advanced deep-learning best practices output concatenate conv strides= conv strides= conv strides= conv conv conv avgpool strides= conv input figure an incept ion modulea subgraph of layers wit several parallel convolut ional branches layer layer residual connection layer layer figure residual connectionreinjection of prior informat ion downst ream via feature-map addit ion these three important use cases--multi-input modelsmulti-output modelsand graph-like models--aren' possible when using only the sequential model class in keras but there' another far more general and flexible way to use kerasthe functional api this section explains in detail what it iswhat it can doand how to use it introduction to the functional api in the functional apiyou directly manipulate tensorsand you use layers as functions that take tensors and return tensors (hencethe name functional api )from keras import inputlayers input_tensor input(shape=( ,) tensor licensed to