Pretty much what it says in the title, but to elaborate on the two questions:

Why isn’t Chainer more used? It seems to have pioneered some nice ideas like model subclassing, has many interesting “sub-libraries”, like ChainerCV and ChainerRL, but I think it is barely used outside Japan (not exactly sure if they use it a lot either)

And then in the same vein, why is it not more discussed when talking about Deep Learning frameworks? We see a lot of comparison between Pytorch and Tensorflow, then maybe some MxNet and new players (Jax, Halide) and non-python frameworks (mostly Julia’s), but Chainer almost seems to be ignored in most of these discussions.

(Also feel welcome to comment on pretty much the same questions but regarding Cupy vs Numba or similar)