in [ ]from keras import applications vgg_model applications vgg (include_top=falseweights='imagenet'now that the pre-trained model is availablewe will utilize it to extract features from our training dataset remember vgg- is trained upon imagenet while we would be using cifar to build classifier since imagenet contains over million images spanning across , categoriesit is safe to assume that cifar ' categories would subset here before moving on to feature extraction using the vgg- modelit would be good idea to check out the model' architecture in [ ]vgg_model summary(layer (typeoutput shape param ================================================================input_ (inputlayer(nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone block _pool (maxpooling (nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone block _pool (maxpooling (nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone block _pool (maxpooling (nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone block _pool (maxpooling (nonenonenone block _conv (conv (nonenonenone block _conv (conv (nonenonenone