Pytorch model.load call ambiguity
Simple one:
what does this do?
model.load_state_dict({name : 
        weights_before[name] + (weights_after[name] - weights_before[name]) * outerstepsize 
        for name in weights_before})

Thank you very much!

load_state_dict loads learnable parameters into neural network from dictionary.
Each layer has it's respective name and parameters. In this case you go over two dictionaries (weights_before and weights_after), weights_after are always used, but additionally the difference between parameter values are added multiplied by outerstepsize.
You can check out more in PyTorch docs.
