totally-safe-transmute VS rust

For example, there is this (pure safe Rust) code: https://github.com/ben0x539/totally-safe-transmute/blob/main... which accesses external resources (/proc/self/mem) in order to violate the safety guarantees.

The first is the totally_safe_transmute crate. I mean, who wouldn't love library code that has .expect("welp") and .expect("oof") as its error handling? But that's not even the really scary part. Issue #2 ("i hate this") remains open to this day, but for obvious reasons there's no chance of resolution. This post has some context and a line-by-line explanation of how it works.

You mean like this?

You can also do that in rust on linux: https://github.com/ben0x539/totally-safe-transmute/blob/master/src/lib.rs

I want to correct this statement: Rust can be safer, but not if a library you use contains unsound code. Unsoundness is most often caused by unsafe code, but not always (totally_safe_transmute, anyone?). There is a misconception that unsafe code blocks are always unsound and should be avoided at all costs, but they're completely fine if the safety contracts are upheld. In fact, unsafe blocks isolate the potential issues to make it easier to identify where undefined behavior may be occurring. unsafe code blocks are a feature of the language, and their usage should not be viewed as opting out of any safety the language provides, imo.

Just reimplement totally_safe_transmute in Zig. No need for unsafe.

Why transmute() when you can totally_safe_transmute()?

Well, there is always the totally-safe-transmute.

They should use https://github.com/ben0x539/totally-safe-transmute

You can use Tensorflow for Rust to simplify that task and avoid pain with regex. Just have the right mindset.

What is the benefit of this compared to using bindings/a wrapper to Tensorflow, or other ML libraries written in C/C++, such as this community hosted project on tensorflow's github. If it's just for fun that is a valid enough reason imo, just curious since you describe it as a better Tensorflow because of the typing vs using the python wrapper, when there already exist ways to interact with tensorflow with both Rust and other statically typed languages, also including C++ (officially supported), C#, Haskell and Scala, as well as probably having bindings not mentioned on the documentation for more niche languages.

(3) You could use TensorFlow as your executor: https://github.com/tensorflow/rust

TensorFlow has language support for TypeScript well as Rust.

Thank you for the restponse! With tensorflow I am probably better of with something like; [tensorflow rust bindings](https://github.com/tensorflow/rust/tree/master/src). But I believe some useful extensions are still written in python for example; [TFDV](https://github.com/tensorflow/data-validation).. and how about scikit-learn or even something that is simpler like fb-prophet that is entirely written in python?

Tensorflow bindings exist, technically, but they're in a pretty rough state AFAIK.

tensorflow/rust (Rust): Rust language bindings for TensorFlow