The predictions and weights will be same all the time if you don’t backpropogate local_model and the loss function will always return a constant value because since the gradients of local_model are not being updated,it will give same prediction every time and labels are also constant so if you are able to interpret this then you will notice that loss will come out constant all the time so while you backpropogate through global_model, the gradients will be same.