Consider a CNN composed of three convolutional layers, each with $33$ kernels, a stride of $2,$ and "same" padding. The lowest layer outputs $100$ feature maps, the middle one outputs $200,$ and the top one outputs $400.$ The input images are RGB images of $200300$ pixels. What is the total number of parameters in the CNN$?$ If we are using $32-$bit floats, at least how much RAM will this network require when making a prediction for a single instance? What about when training on a mini$-$batch of $50$ images?