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Additional toolings for rust
rust_hero is a rust assistant that utilizes NLP to enhance the quality of rust code. It supports unsafe and lifetime (todo) prediction.
[]
= "0.5"
Classify unsafe Rust code
For each function in Rust, the unsafe keyword utilizes the unsafe superpowers. However, the unsafe keyword is not necessary if it can be taken out while the program is compiled successfully.
rust_hero infers the necessity of unsafe keywords without the need of recompiling. rust_hero trains a microsoft/codebert based model and take advantage of bert's strong reasoning capability to inference the necessity of unsafe.
Declaration
Implementation of the language query in this project is based on BrianHicks/tree-grepper.
Performance
It costs 2.06s and 2.90s on average for rust_hero inferencing one rust file on Intel I7-12700K CPU and NVIDIA 3080 12GB GPU, seperately.
rust_hero written in Rust achieves up to 6.58X and 13.04X performance speedup over rust_hero written in Python language for GPU and CPU, seperately.

Installation
Runtime dependencies for rust_hero
Download the tree-grepper vendor (cargo build also download the vendor automatically):
It uses libtorch-1.12.0 (See rust-bert) to inference rust_hero. Download the libtorch with CPU or CUDA from following links:
Unzip the file and set the environment path in .bashrc:
or in 'envConfig' of work directory:
Prepare rust data for rust_hero test (optional):
50 rust files for testing is elaboratly selected from open-source rust project including on rust-openssl, tokio, anyhow, hyper, rand, regex and rayon:
Example usage for rust_hero:
rust_hero also supports classifling all rust files of one directory: