I’m really going through it, trying to get legacy Theano and TensorFlow 1.x models from 2016 running on modern GPUs due to compatibility headaches due to OS, NVIDIA CUDA, CuDNN, drivers, docker, python, and package/image hubs all contributing their own roadblocks to actually coding. Ideally we would abandon this code, but we kind of need it running if we want to thoroughly understand our new model's performance on unseen old data, and/or understand Kappa scores between models. Will the move towards freeing Keras from TF again potentially reintroduce version chaos, or will it future proof it from that? Do you see a potential for something like this to once again befall tomorrow's legacy code relying on TF 1.x and 2.x?