SDSHNet: Dynamic feature fusion with transformer and star operation for efficient detection in aluminum alloys microscopic inclusion

· · 来源:data资讯

icon-to-image#As someone who primarily works in Python, what first caught my attention about Rust is the PyO3 crate: a crate that allows accessing Rust code through Python with all the speed and memory benefits that entails while the Python end-user is none-the-wiser. My first exposure to pyo3 was the fast tokenizers in Hugging Face tokenizers, but many popular Python libraries now also use this pattern for speed, including orjson, pydantic, and my favorite polars. If agentic LLMs could now write both performant Rust code and leverage the pyo3 bridge, that would be extremely useful for myself.

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To test this I built gitgres, about 2,000 lines of C implementing the libgit2 git_odb_backend and git_refdb_backend interfaces against Postgres through libpq, plus roughly 200 lines of PL/pgSQL for the storage functions. libgit2 handles pack negotiation, delta resolution, ref advertisement, and the transport protocol while the backend reads and writes against the two tables, and a git remote helper (git-remote-gitgres) lets you add a Postgres-backed remote to any repo and push or clone with a normal git client that has no idea it’s talking to a database. There’s a Dockerfile in the repo if you want to try it out without building libgit2 and libpq from source.。业内人士推荐搜狗输入法下载作为进阶阅读

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