Why does Pytorch’s implementation of Gated Recurrent Units use two sets of biases for the update, reset and new gates? It seems redundant since these biases are summed before activation. Were there any performance gains for this approach, as opposed to just one set of biases?
https://pytorch.org/docs/stable/generated/torch.nn.GRU.html