Support for einops

[gboduljak]

Hi :)

I am a big fan of einops and I believe that supporting it within the framework would be highly valuable, especially for quick prototyping and situations where performance isn't the primary focus. Are there any plans to implement a feature akin to torch.einsum within the framework? If there's a plan for something like mlx.einsum and contributions are welcome, I'd be eager to contribute.

[gboduljak]

It seems that Apple MLX support was already proposed within einops.

[sck-at-ucy]

I second that. einops saved me quite a few times where the logic was becoming a bit intractable.

[awni]

We'll definitely keep this on the feature roadmap. I think if we had an einsum like NumPY integration with einops is doable. (Contributions welcome!)

[dc-dc-dc]

Will also need a tile op to support einops

[dc-dc-dc]

After #278 and #240 get merged, that should be all thats needed to create a backend for einops

[arogozhnikov]

Einops maintainer here.

Simplest way to get einops functions for framework is to implement array api.
einops.array_api works with all array-api compatible tensors (there is also support for scikit-learn and eindex).

It also simplifies prioritization of ops a lot for framework devs, as what's in the standard is a bare minimum.

[awni]

We can close this as the latest MLX works with einops.array_api back-end.