Hello!
Here is my package version
Python 3.6.5
Torch 1.3.0
Here is a simple schema of my code focusing on seed settings
random.seed(args.seed)
np.random.seed(args.seed)
torch.manual_seed(args.seed)
torch.cuda.manual_seed_all(args.seed)

Loop on epochs
train
Test
The problem is that with seed 1 the result are Ok and consistent if I repeat it many times
for seed=2 the results are consistent from one run to another but are absolutly NOT OK at all (it is not just a matter of percent difference)

have you experienced this kind of behavior
does the seed should respect some convention/range/values ? when I was starting research 30yrs ago with FORTRAN code the random seeds usuable were special, and if one did respect the rules than the results were completky crazy. Is it the case here?

Best.