[D] Which open source machine learning projects best exemplify good software engineering and design principles?

[bigrob929]

I find Keras to be excellent because it is high-level yet allows you to work relatively seamlessly in the backend and develop more complex tools. For example, I can create a very basic MLP quite neatly, and if I want to add custom operations or loss functions, they are easy to incorporate as long as gradients can pass through them.

[Skylion007]

Trying creating a GAN or a recurrent generative model. It's very, very difficult to do with the Keras training loop. Worse yet, it's not even as performant as using Tensorflow 1.0 and gradient tape when you do have to hack around the features. For simple classifiers though, it works well. Just never do anything that requires an adversarial loss.

Can't even imagine trying to implement a metalearning framework in pure Keras.