The following Python packages are required: numpy, torch, torchvision, tqdm.
An example job is
python main.py --optim fromage --lrG 0.01 --lrD 0.01 --epochs 121 --seed 0
See inside main.py for additional command line arguments.
Runnning sh batch.sh, we obtain the following results:
| train FID | test FID | |
|---|---|---|
| Fromage | 16.4 ± 0.5 | 16.3 ± 0.8 |
| Adam | 19.1 ± 0.9 | 19.4 ± 1.1 |
| SGD | 36.4 ± 2.5 | 36.7 ± 2.7 |
- The self attention block implementation is originally by https://github.com/zhaoyuzhi.
- The FID score implementation is by https://github.com/mseitzer/pytorch-fid.
- Thanks also go to Jiahui Yu, who implemented the original version of this codebase.
- This codebase is from the Fromage repository, developed by Jeremy Bernstein, Arash Vahdat, Yisong Yue & Ming-Yu Liu.
This repository (exluding the fid/ subdirectory) is made available under a CC BY-NC-SA 4.0 license.