Deep learning is a discipline where the correctness of code is hard to assess. Random initialization, huge datasets and limited interpretability of weights mean that finding the exact issue of why your model is not training, is trial-and-error most times. In classical software development, automated unit tests are the bread and butter for determining if your code does what it is supposed to do. It helps the developer to trust their code and be confident when introducing changes. A breaking change would be detected by the unit tests. ...