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Fix docs #7789

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Merged
NicolasHug merged 1 commit into from
Aug 1, 2023
Merged

Fix docs #7789

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10 changes: 5 additions & 5 deletions gallery/plot_cutmix_mixup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down Expand Up @@ -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:
Expand Down Expand Up @@ -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 = }")