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Pyrefly suppressions 7/n (#164913)

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Adds suppressions to pyrefly will typecheck clean: https://github.com/pytorch/pytorch/issues/163283

Almost there!

Test plan:
dmypy restart && python3 scripts/lintrunner.py -a
pyrefly check

step 1: delete lines in the pyrefly.toml file from the project-excludes field
step 2: run pyrefly check
step 3: add suppressions, clean up unused suppressions
before: https://gist.github.com/maggiemoss/4b3bf2037014e116bc00706a16aef199

after:
 INFO 0 errors (6,884 ignored)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/164913
Approved by: https://github.com/oulgen
This commit is contained in:
Maggie Moss
2025-10-08 07:27:14 +00:00
committed by PyTorch MergeBot
parent 12d2ef557f
commit c855f8632e
89 changed files with 626 additions and 67 deletions
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9
torch/nn/modules/batchnorm.py
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@ -72,6 +72,7 @@ class _NormBase(Module):
torch.tensor(
0,
dtype=torch.long,
# pyrefly: ignore # bad-argument-type
**{k: v for k, v in factory_kwargs.items() if k != "dtype"},
),
)
@ -221,6 +222,7 @@ class _LazyNormBase(LazyModuleMixin, _NormBase):
dtype=None,
) -> None:
factory_kwargs = {"device": device, "dtype": dtype}
# pyrefly: ignore # bad-argument-type
super().__init__(
# affine and track_running_stats are hardcoded to False to
# avoid creating tensors that will soon be overwritten.
@ -234,22 +236,29 @@ class _LazyNormBase(LazyModuleMixin, _NormBase):
self.affine = affine
self.track_running_stats = track_running_stats
if self.affine:
# pyrefly: ignore # bad-argument-type
self.weight = UninitializedParameter(**factory_kwargs)
# pyrefly: ignore # bad-argument-type
self.bias = UninitializedParameter(**factory_kwargs)
if self.track_running_stats:
# pyrefly: ignore # bad-argument-type
self.running_mean = UninitializedBuffer(**factory_kwargs)
# pyrefly: ignore # bad-argument-type
self.running_var = UninitializedBuffer(**factory_kwargs)
self.num_batches_tracked = torch.tensor(
0,
dtype=torch.long,
# pyrefly: ignore # bad-argument-type
**{k: v for k, v in factory_kwargs.items() if k != "dtype"},
)
def reset_parameters(self) -> None:
# pyrefly: ignore # bad-argument-type
if not self.has_uninitialized_params() and self.num_features != 0:
super().reset_parameters()
def initialize_parameters(self, input) -> None: # type: ignore[override]
# pyrefly: ignore # bad-argument-type
if self.has_uninitialized_params():
self.num_features = input.shape[1]
if self.affine: