Fix docs

pytorch · Aug 1, 2023 · 0cfd88d · 0cfd88d
1 parent 3e4e353
commit 0cfd88d
Showing 1 changed file with 5 additions and 5 deletions.
diff --git a/gallery/plot_cutmix_mixup.py b/gallery/plot_cutmix_mixup.py
@@ -4,8 +4,8 @@
 How to use CutMix and MixUp
 ===========================
 
-:class:`~torchvision.transforms.v2.Cutmix` and
-:class:`~torchvision.transforms.v2.Mixup` are popular augmentation strategies
+:class:`~torchvision.transforms.v2.CutMix` and
+:class:`~torchvision.transforms.v2.MixUp` are popular augmentation strategies
 that can improve classification accuracy.
 
 These transforms are slightly different from the rest of the Torchvision
@@ -79,8 +79,8 @@
 
 dataloader = DataLoader(dataset, batch_size=4, shuffle=True)
 
-cutmix = v2.Cutmix(num_classes=NUM_CLASSES)
-mixup = v2.Mixup(num_classes=NUM_CLASSES)
+cutmix = v2.CutMix(num_classes=NUM_CLASSES)
+mixup = v2.MixUp(num_classes=NUM_CLASSES)
 cutmix_or_mixup = v2.RandomChoice([cutmix, mixup])
 
 for images, labels in dataloader:
@@ -148,5 +148,5 @@ def labels_getter(batch):
     return batch["target"]["classes"]
 
 
-out = v2.Cutmix(num_classes=NUM_CLASSES, labels_getter=labels_getter)(batch)
+out = v2.CutMix(num_classes=NUM_CLASSES, labels_getter=labels_getter)(batch)
 print(f"{out['imgs'].shape = }, {out['target']['classes'].shape = }")