LLT

Pytorch implementation of "Learnable Lookup Table for Neural Network Quantization", CVPR 2022

[CVF] [Supp]

Overview

Image Classification (CIFAR-10)

Requirements

• PyTorch
• TorchVision
• numpy

Train

python train.py --arch resnet20 --epochs 200 --batch_size 128 --learning_rate 0.01 --weight_decay 1e-4 --w_bits 4 --a_bits 4

Test

python test.py --arch resnet20 --batch_size 128 --w_bits 4 --a_bits 4

Results

Image Super-Resolution

Train & Test

To be updated

Results

Point Cloud Classification

Train & Test

To be updated

Results

Citation

@InProceedings{Wang2022Learnable,
  author    = {Wang, Longguang and Dong, Xiaoyu and Wang, Yingqian and Liu, Li and An, Wei and Guo, Yulan},
  title     = {Learnable Lookup Table for Neural Network Quantization},
  booktitle = {CVPR},
  year      = {2022},
  pages     = {12423--12433},
}

Acknowledgements

Part of the code is borrowed from APot. We thank the authors for sharing the codes.