Unverified Commit f524cd3a authored by Nicolas Hug's avatar Nicolas Hug Committed by GitHub
Browse files

Fix docs (#7789)

parent 3e4e353d
......@@ -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 @@ for images, labels in dataloader:
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 = }")
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