    def _cut_vgg(self):
        """
        Loads pre-trained VGG, declares as output the intermediate
        layers selected by self.layers_to_extract.
        """
        
        vgg = VGG19(weights='imagenet', include_top=False, input_shape=self.input_shape)
        vgg.trainable = False
        outputs = [vgg.layers[i].output for i in self.layers_to_extract]
        self.model = Model([vgg.input], outputs)
        self.model._name = 'feature_extractor'
        self.name = 'vgg19'  # used in weights naming
Loads pre-trained VGG, declares as output the intermediate
layers selected by self.layers_to_extract.
ISR/models/cut_vgg19.py