Hi,
The main motivation to make it easy to compare NN-based model with classical ML algorithms.
In particular, the more common code we can add here, the better.
Given that most of these algorithms have very different ways to go through the dataset and specific stopping criterions there was no plan to incorporate them as pytorch optimizers for which the main training loop is user-controlled.
But a similar api to sklearn that takes a data.Dataset (or data.Dataloader) as input could be interesting. In particular that would allow to share all the data loading and preprocessing. And only the training function would be different.
Also an implementation based on Tensor would allow GPU support for free!
Do let me know if you’re interested and want to discuss this further.