Implementation of Swapout by chainer

git clone https://github.com/nutszebra/swapout.git
cd swapout
git submodule init
git submodule update

python main.py -g 0

All hyperparameters and network architecture are the same as in [1] except for data-augmentation.

• Data augmentation
  Train: Pictures are randomly resized in the range of [32, 36], then 32x32 patches are extracted randomly and are normalized locally. Horizontal flipping is applied with 0.5 probability.
  Test: Pictures are resized to 32x32, then they are normalized locally. Single image test is used to calculate total accuracy.

• Stochastic inference
  Implemented

Swapout: Learning an ensemble of deep architectures [1]