I was reading Goodfellow. At the start of the text it was mentioned that there are two ways to represent depth of a deep neural network. One is using the depth of the computation graph and the other is using the depth of the chain of features/concepts that is learned by NN.
Don't every layer in NN represent a concept so the depth would be the number of the layers, but then each layer also does calculation on input from previous layer so the length of computation graph will be same as number of layers. So both representation of depth will be same as number of layers in NN.
Or is it that features can also be represented using more that one layers and not individual layers.
Maybe I have misunderstood the concept of NN.