How to give different L2 regularization factors on different parameters?

Hi, I’m a beginner at Pytorch. I figured out how to give L2 regularization, using weight_decay arguments of optimizers.

optimizer = optim.SGD(net.parameters(), lr=0.1, momentum=0.9,weight_decay=1e-4)

However, I’m not sure how to give different L2 regularization factors to different parameters. Suppose the model has two convolution layers, and give 1e-4 & 2e-4 in each layer’s weight.
Then should I have to use optimizer1 (first layer params) & optimizer2 (second layer params)? or is there any way to exclude L2 regularization in specific parameters, and give different L2 factors?

See, there are no facilities to create parameter groups though :confused: