This repository provides the PyTorch implementation of our CVPR 2023 paper "Genie: Show Me the Data for Quantization".
git clone https://github.com/SamsungLabs/Genie
cd Genie
pip3 install -r requirements.txt# Zero-Shot Quantization (PTQ)
python3 main.py --model_name=resnet18 --bit_w=4 --bit_a=4 --samples=1024 --val_path=IMAGENET_PATH/val
# or Few-Shot Quantization (PTQ)
python3 main.py --model_name=resnet18 --bit_w=4 --bit_a=4 --samples=1024 --train_path=IMAGENET_PATH/train --val_path=IMAGENET_PATH/val Detailed descriptions of arguments are provided in main.py.
If you find this work useful for your research, please cite our paper:
@InProceedings{jeon2023genie,
author = {Jeon, Yongkweon and Lee, Chungman and Kim, Ho-young},
title = {Genie: Show Me the Data for Quantization},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2023},
}
This project is released under the Apache 2.0 License.