It's suggested to use pytorch==1.10.1 in order to reproduce the benchmark results.
Then, you need to run
pip install -r requirements.txt
At last, you need to install torch_sparse following https://github.com/rusty1s/pytorch_sparse.
Following datasets can be downloaded automatically:
TODO
The shell files give all the training scripts we use, e.g.
CUDA_VISIBLE_DEVICES=0 python erm.py data/wilds --lr 3e-2 -b 4096 4096 --epochs 200 \
--seed 0 --deterministic --log logs/erm/obg_lr_0_03_deterministic
| Methods | Val Avg Precision | Test Avg Precision | GPU Memory Usage(GB) |
|---|---|---|---|
| ERM | 29.0 | 28.0 | 17.8 |
We use tensorboard to record the training process and visualize the outputs of the models.
tensorboard --logdir=logs
