Unsupervised Learning of Shape Programs with Repeatable Implicit Parts Supplementary Materials Boyang Deng 1, Zhengyang Dong 1 Congyue Deng

We use an AdamW [5] optimizer with a learning rate of 0.0001 and a batch size of 32. We train the model for 75 epochs which is ~2 hours on an Nvidia Titan RTX. At the second stage, to train the implicit functions, we use the sample points preprocessed by [6] and [3].