dfdx VS cargo-geiger

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...

And for transformers, it's really early days for dfdx, but it's a library that aims to sit basically at the Pytorch level of abstraction, that the difference is it's not just coded in Rust, but it follows the Rust-y/functional-y philosophy of "if it compiles it runs".

Wow that is super interesting. I actually tried to use GATs at first to be generic over shapes, but I couldn't do it, I'm sure it would be possible in the future though. There is this library dfdx that does something similar to what you mentioned, but it feels a little clumsy to me.

Awesome, I added an issue here https://github.com/coreylowman/dfdx/issues/597. We can discuss more there! The first step will just be adding the device and implementing tensor creation methods for it.

The next release of dfdx includes a CUDA device and implements many ops. The same dev created a new crate, cudarc, for a wrapper around CUDA toolkit.

A question I have is: what are the philosophical/design differences with dfdx? As someone who's played around with dfdx and only skimmed the README of burn, it seems like dfdx leans into Rust's type system/type inference for compile time checking of as much as is possible to check at compile time. I wonder if you've gotten a chance to look at dfdx and would like to outline what you think the differences are. Thanks!

Instead of looking at the crates themselves, you might want to check your (or others') Rust application with https://github.com/rust-secure-code/cargo-geiger to get a sense of effective prevalence. I also dispute that the presence of unsafe somewhere in the dependency tree is an issue in itself, but that's a different discussion that many more had in other sub-threads.

There's still plenty. Run cargo geiger on any of your projects and see for yourself.

On point 2, the answer is cargo geiger, and judging how much memory safety you need for a given project.

You can use cargo-geiger or cargo-crev to check for whether people you trusted (e.g. u/jonhoo ) trust this crate.

The amount of unsafe code is also a factor. cargo geiger is a handy tool for measuring it.

We have cargo-geiger that does just that.

For that, I believe you need to use cargo-geiger[0] and audit the results.

[0] - https://github.com/rust-secure-code/cargo-geiger

cargo-geiger is a subcommand you can install which will check all the crates in your dependency graph for unsafe blocks and print out a report (which also shows if a crate has #![forbid(unsafe_code)] or not). You can then inspect those crates' sources to judge their use of unsafe for yourself. I don't think it has a "check" mode that simply errors if your dependency graph contains unsafe though, it's more about just collecting that information.

wrt to memory safety, keep in mind that many rust crates use "unsafe" internally. There are tools available that can find these such as cargo-geiger. So I would suggest to avoid unsafe deps as much as possible. Since they cannot be avoided entirely, it is a good idea to keep a list of unsafe deps.