rustc_codegen_cranelift
tch-rs
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rustc_codegen_cranelift | tch-rs | |
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44 | 37 | |
1,404 | 3,748 | |
5.6% | - | |
9.7 | 7.7 | |
6 days ago | 24 days ago | |
Rust | Rust | |
Apache License 2.0 | Apache License 2.0 |
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rustc_codegen_cranelift
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Cranelift code generation comes to Rust
Windows is supported. See https://github.com/rust-lang/rustc_codegen_cranelift/issues/....
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A Guide to Undefined Behavior in C and C++
> When this happens, it seems like it'll be possible to get the LLVM bits out of the bootstrap process and lead to a fully self-hosted Rust.
What do you mean by "when this happens"? GP's point is that this has already happened: the Cranelift backend is feature-complete from the perspective of the language [0], except for inline assembly and unwinding on panic. It was merged into the upstream compiler in 2020 [1], and a compiler built with only the Cranelift backend is perfectly capable of building another compiler. LLVM hasn't been a necessary component of the Rust compiler for quite some time.
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What are some stuff that Rust isn't good at?
Note that the Cranelift codegen will eventually become standard for debug builds to speed them up.
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Rust port of B3 from WebKit, LLVM-like backend
Maybe one day we'll have rustc b3 backend like what they did with Cranelift
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Any alternate Rust compilers?
Additionally, there is gcc codegen for rustc (https://github.com/rust-lang/rustc_codegen_gcc), which is not a compiler per se, but an alternative code generator, with more architectures supported and other nice things. It's also coming along, but there's still a lot of work to do there too. There's also Cranelift codegen (https://github.com/bjorn3/rustc_codegen_cranelift), which is designed to make debug builds faster, but this is not as exciting/useful as the other 2.
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Capsules, reactive state, and HSR: Perseus v0.4.0 goes stable!
For the instant reloading, that's in Sycamore, so you should speak to its devs, but as for the alternative compiler backend, it's not my project, but it uses Cranelift and works pretty well! See https://github.com/bjorn3/rustc_codegen_cranelift for details.
- Security Engineer looking for ways to see if any of my tasks could slowly be ported to Rust or should I just stick with Python.
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Improving Rust compile times to enable adoption of memory safety
Cranelift is not used for debug builds by default. I think that's probably a goal (although I'm not actually 100% sure about that just because I'm not dialed into what the compiler team is doing). Even the OP mentions this:
> We were able to benchmark bjorn3's cranelift codegen backend on full crates as well as on the build dependencies specifically (since they're also built for cargo check builds, and are always built without optimizations): there were no issues, and it performed impressively. It's well on its way to becoming a viable alternative to the LLVM backend for debug builds.
And the Cranelift codegen backend itself is also clear about it not being ready yet: https://github.com/bjorn3/rustc_codegen_cranelift
(To be clear, I am super excited about using Cranelift for debug builds. I just want to clarify that it isn't actually used by default yet.)
The more immediate goal of "distribute the cranelift backend as a rustup component" has been making good progress and seems like it might happen relatively soon https://github.com/bjorn3/rustc_codegen_cranelift/milestone/...
tch-rs
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Llama2.rs: One-file Rust implementation of Llama2
I wanted to do something like this but then I would miss on proper CUDA acceleration and lose performance compared to using torchlib.
I wrote a forgettable llama implementation for https://github.com/LaurentMazare/tch-rs (pytorch's torchlib rust binding).
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Playing Atari Games in OCaml
I first encountered OCaml's PyTorch bindings because apparently they generate a C wrapper around PyTorch's C++ API, and Rust's PyTorch bindings use OCaml's C wrapper. See: https://github.com/LaurentMazare/tch-rs
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llm: a Rust crate/CLI for CPU inference of LLMs, including LLaMA, GPT-NeoX, GPT-J and more
You could try looking at the min-GPT example of tch-rs. I'd also strongly suggest watching Karpathy's video to understand what's going on.
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A Rust client library for interacting with Microsoft Airsim https://github.com/Sollimann/airsim-client
Pytorch
- [D] HuggingFace in Julia or Rust ?
- This year I tried solving AoC using Rust, here are my impressions coming from Python!
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[Help Needed] Deployment of torchscript using rust
I have looked into this a bit and found some crates which help in loading torchscript models called tch-rs
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Stable Diffusion with Core ML on Apple Silicon
PyTorch has libtorch as its purely native library. There are also Rust bindings for libtorch:
https://github.com/LaurentMazare/tch-rs
I used this in the past to make a transformer-based syntax annotator. Fully in Rust, no Python required:
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I could use some basic help
The game is in Rust, and so I have been working at using the pytorch Rust bindings, which have an A2C example, so that's what I've been going with. Example here: https://github.com/LaurentMazare/tch-rs/blob/main/examples/reinforcement-learning/a2c.rs
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Announcing Burn: New Deep Learning framework with CPU & GPU support using the newly stabilized GAT feature
Burn is different: it is built around the Backend trait which encapsulates tensor primitives. Even the reverse mode automatic differentiation is just a backend that wraps another one using the decorator pattern. The goal is to make it very easy to create optimized backends and support different devices and use cases. For now, there are only 3 backends: NdArray (https://github.com/rust-ndarray/ndarray) for a pure rust solution, Tch (https://github.com/LaurentMazare/tch-rs) for an easy access to CUDA and cuDNN optimized operations and the ADBackendDecorator making any backend differentiable. I am now refactoring the internal backend API to make it as easy as possible to plug in new ones.
What are some alternatives?
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
candle - Minimalist ML framework for Rust
cbindgen - A project for generating C bindings from Rust code
wtpsplit - Code for Where's the Point? Self-Supervised Multilingual Punctuation-Agnostic Sentence Segmentation
veloren - An open world, open source voxel RPG inspired by Dwarf Fortress and Cube World. This repository is a mirror. Please submit all PRs and issues on our GitLab page.
wasmtime - A fast and secure runtime for WebAssembly
gccrs - GCC Front-End for Rust
rustlearn - Machine learning crate for Rust
burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. [Moved to: https://github.com/Tracel-AI/burn]
tokenizers - 💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
linfa - A Rust machine learning framework.
sccache - Sccache is a ccache-like tool. It is used as a compiler wrapper and avoids compilation when possible. Sccache has the capability to utilize caching in remote storage environments, including various cloud storage options, or alternatively, in local storage.