For example; My neural network model takes x as input,  and output two dimensional vector y = model(x) where y = (y1,y2) and I want to restrict the output 0< y1 < y2 < 1. where restricting to domain (0,1) is easy as I can just apply sigmoid() as activation function at last but how to nicely satisfy the sign constraint and the allow backprogation?
I’m not sure if I shuffle the y as  y = sorted(y) as last layer allows backprogration at all