Hi Alex!
I think the fusion optimization of torch.jit only works on  inputs with fixed size that it is warmed up with (Actually I found feeding tensors with another size doesn’t work.). Is my understanding right?
If I want to apply the optimized function to tensors with different sizes(e.g. #channels of feature map are increasing as going deep with a CNN), is there a way to implement it elegantly?