Hi,



 dzimm:

if I understand you correctly, you want to train netD1 with loss1, netD3 with loss2 ,… and netG with loss_other ?


Actually no, don’t want to train netD* at all, all the losses are for training the netG, and all netD* are fixed.
The last point of your reply kind of hit the point, I want to propagate through netG without propagating through netD*.
Why I thought it might work is because of this post Freezing parameters



Freezing parameters


Should just be something like
critic_loss = ((reward+(gamma*critic_new.detach())) - critic_old)**2


.requires_grad = False looks promising, but I am not sure either, would be great if someone can clarify on that.
@apaszke any thoughts on this?
Regards
Nabarun