I’m using this 2 implementation of SegNet in Pytorch, and I want to finetune it. I’ve read online and I’ve found this 4 method (basically freezing all layers except the last one in your net). My problem is that SegNet has more than 100 layers and I’m looking for a simpler way to do it, rather than writing 100 lines of code.
Do you think this could work? Or is this utter nonsense?
import torch.optim as optim

model = SegNet()
for name, param in model.named_modules():
    if name != 'conv11d':    # the last layer should remain active
        param.requires_grad = False

optimizer = optim.SGD(model.parameters(), lr=0.01, momentum=0.5)


def train():
    ...

How can I check if this is working as intended?