By setting the learning rate of the optimizer to zero for the entire model.

By calling requires_grad_(False) on the feature extractor module or its parameters.

By moving the feature extraction layers to a different device than the classifier.

By re-initializing the weights of the feature extractor using nn.init.kaiming_uniform_.

By calling network.eval() before passing data through the feature extractor.