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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -40,10 +40,10 @@ from cutmix.utils import CutMixCrossEntropyLoss
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dataset = datasets.CIFAR100(args.cifarpath, train=True, download=True, transform=transform_train)
dataset = CutMix(dataset, num_class=100, beta=1.0, prob=0.5, num_mix=2) # this is paper's original setting for cifar.
dataset = CutMix(dataset, num_class=100, beta=1.0, prob=0.5, num_mix=1) # this is paper's original setting for cifar. you can mix more than 2 images using `num_mix`.
...

criterion = CutMixCrossEntropyLoss(True)
criterion = CutMixCrossEntropyLoss(True) # this is for soft targets; not required for torch >= 1.10.0.
for _ in range(num_epoch):
for input, target in loader: # input is cutmixed image's normalized tensor and target is soft-label which made by mixing 2 or more labels.
output = model(input)
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