Hello,
I want to not optimize (do back propagation) some part of weights in a neural network. For example, if I have a two fully connected layers (as my neural network). Let’s say nn.Linear(784, 84) and nn.Linear(84,10). So my weights would be w1 = [84, 784], w2 = [10, 84]. I want to only optimize 1 and 2 row of w2 so other rows in w2 should not be optimized. I have checked Pytorch modules and functions, but still don’t know how to do this in Pytorch. I really appreciate your help. Thanks in advance