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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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54
torch/nn/modules/rnn.py
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@ -111,6 +111,7 @@ class RNNBase(Module):
if (
not isinstance(dropout, numbers.Number)
# pyrefly: ignore # unsupported-operation
or not 0 <= dropout <= 1
or isinstance(dropout, bool)
):
@ -119,6 +120,7 @@ class RNNBase(Module):
"representing the probability of an element being "
"zeroed"
)
# pyrefly: ignore # unsupported-operation
if dropout > 0 and num_layers == 1:
warnings.warn(
"dropout option adds dropout after all but last "
@ -639,15 +641,22 @@ class RNN(RNNBase):
@overload
@torch._jit_internal._overload_method # noqa: F811
# pyrefly: ignore # bad-override
def forward(
self, input: Tensor, hx: Optional[Tensor] = None
self,
input: Tensor,
hx: Optional[Tensor] = None,
# pyrefly: ignore # bad-return
) -> tuple[Tensor, Tensor]:
pass
@overload
@torch._jit_internal._overload_method # noqa: F811
def forward(
self, input: PackedSequence, hx: Optional[Tensor] = None
self,
input: PackedSequence,
hx: Optional[Tensor] = None,
# pyrefly: ignore # bad-return
) -> tuple[PackedSequence, Tensor]:
pass
@ -772,7 +781,11 @@ class RNN(RNNBase):
if isinstance(orig_input, PackedSequence):
output_packed = PackedSequence(
output, batch_sizes, sorted_indices, unsorted_indices
output,
# pyrefly: ignore # bad-argument-type
batch_sizes,
sorted_indices,
unsorted_indices,
)
return output_packed, self.permute_hidden(hidden, unsorted_indices)
@ -996,6 +1009,7 @@ class LSTM(RNNBase):
# In the future, we should prevent mypy from applying contravariance rules here.
# See torch/nn/modules/module.py::_forward_unimplemented
# pyrefly: ignore # bad-override
def check_forward_args(
self,
input: Tensor,
@ -1029,8 +1043,12 @@ class LSTM(RNNBase):
# Same as above, see torch/nn/modules/module.py::_forward_unimplemented
@overload # type: ignore[override]
@torch._jit_internal._overload_method # noqa: F811
# pyrefly: ignore # bad-override
def forward(
self, input: Tensor, hx: Optional[tuple[Tensor, Tensor]] = None
self,
input: Tensor,
hx: Optional[tuple[Tensor, Tensor]] = None,
# pyrefly: ignore # bad-return
) -> tuple[Tensor, tuple[Tensor, Tensor]]: # noqa: F811
pass
@ -1038,7 +1056,10 @@ class LSTM(RNNBase):
@overload
@torch._jit_internal._overload_method # noqa: F811
def forward(
self, input: PackedSequence, hx: Optional[tuple[Tensor, Tensor]] = None
self,
input: PackedSequence,
hx: Optional[tuple[Tensor, Tensor]] = None,
# pyrefly: ignore # bad-return
) -> tuple[PackedSequence, tuple[Tensor, Tensor]]: # noqa: F811
pass
@ -1152,7 +1173,11 @@ class LSTM(RNNBase):
# xxx: isinstance check needs to be in conditional for TorchScript to compile
if isinstance(orig_input, PackedSequence):
output_packed = PackedSequence(
output, batch_sizes, sorted_indices, unsorted_indices
output,
# pyrefly: ignore # bad-argument-type
batch_sizes,
sorted_indices,
unsorted_indices,
)
return output_packed, self.permute_hidden(hidden, unsorted_indices)
else:
@ -1318,15 +1343,22 @@ class GRU(RNNBase):
@overload # type: ignore[override]
@torch._jit_internal._overload_method # noqa: F811
# pyrefly: ignore # bad-override
def forward(
self, input: Tensor, hx: Optional[Tensor] = None
self,
input: Tensor,
hx: Optional[Tensor] = None,
# pyrefly: ignore # bad-return
) -> tuple[Tensor, Tensor]: # noqa: F811
pass
@overload
@torch._jit_internal._overload_method # noqa: F811
def forward(
self, input: PackedSequence, hx: Optional[Tensor] = None
self,
input: PackedSequence,
hx: Optional[Tensor] = None,
# pyrefly: ignore # bad-return
) -> tuple[PackedSequence, Tensor]: # noqa: F811
pass
@ -1420,7 +1452,11 @@ class GRU(RNNBase):
# xxx: isinstance check needs to be in conditional for TorchScript to compile
if isinstance(orig_input, PackedSequence):
output_packed = PackedSequence(
output, batch_sizes, sorted_indices, unsorted_indices
output,
# pyrefly: ignore # bad-argument-type
batch_sizes,
sorted_indices,
unsorted_indices,
)
return output_packed, self.permute_hidden(hidden, unsorted_indices)
else: