Balanced Training for Sparse GANs [Paper]
Yite Wang*, Jing Wu*, Naira Hovakimyan, Ruoyu Sun
In NeurIPS'2023
The code is tested using Redhat system with python 3.9. NVIDIA V100 and NVIDIA RTX 2080TI are used to run all the experiments. To install required packages, please find the requirements.txt
file.
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CIFAR-10 and STL-10 datasets will download automatically.
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Modify folder location of IS computation
MODEL_DIR
undersparselearning/gan_utils/inception_score.py
. -
Download FID statistics from this repo of GNGAN.
Please see the scripts in scripts
folder to run our code. For more information, please refer to main.py
and sparselearning/core.py
.
For example, to run the baseline:
chmod +x scripts/baseline1.sh
scripts/baseline1.sh
Our code is mainly based on :
ITOP and GAN ticket.
Yite Wang (yitew2@illinois.edu)
Jing Wu (jingwu6@illinois.edu)