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Quantized Class Incremental Learning

Code for our paper "Hadamard Domain Training with Integers for Class Incremental Quantized Learning" accepted for Third Conference on Lifelong Learning Agents.

Run Commands

No quant baseline CIL:

python3 main.py -model icarl -p benchmark -seed 42467 --dataset="cifar100" --init_cls=20 --incre=20  --model_type="resnet32" --quantMethod="noq"

HDQT with CIL CIFAR100:

python3 main.py -model icarl -p benchmark -seed 42467 --dataset="cifar100" --init_cls=20 --incre=20  --model_type="resnet32" --quantMethod="ours" --quantBits=4 --quantAccBits=8 --quantFWDWgt="int" --quantFWDAct="int" --quantBWDAct="stoch" --quantBWDWgt="int" --quantBWDGrad1="stoch" --quantBWDGrad2="stoch" --quantBlockSize=32

HDQT with CIL HAR-DSADS:

python3 main.py -model icarl -p benchmark -seed 42467 --dataset="dsads" --init_cls=2 --incre=2  --model_type="fcnet" --fc_hid_dim=405 --init_lr=0.01 --lr=0.01 --epochs=100 --init_epoch=100 --memory_size=200 --init_milestones=50 --milestones=50 --quantMethod="ours" --quantBits=4 --quantAccBits=8 --quantFWDWgt="int" --quantFWDAct="int" --quantBWDAct="stoch" --quantBWDWgt="int" --quantBWDGrad1="stoch" --quantBWDGrad2="stoch" --quantBlockSize=32

LuQ [1] with CIL CIFAR100

python3 main.py -model icarl -p benchmark -seed 42467 --dataset="cifar100" --init_cls=20 --incre=20  --model_type="resnet32" --quantMethod="luq_og" --quantBits=4 --quantAccBits=8

Supported CIL methods: icarl, bic, der, lwf, memo, ours
Supported data sets: cifar100, dsads, hapt, pamap

All packages necessary to run commands can be found in requirements.txt

Citation

@article{schiemer2023hadamard,
  title={Hadamard Domain Training with Integers for Class Incremental Quantized Learning},
  author={Schiemer, Martin and Schaefer, Clemens JS and Vap, Jayden Parker and Horeni, Mark James and Wang, Yu Emma and Ye, Juan and Joshi, Siddharth},
  journal={arXiv preprint arXiv:2310.03675},
  year={2023}
}

Sources

[1] LuQ https://openreview.net/forum?id=yTbNYYcopd

[2] FP134 https://openreview.net/forum?id=3HJOA-1hb0e

[2] https://github.com/zhoudw-zdw/CIL_Survey