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fix annotations for Python >= 3.8 #5301

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Merged
merged 4 commits into from
Jan 28, 2022
Merged

fix annotations for Python >= 3.8 #5301

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b935c83
run mypy on Python 3.9
pmeier Jan 27, 2022
4574b38
appease mypy
pmeier Jan 28, 2022
c51fafa
Revert "run mypy on Python 3.9"
pmeier Jan 28, 2022
c1059bc
Merge branch 'main' into mypy-39
pmeier Jan 28, 2022
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1 change: 1 addition & 0 deletions setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,6 +58,7 @@ def write_version_file():
pytorch_dep += "==" + os.getenv("PYTORCH_VERSION")

requirements = [
"typing_extensions",
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PyTorch core already hard-depends on it: https://github.com/pytorch/pytorch/blob/be2dc8f2940d3c95941516a811be8c504910d1ea/setup.py#L408-L411

"numpy",
"requests",
pytorch_dep,
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4 changes: 3 additions & 1 deletion torchvision/datasets/stl10.py
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@@ -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
Expand Down Expand Up @@ -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)
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We already have self.labels: Optional[np.ndarray] above, should we remove one of these?

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I missed that. Let me have a look.

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))
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5 changes: 3 additions & 2 deletions torchvision/transforms/functional_pil.py
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Expand Up @@ -4,6 +4,7 @@
import numpy as np
import torch
from PIL import Image, ImageOps, ImageEnhance
from typing_extensions import Literal

try:
import accimage
Expand Down Expand Up @@ -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",
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That's a new one for me, Literally.

) -> Image.Image:

if not _is_pil_image(img):
Expand Down Expand Up @@ -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
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