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sparse-structure-selection

This code is a re-implementation of the imagenet classification experiments in the paper Data-Driven Sparse Structure Selection for Deep Neural Networks (ECCV2018).

Citation

If you use our code in your research or wish to refer to the baseline results, please use the following BibTeX entry.

@article{SSS2018
  author =   {Zehao Huang and Naiyan Wang},
  title =    {Data-Driven Sparse Structure Selection for Deep Neural Networks},
  journal =  {ECCV},
  year =     {2018}
}

Implementation

This code is implemented by a modified MXNet which supports ResNeXt-like augmentation. (This version of MXNet does not support cudnn7)

ImageNet data preparation

Download the ImageNet dataset and create pass through rec (following tornadomeet's repository but using unchange mode)

Run

  • modify config/cfgs.py
  • python train.py

Results on ImageNet-1k

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  • Python 100.0%