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Fix error, remove file from pyrefly checking (#165094)
Reported issue with formatting and parsing. Removing suppressions and avoiding this file in future type checking until we can get a more complete fix in . Pull Request resolved: https://github.com/pytorch/pytorch/pull/165094 Approved by: https://github.com/albanD
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PyTorch MergeBot
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48fe858fef
@ -33,6 +33,7 @@ project-excludes = [
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"torch/_export/utils.py",
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"torch/fx/experimental/unification/multipledispatch/__init__.py",
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"torch/nn/modules/__init__.py",
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"torch/nn/modules/rnn.py", # only remove when parsing errors are fixed
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"torch/_inductor/codecache.py",
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"torch/distributed/elastic/metrics/__init__.py",
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# ====
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@ -111,7 +111,6 @@ class RNNBase(Module):
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if (
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not isinstance(dropout, numbers.Number)
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# pyrefly: ignore # unsupported-operation
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or not 0 <= dropout <= 1
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or isinstance(dropout, bool)
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):
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@ -120,7 +119,6 @@ class RNNBase(Module):
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"representing the probability of an element being "
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"zeroed"
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)
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# pyrefly: ignore # unsupported-operation
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if dropout > 0 and num_layers == 1:
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warnings.warn(
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"dropout option adds dropout after all but last "
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@ -641,12 +639,10 @@ class RNN(RNNBase):
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@overload
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@torch._jit_internal._overload_method # noqa: F811
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# pyrefly: ignore # bad-override
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def forward(
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self,
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input: Tensor,
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hx: Optional[Tensor] = None,
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# pyrefly: ignore # bad-return
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) -> tuple[Tensor, Tensor]:
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pass
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@ -656,7 +652,6 @@ class RNN(RNNBase):
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self,
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input: PackedSequence,
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hx: Optional[Tensor] = None,
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# pyrefly: ignore # bad-return
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) -> tuple[PackedSequence, Tensor]:
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pass
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@ -782,7 +777,6 @@ class RNN(RNNBase):
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if isinstance(orig_input, PackedSequence):
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output_packed = PackedSequence(
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output,
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# pyrefly: ignore # bad-argument-type
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batch_sizes,
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sorted_indices,
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unsorted_indices,
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@ -1009,7 +1003,6 @@ class LSTM(RNNBase):
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# In the future, we should prevent mypy from applying contravariance rules here.
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# See torch/nn/modules/module.py::_forward_unimplemented
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# pyrefly: ignore # bad-override
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def check_forward_args(
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self,
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input: Tensor,
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@ -1043,12 +1036,10 @@ class LSTM(RNNBase):
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# Same as above, see torch/nn/modules/module.py::_forward_unimplemented
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@overload # type: ignore[override]
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@torch._jit_internal._overload_method # noqa: F811
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# pyrefly: ignore # bad-override
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def forward(
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self,
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input: Tensor,
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hx: Optional[tuple[Tensor, Tensor]] = None,
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# pyrefly: ignore # bad-return
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) -> tuple[Tensor, tuple[Tensor, Tensor]]: # noqa: F811
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pass
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@ -1059,7 +1050,6 @@ class LSTM(RNNBase):
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self,
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input: PackedSequence,
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hx: Optional[tuple[Tensor, Tensor]] = None,
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# pyrefly: ignore # bad-return
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) -> tuple[PackedSequence, tuple[Tensor, Tensor]]: # noqa: F811
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pass
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@ -1174,7 +1164,6 @@ class LSTM(RNNBase):
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if isinstance(orig_input, PackedSequence):
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output_packed = PackedSequence(
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output,
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# pyrefly: ignore # bad-argument-type
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batch_sizes,
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sorted_indices,
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unsorted_indices,
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@ -1343,12 +1332,10 @@ class GRU(RNNBase):
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@overload # type: ignore[override]
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@torch._jit_internal._overload_method # noqa: F811
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# pyrefly: ignore # bad-override
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def forward(
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self,
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input: Tensor,
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hx: Optional[Tensor] = None,
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# pyrefly: ignore # bad-return
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) -> tuple[Tensor, Tensor]: # noqa: F811
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pass
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@ -1358,7 +1345,6 @@ class GRU(RNNBase):
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self,
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input: PackedSequence,
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hx: Optional[Tensor] = None,
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# pyrefly: ignore # bad-return
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) -> tuple[PackedSequence, Tensor]: # noqa: F811
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pass
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@ -1453,7 +1439,6 @@ class GRU(RNNBase):
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if isinstance(orig_input, PackedSequence):
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output_packed = PackedSequence(
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output,
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# pyrefly: ignore # bad-argument-type
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batch_sizes,
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sorted_indices,
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unsorted_indices,
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