What's this

Implementation of Appendix A (Neural Architecture Search with Reinforcement Learning) by chainer

Dependencies

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

How to run

python main.py -p ./ -g 0 

Details about my implementation

All hyperparameters and network architecture are the same as in [1] except for some parts.

• 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.

• Learning rate schedule
  Learning rate is divided by 10 at [150, 170] epochs. The total number of epochs is 200.

• batch
  128

Cifar10 result

References

Neural Architecture Search with Reinforcement Learning [1]