Earlier this year wrote a custom U-Net inspired model for semantic image segmentation in PyTorch. This one I designed to be fully modular so that it's really simple to change the architecture from a config file. Writing the code eloquently took some time, I like the idea of generating blocks of layers to keep the model neat rather than layer by layer (e.g. block includes conv layer, bn, activation, etc.). Probably going to try and do a GAN soon