An unofficial PyTorch implementation of Unsupervised Data Augmentation for Consistency Training (UDA). The official Tensorflow implementation is here.
This code is only available in UDA for image classifications.
| CIFAR-10-4K | SVHN-1K | |
|---|---|---|
| Paper (WRN-28-2) | 95.68 ± 0.08 | 97.77 ± 0.07 |
| This code (WRN-28-2) | - | - |
| Acc. curve | - | - |
* This code has not been tested, but only part of my FixMatch code that has been tested several times has been modified.
- python 3.6+
- torch 1.4
- torchvision 0.5
- tensorboard
- numpy
- tqdm
- apex (optional)
@article{xie2019unsupervised,
title={Unsupervised Data Augmentation for Consistency Training},
author={Xie, Qizhe and Dai, Zihang and Hovy, Eduard and Luong, Minh-Thang and Le, Quoc V},
journal={arXiv preprint arXiv:1904.12848},
year={2019}
}
@article{cubuk2019randaugment,
title={RandAugment: Practical data augmentation with no separate search},
author={Cubuk, Ekin D and Zoph, Barret and Shlens, Jonathon and Le, Quoc V},
journal={arXiv preprint arXiv:1909.13719},
year={2019}
}