As I understand, you would like to change the intermediate output in some way (I call it changed_out) and you do not want the gradient to be accounted for that operation. Also, changed_out is going to the input for the other layers down the line.
I think, it will lead to disconnected networks (network1 --> intermediate operation --> network2). Unless network1 gets gradient with respect to its output, it is not going to be trained. I am not sure about the usecase why such operation is needed. Maybe if you could explain a bit more on the usecase, you would get valuable answers.