Official implementation of Unifying and Merging Well-trained Deep Neural Networks for Inference Stage.
Created by Yi-Min Chou , Yi-Ming Chan, Jia-Hong Lee, Chih-Yi Chiu, Chu-Song Chen
Fine-tuning: Finetune the merged model of two well-trained neural networks (Tensorflow implementation).
Inference: Test the speed of the merged model (C implementation).
NeuralMerger
├─────── Fine-tuning
└─────── Inference
1.Clone the NeuralMerger repository:
$ git clone --recursive https://github.com/ivclab/NeuralMerger.git
2.Follow the instruction in Fine-tuning and get the well-trained merged model.
3.Test the well-trained merged model on Inference.
Please cite following paper if these codes help your research:
@inproceedings{chou2018unifying,
title={Unifying and merging well-trained deep neural networks for inference stage},
author={Chou, Yi-Min and Chan, Yi-Ming and Lee, Jia-Hong and Chiu, Chih-Yi and Chen, Chu-Song},
booktitle={Proceedings of the 27th International Joint Conference on Artificial Intelligence},
pages={2049--2056},
year={2018},
organization={AAAI Press}
}
@inproceedings{chou2018merging,
title={Merging Deep Neural Networks for Mobile Devices},
author={Chou, Yi-Min and Chan, Yi-Ming and Lee, Jia-Hong and Chiu, Chih-Yi and Chen, Chu-Song},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops},
pages={1686--1694},
year={2018}
}
Please feel free to leave suggestions or comments to Yi-Min Chou([email protected]) , Yi-Ming Chan([email protected]), Jia-Hong Lee([email protected]), Chih-Yi Chiu([email protected]), Chu-Song Chen([email protected])