Hi ptrblock,
Thank you for your response. I don’t have an activation on the outputs because I just want the three numbers output (like regression problems) - have I programmed this wrong? My previous experience is Keras and with that I simply don’t give the final layer an activation function
I did output-output as a last ditch effort since I want my loss of the network to simply be ftn (torch.mean(ftn) won’t compile). It doesn’t work since no training is performed after the initial random distributions are tested for fitness. I think it’s something to do with the gradients being killed but I’m unfortunately not knowledgeable enough to figure out how to overcome this.
Pretty much all I want the network to do is learn from a single dummy input over and over again where the fitness is a custom fitness(output 1, output 2, output 3) and thus will update weights towards minimizing this function.
Thank you