My ultimate aim is to minimise loss1 for some samples and loss2 for other samples.
I tried minimising a*loss1+b*loss2 for samples from dataloader 1 a=1,b=0 and samples from dataloader 2 a=0,b=1. I think this is an hacky solution and wanted know if some special provisions in pytorch exist.