I’ve been asked to convert a fully-trained CNN to a simple FC network with fixed architecture (it’ll be used on a small chip if I remember correctly). They understand the classification performance will drop but it needs to be done anyway. I’ve set up the student network such that it just takes the flattened image as the input but I’m unsure what my targets are. I have the data the teacher network was trained on so I guess I can train the student using those inputs with the correspoding teacher output (rather than one-hot targets in the dataset). But my real question is can I just generate random input images and use whatever the teacher outputs as a target for the student to train on? Is that what is usually done to generate a lot of training data for the student network?