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License: MIT License

Python 100.00%
audio-classification model-compression model-optimization neural-network-pruning pruning sparsification neural-network-compression

neural-network-pruning's Introduction

Simultaneously Learning Architectures and Features of Deep Neural Networks

This repository contains a reimplementation for paper "Simultaneously Learning Architectures and Features of Deep Neural Networks, ICANN 2019".

Usage

Clone this repo
git clone https://github.com/vi2enne/Neural-Network-Pruning
cd Neural-Network-Pruning

Python requirements

Currently, the code supports Python 3

  • numpy
  • PyTorch (>=1.1.0)
  • pandas
  • thop
  • sklearn

Download

Download audio spectrograms data from ISMIR2018 Tutorial from https://github.com/slychief/ismir2018_tutorial

python train.py -sr --filter-percent 0.5

If you use this code, please cite:

@inproceedings{wang2019simultaneously,
  title={Simultaneously learning architectures and features of deep neural networks},
  author={Wang, Tinghuai and Fan, Lixin and Wang, Huiling},
  booktitle={International Conference on Artificial Neural Networks},
  pages={275--287},
  year={2019},
  organization={Springer}
}

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