Hi WILDS Team,
I am currently working with the WILDS repository. Currently, I work with the poverty dataset. I've run the script run_exp.py in the examples folder with the argument --n_groups_per_batch=3 or a different number. However, per batch, I get samples from more than 3 different groups. Do is use this argument wrongly? I understood the argument --n_groups_per_batch as the number of different environments from which samples exist in one batch.

The command line reads:
python examples/run_expt.py --dataset poverty --algorithm ERM --root_dir data --n_epochs=200 --seed=0 --log_every=200 --batch_size=64 --n_groups_per_batch=2 --progress_bar True

The output when i use the n_groups_variable defined in IRM.py:
n groups: 13
groups: tensor([ 3, 5, 7, 9, 10, 11, 13, 14, 16, 19, 20, 21, 22], device='cuda:0')

In addition, is the command --uniform_over_groups valid for Poverty? Since the samples are not uniformly distributed over the different environments used in the training split?

Thanks in advance for your help.

Niels