add type annotations to torch.nn.modules.fold (pytorch#49479)

Summary:
closes pytorchgh-49478

Fixes pytorch#49478

Pull Request resolved: pytorch#49479

Reviewed By: mruberry

Differential Revision: D25723838

Pulled By: walterddr

fbshipit-source-id: 45c4cbd6f147b6dc4a5f5419c17578c49c201022

mypy.ini

@@ -76,9 +76,6 @@ ignore_errors = True
 [mypy-torch.nn.modules.conv]
 ignore_errors = True
 
-[mypy-torch.nn.modules.fold]
-ignore_errors = True
-
 [mypy-torch.nn.modules.module]
 ignore_errors = True
 

torch/nn/functional.pyi.in

@@ -1,7 +1,7 @@
 from torch import Tensor
 from torch.types import _size
 from typing import Any, Optional, Tuple, Dict, List, Callable, Sequence, Union
-from .common_types import _ratio_any_t, _size_1_t, _size_2_t, _size_3_t, _size_2_opt_t, _size_3_opt_t
+from .common_types import _ratio_any_t, _size_any_t, _size_1_t, _size_2_t, _size_3_t, _size_2_opt_t, _size_3_opt_t
 
 # 'TypedDict' is a new accepted type that represents a dictionary with a fixed set of allowed keys.
 # It is standards-track but not in `typing` yet. We leave this hear to be uncommented once the feature
@@ -335,12 +335,12 @@ def normalize(input: Tensor, p: float = ..., dim: int = ..., eps: float = ...,
 def assert_int_or_pair(arg: Any, arg_name: Any, message: Any) -> None: ...
 
 
-def unfold(input: Tensor, kernel_size: _size, dilation: _size = ..., padding: _size = ...,
-           stride: _size = ...) -> Tensor: ...
+def unfold(input: Tensor, kernel_size: _size_any_t, dilation: _size_any_t = ..., padding: _size_any_t = ...,
+           stride: _size_any_t = ...) -> Tensor: ...
 
 
-def fold(input: Tensor, output_size: _size, kernel_size: _size, dilation: _size = ..., padding: _size = ...,
-         stride: _size = ...) -> Tensor: ...
+def fold(input: Tensor, output_size: _size_any_t, kernel_size: _size_any_t, dilation: _size_any_t = ..., padding: _size_any_t = ...,
+         stride: _size_any_t = ...) -> Tensor: ...
 
 
 def multi_head_attention_forward(query: Tensor,