Replacing all torch.jit.annotations with typing (#3174)

* Replacing all torch.jit.annotations with typing

* Replacing remaining typing

torchvision/ops/ps_roi_align.py

@@ -2,7 +2,6 @@ import torch
 from torch import nn, Tensor
 
 from torch.nn.modules.utils import _pair
-from torch.jit.annotations import List, Tuple
 
 from torchvision.extension import _assert_has_ops
 from ._utils import convert_boxes_to_roi_format, check_roi_boxes_shape

torchvision/ops/ps_roi_pool.py

@@ -2,7 +2,6 @@ import torch
 from torch import nn, Tensor
 
 from torch.nn.modules.utils import _pair
-from torch.jit.annotations import List, Tuple
 
 from torchvision.extension import _assert_has_ops
 from ._utils import convert_boxes_to_roi_format, check_roi_boxes_shape

torchvision/ops/roi_align.py

@@ -2,7 +2,7 @@ import torch
 from torch import nn, Tensor
 
 from torch.nn.modules.utils import _pair
-from torch.jit.annotations import List, BroadcastingList2
+from torch.jit.annotations import BroadcastingList2
 
 from torchvision.extension import _assert_has_ops
 from ._utils import convert_boxes_to_roi_format, check_roi_boxes_shape

torchvision/ops/roi_pool.py

@@ -2,7 +2,7 @@ import torch
 from torch import nn, Tensor
 
 from torch.nn.modules.utils import _pair
-from torch.jit.annotations import List, BroadcastingList2
+from torch.jit.annotations import BroadcastingList2
 
 from torchvision.extension import _assert_has_ops
 from ._utils import convert_boxes_to_roi_format, check_roi_boxes_shape

torchvision/transforms/autoaugment.py

@@ -3,8 +3,7 @@ import torch
 
 from enum import Enum
 from torch import Tensor
-from torch.jit.annotations import List, Tuple
-from typing import Optional
+from typing import List, Tuple, Optional
 
 from . import functional as F, InterpolationMode
 

torchvision/transforms/functional.py

@@ -2,14 +2,13 @@ import math
 import numbers
 import warnings
 from enum import Enum
-from typing import Any, Optional
 
 import numpy as np
 from PIL import Image
 
 import torch
 from torch import Tensor
-from torch.jit.annotations import List, Tuple
+from typing import List, Tuple, Any, Optional
 
 try:
     import accimage

torchvision/transforms/functional_tensor.py

 import warnings
-from typing import Optional, Tuple
 
 import torch
 from torch import Tensor
 from torch.nn.functional import grid_sample, conv2d, interpolate, pad as torch_pad
-from torch.jit.annotations import List, BroadcastingList2
+from torch.jit.annotations import BroadcastingList2
+from typing import Optional, Tuple, List
 
 
 def _is_tensor_a_torch_image(x: Tensor) -> bool: