Merge branch 'main' into main

Author: younessdkhissi

torchvision/models/mnasnet.py

@@ -173,7 +173,7 @@ def _load_from_state_dict(
     ) -> None:
         version = local_metadata.get("version", None)
         if version not in [1, 2]:
-            raise ValueError(f"version shluld be set to 1 or 2 instead of {version}")
+            raise ValueError(f"version should be set to 1 or 2 instead of {version}")
 
         if version == 1 and not self.alpha == 1.0:
             # In the initial version of the model (v1), stem was fixed-size.

torchvision/transforms/transforms.py

@@ -145,7 +145,15 @@ class PILToTensor:
 
     This transform does not support torchscript.
 
-    Converts a PIL Image (H x W x C) to a Tensor of shape (C x H x W).
+    Convert a PIL Image with H height, W width, and C channels to a Tensor of shape (C x H x W).
+
+    Example:
+        >>> from PIL import Image
+        >>> import torchvision.transforms as T
+        >>> img = Image.new("RGB", (320, 240))  # size (W=320, H=240)
+        >>> tensor = T.PILToTensor()(img)
+        >>> print(tensor.shape)
+        torch.Size([3, 240, 320])
     """
 
     def __init__(self) -> None:

torchvision/transforms/v2/_type_conversion.py

@@ -15,7 +15,15 @@ class PILToTensor(Transform):
 
     This transform does not support torchscript.
 
-    Converts a PIL Image (H x W x C) to a Tensor of shape (C x H x W).
+    Convert a PIL Image with H height, W width, and C channels to a Tensor of shape (C x H x W).
+
+    Example:
+        >>> from PIL import Image
+        >>> from torchvision.transforms import v2
+        >>> img = Image.new("RGB", (320, 240))  # size (W=320, H=240)
+        >>> tensor = v2.PILToTensor()(img)
+        >>> print(tensor.shape)
+        torch.Size([3, 240, 320])
     """
 
     _transformed_types = (PIL.Image.Image,)