[fix]modify ut and hf_Bert model bug-pytorch-AtomGit

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已合并

[fix]modify ut and hf_Bert model bug #37829

zzll创建于 6月8日从zhoujinning/pytorch： v2719 合入到 Ascend/pytorch： v2.7.1

[fix]modify ut and hf_Bert model bug #37829

已合并

zzll创建于 6月8日

从zhoujinning/pytorch v2719合入到Ascend/pytorch v2.7.1

共 17 个文件变更+36-36

Mtest/_inductor/test_cast_standard_pass.py+2-2

	@@ -27,8 +27,8 @@ class TestCastStandardPass(TestUtils):
27	std_result = self.op_calc(first_element)	27	std_result = self.op_calc(first_element)
28	with torch.no_grad():	28	with torch.no_grad():
29	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	29	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
30	- inductor_result = compiled_op_calc(first_element)	30	+ inductor_result = compiled_op_calc(first_element)
31	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	31	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
32		32
33		33
34	@parametrize('shape', [(256, 5)])	34	@parametrize('shape', [(256, 5)])

Mtest/_inductor/test_cat_slice_cat_pass.py+2-2

	@@ -62,8 +62,8 @@ class TestCatSliceCatPass(TestUtils):
62	std_result = self.op_calc(first_element)	62	std_result = self.op_calc(first_element)
63	with torch.no_grad():	63	with torch.no_grad():
64	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	64	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
65	- inductor_result = compiled_op_calc(first_element)	65	+ inductor_result = compiled_op_calc(first_element)
66	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	66	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
67		67
68		68
69	@parametrize('shape', [(1, 3, 64, 1024)])	69	@parametrize('shape', [(1, 3, 64, 1024)])

Mtest/_inductor/test_fold_add_pass.py+2-2

	@@ -29,8 +29,8 @@ class TestFoldAddPass(TestUtils):
29	std_result = self.op_calc(first_element)	29	std_result = self.op_calc(first_element)
30	with torch.no_grad():	30	with torch.no_grad():
31	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	31	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
32	- inductor_result = compiled_op_calc(first_element)	32	+ inductor_result = compiled_op_calc(first_element)
33	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	33	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
34		34
35		35
36	@parametrize('shape', [(1, 2, 3)])	36	@parametrize('shape', [(1, 2, 3)])

Mtest/_inductor/test_fold_cat_pass.py+2-2

	@@ -37,8 +37,8 @@ class TestFoldCatPass(TestUtils):
37	std_result = self.op_calc(t1, t2, t3, t4, t5)	37	std_result = self.op_calc(t1, t2, t3, t4, t5)
38	with torch.no_grad():	38	with torch.no_grad():
39	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	39	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
40	- inductor_result = compiled_op_calc(t1, t2, t3, t4, t5)	40	+ inductor_result = compiled_op_calc(t1, t2, t3, t4, t5)
41	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	41	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
42		42
43		43
44	@parametrize('shape', [(2, 4)])	44	@parametrize('shape', [(2, 4)])

Mtest/_inductor/test_fold_clone_pass.py+2-2

	@@ -29,8 +29,8 @@ class TestFoldClonePass(TestUtils):
29	std_result = self.op_calc(t1)	29	std_result = self.op_calc(t1)
30	with torch.no_grad():	30	with torch.no_grad():
31	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	31	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
32	- inductor_result = compiled_op_calc(t1)	32	+ inductor_result = compiled_op_calc(t1)
33	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	33	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
34		34
35		35
36	@parametrize('shape', [(1, 2, 3)])	36	@parametrize('shape', [(1, 2, 3)])

Mtest/_inductor/test_fold_detach_pass.py+2-2

	@@ -30,8 +30,8 @@ class TestFoldDetachPass(TestUtils):
30	std_result = self.op_calc(t1)	30	std_result = self.op_calc(t1)
31	with torch.no_grad():	31	with torch.no_grad():
32	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	32	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
33	- inductor_result = compiled_op_calc(t1)	33	+ inductor_result = compiled_op_calc(t1)
34	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	34	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
35		35
36		36
37	@parametrize('shape', [(3, 3)])	37	@parametrize('shape', [(3, 3)])

Mtest/_inductor/test_fold_div_pass.py+2-2

	@@ -30,8 +30,8 @@ class TestFoldDivPass(TestUtils):
30	std_result = self.op_calc(t1)	30	std_result = self.op_calc(t1)
31	with torch.no_grad():	31	with torch.no_grad():
32	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	32	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
33	- inductor_result = compiled_op_calc(t1)	33	+ inductor_result = compiled_op_calc(t1)
34	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	34	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
35		35
36		36
37	@parametrize('shape', [(2, 4, 8)])	37	@parametrize('shape', [(2, 4, 8)])

Mtest/_inductor/test_fold_expand_pass.py+2-2

	@@ -30,8 +30,8 @@ class TestFoldExpandPass(TestUtils):
30	std_result = self.op_calc(t1)	30	std_result = self.op_calc(t1)
31	with torch.no_grad():	31	with torch.no_grad():
32	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	32	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
33	- inductor_result = compiled_op_calc(t1)	33	+ inductor_result = compiled_op_calc(t1)
34	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	34	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
35		35
36		36
37	@parametrize('shape', [(256, 128, 1)])	37	@parametrize('shape', [(256, 128, 1)])

Mtest/_inductor/test_fold_mul_pass.py+2-2

	@@ -30,8 +30,8 @@ class TestFoldMulPass(TestUtils):
30	std_result = self.op_calc(t1)	30	std_result = self.op_calc(t1)
31	with torch.no_grad():	31	with torch.no_grad():
32	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	32	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
33	- inductor_result = compiled_op_calc(t1)	33	+ inductor_result = compiled_op_calc(t1)
34	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	34	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
35		35
36		36
37	@parametrize('shape', [(1, 2, 3)])	37	@parametrize('shape', [(1, 2, 3)])

Mtest/_inductor/test_fold_reduce_pass.py+2-2

	@@ -28,8 +28,8 @@ class TestFoldReducePass(TestUtils):
28	std_result = self.op_calc(t1)	28	std_result = self.op_calc(t1)
29	with torch.no_grad():	29	with torch.no_grad():
30	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	30	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
31	- inductor_result = compiled_op_calc(t1)	31	+ inductor_result = compiled_op_calc(t1)
32	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	32	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
33		33
34		34
35	@parametrize('shape', [(128, 1, 64, 1)])	35	@parametrize('shape', [(128, 1, 64, 1)])

Mtest/_inductor/test_fold_sink_view_pass.py+2-2

	@@ -29,8 +29,8 @@ class TestFoldSinkViewPass(TestUtils):
29	std_result = self.op_calc(t1)	29	std_result = self.op_calc(t1)
30	with torch.no_grad():	30	with torch.no_grad():
31	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	31	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
32	- inductor_result = compiled_op_calc(t1)	32	+ inductor_result = compiled_op_calc(t1)
33	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	33	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
34		34
35		35
36	@parametrize('shape', [(2, 3, 4)])	36	@parametrize('shape', [(2, 3, 4)])

Mtest/_inductor/test_fold_sub_pass.py+2-2

	@@ -33,8 +33,8 @@ class TestFoldSubPass(TestUtils):
33	std_result = self.op_calc(t1)	33	std_result = self.op_calc(t1)
34	with torch.no_grad():	34	with torch.no_grad():
35	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	35	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
36	- inductor_result = compiled_op_calc(t1)	36	+ inductor_result = compiled_op_calc(t1)
37	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	37	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
38		38
39		39
40	@parametrize('shape', [(1, 2, 3)])	40	@parametrize('shape', [(1, 2, 3)])

Mtest/_inductor/test_fold_to_copy_pass.py+2-2

	@@ -29,8 +29,8 @@ class TestFoldToCopyPass(TestUtils):
29	std_result = self.op_calc(t1)	29	std_result = self.op_calc(t1)
30	with torch.no_grad():	30	with torch.no_grad():
31	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	31	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
32	- inductor_result = compiled_op_calc(t1)	32	+ inductor_result = compiled_op_calc(t1)
33	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	33	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
34		34
35		35
36	@parametrize('shape', [(2, 4)])	36	@parametrize('shape', [(2, 4)])

Mtest/_inductor/test_fold_where_pass.py+2-2

	@@ -27,8 +27,8 @@ class TestFoldWherePass(TestUtils):
27	std_result = self.op_calc(t1)	27	std_result = self.op_calc(t1)
28	with torch.no_grad():	28	with torch.no_grad():
29	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	29	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
30	- inductor_result = compiled_op_calc(t1)	30	+ inductor_result = compiled_op_calc(t1)
31	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	31	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
32		32
33		33
34	@parametrize('shape', [(3, 4)])	34	@parametrize('shape', [(3, 4)])

Mtest/_inductor/test_multi_stream.py+4-4

	@@ -742,8 +742,8 @@ class TestMultiStreamPass(TestUtils):
742	std_result = self.multi_stream_test(arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1, arg6_1, arg7_1, arg8_1, arg9_1, arg10_1, arg11_1, arg12_1, arg13_1, arg14_1, arg15_1, arg16_1, arg17_1, arg18_1, arg19_1, arg20_1, arg21_1, arg22_1, arg23_1, arg24_1, arg25_1, arg26_1, arg27_1, arg28_1, arg29_1, arg30_1, arg31_1, arg32_1, arg33_1, arg34_1, arg35_1, arg36_1, arg37_1, arg38_1, arg39_1)	742	std_result = self.multi_stream_test(arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1, arg6_1, arg7_1, arg8_1, arg9_1, arg10_1, arg11_1, arg12_1, arg13_1, arg14_1, arg15_1, arg16_1, arg17_1, arg18_1, arg19_1, arg20_1, arg21_1, arg22_1, arg23_1, arg24_1, arg25_1, arg26_1, arg27_1, arg28_1, arg29_1, arg30_1, arg31_1, arg32_1, arg33_1, arg34_1, arg35_1, arg36_1, arg37_1, arg38_1, arg39_1)
743	with torch.no_grad():	743	with torch.no_grad():
744	compiled_op_calc = torch.compile(self.multi_stream_test, backend="inductor")	744	compiled_op_calc = torch.compile(self.multi_stream_test, backend="inductor")
745	- inductor_result = compiled_op_calc(arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1, arg6_1, arg7_1, arg8_1, arg9_1, arg10_1, arg11_1, arg12_1, arg13_1, arg14_1, arg15_1, arg16_1, arg17_1, arg18_1, arg19_1, arg20_1, arg21_1, arg22_1, arg23_1, arg24_1, arg25_1, arg26_1, arg27_1, arg28_1, arg29_1, arg30_1, arg31_1, arg32_1, arg33_1, arg34_1, arg35_1, arg36_1, arg37_1, arg38_1, arg39_1)	745	+ inductor_result = compiled_op_calc(arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1, arg6_1, arg7_1, arg8_1, arg9_1, arg10_1, arg11_1, arg12_1, arg13_1, arg14_1, arg15_1, arg16_1, arg17_1, arg18_1, arg19_1, arg20_1, arg21_1, arg22_1, arg23_1, arg24_1, arg25_1, arg26_1, arg27_1, arg28_1, arg29_1, arg30_1, arg31_1, arg32_1, arg33_1, arg34_1, arg35_1, arg36_1, arg37_1, arg38_1, arg39_1)
746	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	746	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
747		747
748	def op_calc(self, arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1):	748	def op_calc(self, arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1):
749	relu_1 = torch.ops.aten.relu.default(arg0_1)	749	relu_1 = torch.ops.aten.relu.default(arg0_1)
	@@ -781,8 +781,8 @@ class TestMultiStreamPass(TestUtils):
781	std_result = self.op_calc(arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1)	781	std_result = self.op_calc(arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1)
782	with torch.no_grad():	782	with torch.no_grad():
783	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	783	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
784	- inductor_result = compiled_op_calc(arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1)	784	+ inductor_result = compiled_op_calc(arg0_1, arg1_1, arg2_1, arg3_1, arg4_1, arg5_1)
785	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	785	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
786		786
787		787
788	instantiate_parametrized_tests(TestMultiStreamPass)	788	instantiate_parametrized_tests(TestMultiStreamPass)

Mtest/_inductor/test_pad_slice_pass.py+2-2

	@@ -31,8 +31,8 @@ class TestFoldPadSlicePass(TestUtils):
31	std_result = self.op_calc(t1)	31	std_result = self.op_calc(t1)
32	with torch.no_grad():	32	with torch.no_grad():
33	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")	33	compiled_op_calc = torch.compile(self.op_calc, backend="inductor")
34	- inductor_result = compiled_op_calc(t1)	34	+ inductor_result = compiled_op_calc(t1)
35	- self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)	35	+ self.assertEqual(std_result, inductor_result, atol=1e-3, rtol=1e-3)
36		36
37		37
38	@parametrize('shape', [(128, 50, 128)])	38	@parametrize('shape', [(128, 50, 128)])

Mtorch_npu/_inductor/fx_passes/ascend_custom_passes/ascend_graph_pass.py+2-2

	@@ -476,7 +476,7 @@ def fold_sink_view(graph: torch.fx.Graph) -> None:
476	name=node.name + "_replacement",	476	name=node.name + "_replacement",
477	)	477	)
478	propagate_fake_tensor(	478	propagate_fake_tensor(
479	- new_act_view, new_act, lambda fake: node.target(fake, node.args[1])	479	+ new_act_view, new_act, lambda fake: node.target(fake, view_shape)
480	)	480	)
481	user.replace_all_uses_with(new_act_view)	481	user.replace_all_uses_with(new_act_view)
482	graph.erase_node(user)	482	graph.erase_node(user)
	@@ -540,7 +540,7 @@ def fold_sink_view(graph: torch.fx.Graph) -> None:
540	propagate_fake_tensor(	540	propagate_fake_tensor(
541	new_add_view,	541	new_add_view,
542	new_add,	542	new_add,
543	- lambda fake: node.target(fake, node.args[1]),	543	+ lambda fake: node.target(fake, view_shape),
544	)	544	)
545	user.replace_all_uses_with(new_add_view)	545	user.replace_all_uses_with(new_add_view)
546	graph.erase_node(user)	546	graph.erase_node(user)