cbindgen
tokenizers
cbindgen | tokenizers | |
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19 | 8 | |
2,205 | 8,458 | |
1.5% | 2.0% | |
7.8 | 8.5 | |
13 days ago | 2 days ago | |
Rust | Rust | |
Mozilla Public License 2.0 | Apache License 2.0 |
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cbindgen
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Hello World in Go From Rust
Golang uses cgo to communicate with external C libraries and Rust uses FFI (Foreign function interfaces) to export C functions. Additionally, a library for automatically generating bindings can be used to generate the header files (.h). In our case, we'll only be exporting two C functions, so using cbindgen is overkill but we'll use it regardless because why not? Firstly, we'll write the rust functions we want to export. We'll start by creating a new rust library:
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Ask HN: Automating multi-lang communication with a meta programming language
[1]: https://github.com/mozilla/cbindgen
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Nim v2.0 Released
As a 2-step approach, you could also probably use https://github.com/mozilla/cbindgen and then Nim's native C FFI.
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ffizz: Build a Beautiful C API in Rust
The tooling for the first kind -- calling Rust from another language -- is a bit less developed, and tends to rely on code generation that doesn't necessarily produce a natural C API. cbindgen, uniffi, cxx, and Diplomat all take this course.
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How can I use rust libraries in zig/C
There's also cbindgen for automating the generation of C headers once you've got your code in the right shape and you'll also want to read the Rustonomicon.
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C Strings and my slow descent to madness
You can backport Rust standard library to C using https://github.com/eqrion/cbindgen .
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Rust FFI and cbindgen: Integrating Embedded Rust Code in C
Later we'll see what cbindgen essentially does is receive a configuration and a Rust library and then spit out a C header (.h) file. One might think that what cbindgen is doing might not be that special and can be done by hand. In which some cases that might be true if the project is simple enough. Though additionally as the cbindgen documentation states:
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Nautilus just fucked me. (Gnome paper cuts)
Fuck it, I'll take the bait. Rust allows for amazing C interop by allowing for exporting of C types as a dynamic library, like C. Unlike C, this still allows for Rust's advanced checking at compile time. librsvg is one such library that is being used in the GTK ecosystem that is also almost completely Rust. You can use tools like cbindgen to generate C bindings.
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Hey Rustaceans! Got a question? Ask here! (47/2022)!
Or alternatively cbindgen to create the header file from the Rust source.
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7 ways to pass a string between 🦀 Rust and C
The easiest way to obtain the headers for the rust code is to use the cbingen library.
tokenizers
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HF Transfer: Speed up file transfers
Hugging Face seems to like Rust. They also wrote Tokenizers in Rust.
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LLM custom dictionary
Your intuition is right. There are two ways (in increasing order of result performance) : 1. You can simply extend vocab file of the tokenizer and test the predictions 2. You can extend the vocab file and re-train your model on custom data which has these new tokens. Check the following issue on GitHub : https://github.com/huggingface/tokenizers/issues/247
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[D] SentencePiece, WordPiece, BPE... Which tokenizer is the best one?
SentencePiece -> implementation of some algorithms (there are several others, https://github.com/microsoft/BlingFire https://github.com/glample/fastBPE https://github.com/huggingface/tokenizers )
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Portability of Rust in 2021
In sum I would like the idea to go with Rust as I more or less got to rewrite the whole thing anyway, but I am a bit skeptical if I will be able to interface with everything that might come up at some point. Or probably end up in a wrapper hell if I got to use more C++ libraries. On the other hand there are definitely a few Rust projects out there that might come in handy (for example https://github.com/huggingface/tokenizers). And the build process is pretty awful right now (CMake it is but with lots of hacks).
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[D] What's going to be the dominant language for machine learning in 5 years?
A full machine learning pipeline usually comprises far more than just the model, and this is the area where Rust may shine (the recent work by HuggingFace and their https://github.com/huggingface/tokenizers library is a good example)
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substitute for tokenizer in torchtext
As for other tokenizers, you can take a look at - Huggingface tokenizers library: https://github.com/huggingface/tokenizers - NLTK tokenize: https://www.nltk.org/api/nltk.tokenize.html - Polygot: https://pypi.org/project/polyglot/
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PyO3: Rust Bindings for the Python Interpreter
Huggingface Tokenizers (https://github.com/huggingface/tokenizers), which are now used by default in their Transformers Python library, use pyO3 and became popular due to the pitch that it encoded text an order of magnitude faster with zero config changes.
It lives up to that claim. (I had issues with return object typing when going between Python/Rust at first but those are more consistent now)
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Rusticles #19 - Wed Nov 11 2020
huggingface/tokenizers (Rust): 💥Fast State-of-the-Art Tokenizers optimized for Research and Production
What are some alternatives?
rust-bindgen - THIS CRATE IS DEPRECATED, please use https://github.com/servo/rust-bindgen.
onnx-tensorflow - Tensorflow Backend for ONNX
cxx - Safe interop between Rust and C++
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
rusty-cheddar - A Rust crate for automatically generating C header files from Rust source file.
setuptools-rust - Setuptools plugin for Rust support
flutter_rust_bridge - Flutter/Dart <-> Rust binding generator, feature-rich, but seamless and simple.
BlingFire - A lightning fast Finite State machine and REgular expression manipulation library.
tch-rs - Rust bindings for the C++ api of PyTorch.
rayon - Rayon: A data parallelism library for Rust
Module Linker - browse modules by clicking directly on "import" statements on GitHub