[ntr--]

https://docs.rs/ndarray/0.15.6/ndarray/

Rust to the rescue, as it always is for safety. (I don't know if this directly translates for tensors, I used it for manipulating point clouds and iirc it allows for arbitrary dimension containers)

[survirtual]

I use this crate extensively and while I have gotten good results, it is not ergonomic and it is not equivalent to numpy ndarray. There are a lot of issues and work still to be done.

Just a word of caution for anyone interested in using it.

Things like windowing, slicing, views are all “supported” but have many limitations and are non intuitive. In particular, I needed an “axis shift” fn and I ended up spending hours scouring docs just to find a way to shift along an axis. When I mean by shift is a roll in numpy, ala: https://github.com/rust-ndarray/ndarray/issues/281

Answer: you can’t with this crate. I implemented a dynamic n-dim solution myself but it uses views of integer indices that get copied to a new array, which have indexes to another flattened array in order to avoid duplication of possibly massive amounts of n-dimensional data; using the crate alone, copying all the array data would be unavoidable.

Ultimately I’ve had to make my own axis shifting and windowing mechanisms. But the crate is still a useful lib and continuing effort.

While I don’t mind getting into the weeds, these kinds of side efforts can really impact context focus so it’s just something to be aware of.

[gpderetta]

How does this help with typechecking tensor types in python?