Yeah, I can load them back to the  model. I copied the contents in the original model, and change the contents in the forward function by reducing one input, and removing the corresponding line in the forward function which uses the same layer as other inputs. During the training, this input is used to pass through a part of the network and its output is constrained to provide some regularization to the network. In the test stage, this process is not used anymore, so I want to remove it by changing the forward function.