fix annotations for Python >= 3.8 (#5301)

* run mypy on Python 3.9

* appease mypy

* Revert "run mypy on Python 3.9"

This reverts commit b935c83.

setup.py

@@ -58,6 +58,7 @@ def write_version_file():
     pytorch_dep += "==" + os.getenv("PYTORCH_VERSION")
 
 requirements = [
+    "typing_extensions",
     "numpy",
     "requests",
     pytorch_dep,

torchvision/datasets/stl10.py

@@ -1,5 +1,5 @@
 import os.path
-from typing import Any, Callable, Optional, Tuple
+from typing import Any, Callable, Optional, Tuple, cast
 
 import numpy as np
 from PIL import Image
@@ -65,10 +65,12 @@ def __init__(
         self.labels: Optional[np.ndarray]
         if self.split == "train":
             self.data, self.labels = self.__loadfile(self.train_list[0][0], self.train_list[1][0])
+            self.labels = cast(np.ndarray, self.labels)
             self.__load_folds(folds)
 
         elif self.split == "train+unlabeled":
             self.data, self.labels = self.__loadfile(self.train_list[0][0], self.train_list[1][0])
+            self.labels = cast(np.ndarray, self.labels)
             self.__load_folds(folds)
             unlabeled_data, _ = self.__loadfile(self.train_list[2][0])
             self.data = np.concatenate((self.data, unlabeled_data))

torchvision/transforms/functional_pil.py

@@ -4,6 +4,7 @@
 import numpy as np
 import torch
 from PIL import Image, ImageOps, ImageEnhance
+from typing_extensions import Literal
 
 try:
     import accimage
@@ -130,7 +131,7 @@ def pad(
     img: Image.Image,
     padding: Union[int, List[int], Tuple[int, ...]],
     fill: Optional[Union[float, List[float], Tuple[float, ...]]] = 0,
-    padding_mode: str = "constant",
+    padding_mode: Literal["constant", "edge", "reflect", "symmetric"] = "constant",
 ) -> Image.Image:
 
     if not _is_pil_image(img):
@@ -189,7 +190,7 @@ def pad(
         if img.mode == "P":
             palette = img.getpalette()
             img = np.asarray(img)
-            img = np.pad(img, ((pad_top, pad_bottom), (pad_left, pad_right)), padding_mode)
+            img = np.pad(img, ((pad_top, pad_bottom), (pad_left, pad_right)), mode=padding_mode)
             img = Image.fromarray(img)
             img.putpalette(palette)
             return img