Merge branch 'main' into update_batched_nms

Author: NicolasHug

torchvision/models/optical_flow/raft.py

@@ -486,7 +486,7 @@ def forward(self, image1, image2, num_flow_updates: int = 12):
         batch_size, _, h, w = image1.shape
         if (h, w) != image2.shape[-2:]:
             raise ValueError(f"input images should have the same shape, instead got ({h}, {w}) != {image2.shape[-2:]}")
-        if not (h % 8 == 0) and (w % 8 == 0):
+        if not ((h % 8 == 0) and (w % 8 == 0)):
             raise ValueError(f"input image H and W should be divisible by 8, instead got {h} (h) and {w} (w)")
 
         fmaps = self.feature_encoder(torch.cat([image1, image2], dim=0))

torchvision/transforms/v2/_color.py

@@ -134,7 +134,7 @@ def _check_input(
             raise TypeError(f"{name}={value} should be a single number or a sequence with length 2.")
 
         if not bound[0] <= value[0] <= value[1] <= bound[1]:
-            raise ValueError(f"{name} values should be between {bound}, but got {value}.")
+            raise ValueError(f"{name} values should be between {bound} and increasing, but got {value}.")
 
         return None if value[0] == value[1] == center else (float(value[0]), float(value[1]))
 

torchvision/transforms/v2/_geometry.py

@@ -567,7 +567,7 @@ class RandomRotation(Transform):
     Args:
         degrees (sequence or number): Range of degrees to select from.
             If degrees is a number instead of sequence like (min, max), the range of degrees
-            will be (-degrees, +degrees).
+            will be [-degrees, +degrees].
         interpolation (InterpolationMode, optional): Desired interpolation enum defined by
             :class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``.
             If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported.