Hey thanks,
I went through that thread and got a pretty good idea of how to fine-tune stuff, however is there a way to manually remove a layer of the pre-trained network? From what I’ve learnt, even if I set the required_grad in the layers I don’t want in my graph, they still will have the pre-trained weights in them. So essentially I want to do something like this(in pseudo-code):
`
vgg = models.vgg16(pretrained=True)
remove the last two pooling layers
vgg.layer1 = nn.Conv2d(…dilation=2)
`
Any advice?