KeepAugment_Pytorch

Unofficial implementation of "KeepAugment: A Simple Information-Preserving Data Augmentation Approach". CVPR2021

Results

CIFAR 10

Model	ResNet-18	Wide ResNet-28-10
Cutout	95.6±0.1(paepr)	96.9±0.1(paepr)
KeepCutout	96.2	97.2
KeepCutout (low resolution)	96.1	97.1
KeepCutout (early loss)	96.2	TODO
KeepCutout (low + early)	96.2	TODO

Model	ResNet-18	Wide ResNet-28-10
AutoAugment	96.0	97.3±0.1(paepr)
KeepAutoAugment	96.4	97.4
KeepAutoAugment (low resolution)	96.3	97.5
KeepAutoAugment (early loss)	96.3	97.4
KeepAutoAugment (low + early)	96.5	TODO

All results have slight differences(±0.1).

Run

The type of method is
'keep_cutout', 'keep_cutout_low', 'keep_cutout_early', 'keep_cutout_low_early',
'keep_autoaugment', 'keep_autoaugment_low', 'keep_autoaugment_early', 'keep_autoaugment_low_early'.

The type of model is 'resnet', 'wide_resnet'.

python train.py --model resnet --method keep_cutout

Any feedback on code simplification and incorrect implementation would be appreciated!

Referenced. Thank you all:+1:

baseline & cutout code : https://github.com/uoguelph-mlrg/Cutout
autoaugment code : https://github.com/DeepVoltaire/AutoAugment
saliency map code : https://github.com/sunnynevarekar/pytorch-saliency-maps