Aaron Orenstein
62bcdc0ac9
Flip default value for mypy disallow_untyped_defs [4/11] ( #127841 )
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See #127836 for details.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127841
Approved by: https://github.com/oulgen
2024-06-08 18:36:48 +00:00
Edward Z. Yang
3bf922a6ce
Apply UFMT to low traffic torch modules ( #106249 )
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Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/106249
Approved by: https://github.com/Skylion007
2023-07-29 23:37:30 +00:00
Xuehai Pan
5b1cedacde
[BE] [2/3] Rewrite super() calls in functorch and torch ( #94588 )
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Rewrite Python built-in class `super()` calls. Only non-semantic changes should be applied.
- #94587
- #94588
- #94592
Also, methods with only a `super()` call are removed:
```diff
class MyModule(nn.Module):
- def __init__(self):
- super().__init__()
-
def forward(self, ...):
...
```
Some cases that change the semantics should be kept unchanged. E.g.:
f152a79be9/caffe2/python/net_printer.py (L184-L190)f152a79be9/test/test_jit_fuser_te.py (L2628-L2635)https://github.com/pytorch/pytorch/pull/94588
Approved by: https://github.com/ezyang , https://github.com/albanD
2023-02-10 21:16:33 +00:00
Aaron Gokaslan
8fce9a09cd
[BE]: pyupgrade Python to 3.8 - imports and object inheritance only ( #94308 )
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Apply parts of pyupgrade to torch (starting with the safest changes).
This PR only does two things: removes the need to inherit from object and removes unused future imports.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94308
Approved by: https://github.com/ezyang , https://github.com/albanD
2023-02-07 21:10:56 +00:00
Xiang Gao
20ac736200
Remove py2 compatible future imports ( #44735 )
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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/44735
Reviewed By: mruberry
Differential Revision: D23731306
Pulled By: ezyang
fbshipit-source-id: 0ba009a99e475ddbe22981be8ac636f8a1c8b02f
2020-09-16 12:55:57 -07:00
Kimish Patel
4c30fc7238
Integrate XNNPACK with custom class for packing weights. ( #34047 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34047
This PR integrates the added xnnpack conv2d and linear op via
custom class registration for packed weights. The packed struct
is serializable.
Test Plan:
python test test/test_xnnpack_integration.py
Imported from OSS
Differential Revision: D20185657
fbshipit-source-id: fc7e692d8f913e493b293b02d92f4e78536d7698
2020-03-14 12:51:56 -07:00
