You are right. I missed the second output due to an error message, sorry.
Thinking about it, it might make sense that this flag is not propagated using DataParallel.
E.g. what would the expected result be, if the models on GPU0,1,2 set this flag to False, while all others keep it as True?
I think the cleanest approach would be to manipulate this flag after the forward pass manually using:
_ = model(torch.randn(8, 100, device='cuda'))
model.module.percentile.calculate_running = False

which will make sure that each new copy of the model uses the new value.