dfdx

Hard disagree that julai perfected arrays. I love Julia but even compared with old with old “array programming lenguaje” like APL not even mentioning newer ones like BQN. Julia array still seem a less expressive than one might hope. There’s also an under explored area of compile time Shape checking, that might open up a new era in array. There has been interesting advancements in the Rust space like https://github.com/JErnestoMtz/rapl or https://github.com/chelsea0x3b/dfdx

You might be interested in `dfdx`, shape checked deep learning in rust: https://github.com/coreylowman/dfdx.

I keep checking the progress on dfdx for this reason. It does what I (and, I assume from context, you) want: Provides static checking of tensor shapes. Which is fantastic. Not quite as much inference as I'd like but I love getting compile-time errors that I forgot to transpose before a matmul. It depends on the generic_const_exprs feature which is still, to quote, "highly experimental": https://github.com/rust-lang/rust/issues/76560 Definitely not for production use, but it gives a flavor for where things can head in the medium term, and it's .. it's nice. You could imagine future type support allowing even more inference for some intermediate shapes, of course, but even what it has now is really nice. Like this cute little convnet example: https://github.com/coreylowman/dfdx/blob/main/examples/night...

Also dfdx [1], which is shaping up to become a great neural network library (though GPU support is still WIP, give it a couple months before production use). Of course the ecosystem isn't as diverse as python yet, but if you're willing to call a bit back and forth between rust and python it's great. 1: https://github.com/coreylowman/dfdx