During Training, How to freeze intermediate layers of network architecture in transfer learning?
Just need to set requires_grad
of the parameters of those intermediate layers to False
. There’s an example here (in the context of Resnet 18):
http://pytorch.org/docs/notes/autograd.html#excluding-subgraphs
Thanks for the reply