extract_vgg19_pretrained_layers.py

    def extract_vgg19_pretrained_layers(self):
        # get pretrained model
        features = torchvision.models.vgg19_bn(pretrained=True, progress=True).features

        # change to reflection
        for i in features:
            if isinstance(i, nn.Conv2d):
                i.padding_mode = 'reflect'

        # get blocks of layers we want
        feats1 = features[0:3]
        feats2 = features[3:10]
        feats3 = features[10:17]
        feats4 = features[17:30]

        return feats1, feats2, feats3, feats4