I found a workaround. Apparently torch.stack() on my list of Variables made backpropagation ridiculously long. By computing my loss by iterating over my list of Variables instead of converting it in a single tensor seem to have resolved the issue. However, I stil don’t understand why torch.stack() would cause such a slow down.