I'm a little confused by the architecture here. Keras already abstracts TensorFlow and PyTorch - and CNTK. Don't at least TF and CNTK already handle the distributed training use cases natively? (I am not familiar with PyTorch). It's certainly one of CNTK's main selling points. What are the use cases for adding yet another layer to the stack? In what way is this simpler than tweaking to use the distributed features of the underlying packages natively? Which is what they are designed for.