Gate Decorator (NeurIPS 2019)

This repo contains required scripts to reproduce results from paper:

Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks, in NeurIPS 2019.

Requirements

python 3.6+ and PyTorch 1.0

The code has been tested only with PyTorch 1.0. We will test it with newer version later.

Installation

1. clone the code
2. pip install --upgrade git+https://github.com/youzhonghui/pytorch-OpCounter.git
3. pip install tqdm
4. mkdir data

How to use

In the run/resnet-56 folder we provide an example to show how to use the code.

If you want to run the code, you may need install jupyter notebook

TODO

• Basic running example.
• PyTorch 1.2 compatibility test.
• ResNet-50 pruned model.

Citation

If you use this code for your research, please cite our papers.

@inproceedings{zhonghui2019gate,
  title={Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks},
  author={Zhonghui You and
          Kun Yan and
          Jinmian Ye and
          Meng Ma and
          Ping Wang},
  booktitle={Advances in Neural Information Processing Systems},
  year={2019}
}