Hi there,
I’ve not dig deep into the PyTorch codebase but I assume that in order to perform batch inference/training, weights are duplicated and loaded into the GPU to perform parallel inference depending on the batch size. Let’s say I’d like to access the weights corresponding to every element in a batch, i.e. my model is an adaptive one and I’d like to modify the duplicated weights independently w.r.t. to the current input. What’s the best way to do this?
Thanks!