[w4nderlust]

Your configuration file looks really good! Why did you stop pursuing it? To your points:

* That may be true, but I think it also depends on the level of abstraction. Fon instance in Ludwig the encoder, although configurable, are pretty monolitic. It's a trade off with flexibility, in Caffe or in your configuration file you are super flexible in specifying each single operation, while in Ludwig that is abstracted from you, but the advantage is that, as long as you trust the encoder implementation, those encoders mimic papers / state of the art models and require much less configuration to be written in order to run (in many cases if you are happy with the default parameters you don't have to configure them at all). So if the field moves and a new text encoder comes in, one can easily add a new encoder to Ludwig too. It's a dangerous game to play catch up, but hopefully releasing it as open source and making it easy to extend may help spontaneous contributions from the community.

* debugging is an issue, that is true, I answered to another post about that, but again, it's a matter of tradeoffs. Debugging is kind of a nightmare in SQL too for instance, or is in TensorFlow (even if the tfdbg improved things a bit).

* extending requires coding, that is also true, but if you have an idea for a new encoder for instance, all you have to do is implement a function that takes a tensor of rank k ad input and output a tensor of rank z as output, and all the rest (preprocessing, training loop, distributed training, etc.) comes for free, which kind of a nice value proposition imho and let you focus on the model rather than all the rest.

Thanks for the interesting discussion!