Hi,
I want to use a pretrained DenseNet-121 model which I load directly from Torchvision. However, I want to be able to split the model from one of the transition layers, say, transition2, and use the values up to that point.
There has been some discussion going on: How to load part of pre trained model? 9, but it got me confused.
How can I split the parameters until a certain point. to clarify myself further, I want to have the values of the keys in such a way:
for key,value in densenet.state_dict().items():
   print(key)
   if key == "features.transition2.conv.weight":
		break