convolutional layers each one having like a real ooh non-linearity but you could also say well I'm going to build like a skip connection from here to here you could also say that I'm going to down sample by you could have maybe a bigger stride and so on so the kernel size of the convolution you can vary until now people have done this by hand right in effect we all use like the same 10 to 20 different architectures so if it's an image problem we tend to go for like a res net or a wide ResNet like a vgg style architecture someone has come up