MixUp

This is an implement and Improvement  on mixup: Beyond Empirical Risk Minimization https://arxiv.org/abs/1710.09412

The improvement

1. add backward
2. add mix rate

Two scenes:

The detail design of MixUp layer:

The results:

The symbol of resnet50 is writen by mxnet https://github.com/apache/incubator-mxnet/tree/master/example/image-classification/symbols, there have many versions. And i havenot do any optimizion for it. All the results are based on this baseline.

MixUp

Mixup in feature map （resnet50 head conv）

ERM

Usage

install mxnet0.12 The mixup is in:symbols/mixup.py you can use it in your codes like:

data ,label = mx.sym.Custom(data= data,label = label,alpha = 0.2,num_classes = num_classes,batch_size = batch_size,mix_rate =0.7,op_type = 'MixUp')

label is the vector like [4,8,...9]

download the dataset

http://data.mxnet.io/data/cifar10/cifar10_val.rec

http://data.mxnet.io/data/cifar10/cifar10_train.rec

train & test:

./train.sh
./test.sh

Reference

Zhang H, Cisse M, Dauphin Y N, et al. mixup: Beyond Empirical Risk Minimization[J]. arXiv preprint arXiv:1710.09412, 2017.