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