This is implementation of Noisy Student [paper][tensorflow] in PyTorch using smaller dataset(CIFAR10/CIFAR100) and smaller model architecture(ResNet).

• RandAugment : Substituted to AutoAugment

• Dropout : O
• Stochastic Depth : X

• gamma 0.97 (every 4.8 epochs if small model 700 epochs / every 2.4 epochs if large model 350 epochs) : O? X?

• increase test time crop size & fine tune : X

• filter images that the teacher has low confidences on : O
• balance the number of unlabeled images for each class : X

To run the code,

        python main.py \
            --lr=0.001 \
            --dataset='CIFAR10'