Update code to Python 3.7 compliance (#5125)

* Upgrade to py37

* Update

torchvision/datasets/_optical_flow.py

@@ -338,10 +338,10 @@ class FlyingThings3D(FlowDataset):
         directions = ("into_future", "into_past")
         for pass_name, camera, direction in itertools.product(passes, cameras, directions):
             image_dirs = sorted(glob(str(root / pass_name / split / "*/*")))
-            image_dirs = sorted([Path(image_dir) / camera for image_dir in image_dirs])
+            image_dirs = sorted(Path(image_dir) / camera for image_dir in image_dirs)
 
             flow_dirs = sorted(glob(str(root / "optical_flow" / split / "*/*")))
-            flow_dirs = sorted([Path(flow_dir) / direction / camera for flow_dir in flow_dirs])
+            flow_dirs = sorted(Path(flow_dir) / direction / camera for flow_dir in flow_dirs)
 
             if not image_dirs or not flow_dirs:
                 raise FileNotFoundError(

torchvision/datasets/food101.py

@@ -51,7 +51,7 @@ class Food101(VisionDataset):
 
         self._labels = []
         self._image_files = []
-        with open(self._meta_folder / f"{split}.json", "r") as f:
+        with open(self._meta_folder / f"{split}.json") as f:
             metadata = json.loads(f.read())
 
         self.classes = sorted(metadata.keys())

torchvision/io/_video_opt.py

@@ -71,7 +71,7 @@ def _validate_pts(pts_range: Tuple[int, int]) -> None:
         assert (
             pts_range[0] <= pts_range[1]
         ), """Start pts should not be smaller than end pts, got
-            start pts: {0:d} and end pts: {1:d}""".format(
+            start pts: {:d} and end pts: {:d}""".format(
             pts_range[0],
             pts_range[1],
         )

torchvision/models/optical_flow/raft.py

@@ -74,7 +74,7 @@ class BottleneckBlock(nn.Module):
     """Slightly modified BottleNeck block (extra relu and biases)"""
 
     def __init__(self, in_channels, out_channels, *, norm_layer, stride=1):
-        super(BottleneckBlock, self).__init__()
+        super().__init__()
 
         # See note in ResidualBlock for the reason behind bias=True
         self.convnormrelu1 = ConvNormActivation(