DiamondSheep / DPL_Compression

the official repository for IEEE ICDM 2021 paper

This is the official repository for IEEE ICDM 2021 paper: Dictionary Pair-based Data-Free Fast Deep Neural Network Compression

How to run

1. add soft link to your dataset folder which should be organized as following:

   data
    |
    --imagenet
        |
        --ILSVRC2012_img_val.lmdb
        --ILSVRC2012_img_train.lmdb (unused)
    --cifar10
   

   (or modify the source code to fit your environment)
2. run script

   sh run_DPL_Compress.sh
   

   It will make directories to save results and reconstructed path files. And pre-trained models from PyTorchcv will be downloaded

Noted that we implement evaluation on ImageNet with lmdb, the code of get_imagenet.py should be modified to fit your environment.

Further Improvement

This conference paper is invited for Knowledge and Information Systems (KAIS) publication as Best-ranked paper. New features in KAIS verison are listed as following:

• Shared dictionary design
• Auto hyper-parameter tuning
• Higher compression ratio