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Unverified Commit f524cd3a authored by Nicolas Hug's avatar Nicolas Hug Committed by GitHub
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Fix docs (#7789)

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gallery/plot_cutmix_mixup.py
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...@@ -4,8 +4,8 @@ ...@@ -4,8 +4,8 @@
How to use CutMix and MixUp How to use CutMix and MixUp
=========================== ===========================
:class:`~torchvision.transforms.v2.Cutmix` and :class:`~torchvision.transforms.v2.CutMix` and
:class:`~torchvision.transforms.v2.Mixup` are popular augmentation strategies :class:`~torchvision.transforms.v2.MixUp` are popular augmentation strategies
that can improve classification accuracy. that can improve classification accuracy.
These transforms are slightly different from the rest of the Torchvision These transforms are slightly different from the rest of the Torchvision
...@@ -79,8 +79,8 @@ for images, labels in dataloader: ...@@ -79,8 +79,8 @@ for images, labels in dataloader:
dataloader = DataLoader(dataset, batch_size=4, shuffle=True) dataloader = DataLoader(dataset, batch_size=4, shuffle=True)
cutmix = v2.Cutmix(num_classes=NUM_CLASSES) cutmix = v2.CutMix(num_classes=NUM_CLASSES)
mixup = v2.Mixup(num_classes=NUM_CLASSES) mixup = v2.MixUp(num_classes=NUM_CLASSES)
cutmix_or_mixup = v2.RandomChoice([cutmix, mixup]) cutmix_or_mixup = v2.RandomChoice([cutmix, mixup])
for images, labels in dataloader: for images, labels in dataloader:
...@@ -148,5 +148,5 @@ def labels_getter(batch): ...@@ -148,5 +148,5 @@ def labels_getter(batch):
return batch["target"]["classes"] 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 = }") print(f"{out['imgs'].shape = }, {out['target']['classes'].shape = }")
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