.arange(3, 30, device=device, dtype=dtype)	1112	+ b = torch.tensor(np.arange(3, 30)).to(dtype).to(device)
1109	ec = define_expected([[False, False, False], [True, True, True]], invert=invert)	1113	ec = define_expected([[False, False, False], [True, True, True]], invert=invert)
1110	c = torch.isin(a, b, invert=invert, assume_unique=assume_unique)	1114	c = torch.isin(a, b, invert=invert, assume_unique=assume_unique)
1111	self.assertEqual(c, ec)	1115	self.assertEqual(c, ec)
1112		1116
1113	def test_isin_different_dtypes(self, device):	1117	def test_isin_different_dtypes(self, device):
1114	- supported_types = all_types() if device == 'cpu' else all_types_and(torch.half)	1118	+ supported_types = all_types() if device == 'cpu' else all_types_without_double
1115	for mult in [1, 10]:	1119	for mult in [1, 10]:
1116	for assume_unique in [False, True]:	1120	for assume_unique in [False, True]:
1117	for dtype1, dtype2 in product(supported_types, supported_types):	1121	for dtype1, dtype2 in product(supported_types, supported_types):
	@@ -1124,13 +1128,13 @@ class TestSortAndSelect(TestCase):
1124	@onlyPRIVATEUSE1	1128	@onlyPRIVATEUSE1
1125	@dtypes(*all_types())	1129	@dtypes(*all_types())
1126	def test_isin_different_devices(self, device, dtype):	1130	def test_isin_different_devices(self, device, dtype):
1127	- a = torch.arange(6, device=device, dtype=dtype).reshape([2, 3])	1131	+ a = torch.tensor(np.arange(6)).to(dtype).to(device).reshape([2, 3])
1128	- b = torch.arange(3, 30, device='cpu', dtype=dtype)	1132	+ b = torch.tensor(np.arange(3, 30)).to(dtype).to('cpu')
1129	with self.assertRaises(RuntimeError):	1133	with self.assertRaises(RuntimeError):
1130	torch.isin(a, b)	1134	torch.isin(a, b)
1131		1135
1132	- c = torch.arange(6, device='cpu', dtype=dtype).reshape([2, 3])	1136	+ c = torch.tensor(np.arange(6)).to(dtype).to('cpu').reshape([2, 3])
1133	- d = torch.arange(3, 30, device=device, dtype=dtype)	1137	+ d = torch.tensor(np.arange(3, 30)).to(dtype).to(device)
1134	with self.assertRaises(RuntimeError):	1138	with self.assertRaises(RuntimeError):
1135	torch.isin(c, d)	1139	torch.isin(c, d)
1136		1140

Mtest/unsupported_test_cases/.pytorch-disabled-tests.json+1-10

	@@ -2032,18 +2032,9 @@
2032	"test_nonzero_npu_uint8 (__main__.TestShapeOpsPRIVATEUSE1)": ["", [""]],	2032	"test_nonzero_npu_uint8 (__main__.TestShapeOpsPRIVATEUSE1)": ["", [""]],
2033	"test_sparse_dense_dim_npu_complex128 (__main__.TestShapeOpsPRIVATEUSE1)": ["", [""]],	2033	"test_sparse_dense_dim_npu_complex128 (__main__.TestShapeOpsPRIVATEUSE1)": ["", [""]],
2034	"test_trace_npu_float64 (__main__.TestShapeOpsPRIVATEUSE1)": ["", [""]],	2034	"test_trace_npu_float64 (__main__.TestShapeOpsPRIVATEUSE1)": ["", [""]],
2035	- "test_isin_different_devices_npu_float32 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2036	"test_isin_different_devices_npu_float64 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],	2035	"test_isin_different_devices_npu_float64 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2037	- "test_isin_different_devices_npu_int16 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2038	- "test_isin_different_devices_npu_int32 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2039	- "test_isin_different_devices_npu_int64 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2040	- "test_isin_different_devices_npu_int8 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2041	- "test_isin_different_devices_npu_uint8 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2042	- "test_isin_different_dtypes_npu (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2043	"test_isin_npu_float16 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],	2036	"test_isin_npu_float16 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2044	- "test_isin_npu_int16 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],	2037	+ "test_isin_npu_float64 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2045	- "test_isin_npu_int8 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2046	- "test_isin_npu_uint8 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2047	"test_kthvalue_npu_float64 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],	2038	"test_kthvalue_npu_float64 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2048	"test_kthvalue_scalar_npu_float32 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],	2039	"test_kthvalue_scalar_npu_float32 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],
2049	"test_msort_npu_bfloat16 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],	2040	"test_msort_npu_bfloat16 (__main__.TestSortAndSelectPRIVATEUSE1)": ["", [""]],