neuronika
rfcs
neuronika | rfcs | |
---|---|---|
19 | 666 | |
1,033 | 5,700 | |
1.3% | 0.8% | |
0.0 | 9.8 | |
over 1 year ago | 7 days ago | |
Rust | Markdown | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
neuronika
- This year I tried solving AoC using Rust, here are my impressions coming from Python!
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Deep Learning in Rust: Burn 0.4.0 released and plans for 2023
Also perhaps comparing to Neuronika.
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Making a better Tensorflow thanks to strong typing
how does it compare with https://github.com/spearow/juice, https://github.com/neuronika/neuronika and https://github.com/spearow/juice?
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[D] To what extent can Rust be used for Machine Learning?
Check where and how this struct is used. https://github.com/neuronika/neuronika/blob/variable-rework/neuronika-variable/src/history.rs
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What do I need for an ML/DL based scripting language in Rust?
Also you can take a look at neuronika.
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ML in Rust
There is also https://github.com/neuronika/neuronika
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Enzyme: Towards state-of-the-art AutoDiff in Rust
I have a question: as the maintainer of [neuronika](https://github.com/neuronika/neuronika), a crate that offers dynamic neural network and auto-differentiation with dynamic graphs, I'm looking at a future possible feature for such framework consisting in the possibility of compiling models, getting thus rid of the "dynamic" part, which is not always needed. This would speed the inference and training times quite a bit.
- Any role that Rust could have in the Data world (Big Data, Data Science, Machine learning, etc.)?
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What sort of mature, open-source libraries do you feel Rust should have but currently lacks?
If you like autograd you will love neuronika
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bhtsne 0.5.0, now 5.6x faster on a 4 core machine, plus a summary of my Rust journey (so far)
After reading most of the book, I wanted to get my hands dirty. My initial idea was to build a small machine learning framework but I deemed it to be too difficult if not impossible for me at the time. (Now, neuronika would have something to say). When gathering the bibliography for my thesis, I recalled to have stumbled upon a particular algorithm, t-SNE, whom I liked very much. I found the idea behind it to be very clever and elegant (t-SNE it's still one of my favorite algorithms, together with backprop and SOM, I find manifold learning fascinating in general). "So be it", I said, and I began writing a mess of a code, that was basically a translation of the C++ implementation. Boy was it bad.
rfcs
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Ask HN: What April Fools jokes have you noticed this year?
RFC: Add large language models to Rust
https://github.com/rust-lang/rfcs/pull/3603
- Rust to add large language models to the standard library
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Why does Rust choose not to provide `for` comprehensions?
Man, SO and family has really gone downhill. That top answer is absolutely terrible. In fact, if you care, you can literally look at the RFC discussion here to see the actual debate: https://github.com/rust-lang/rfcs/pull/582
Basically, `for x in y` is kind of redundant, already sorta-kinda supported by itertools, and there's also a ton of macros that sorta-kinda do it already. It would just be language bloat at this point.
Literally has nothing to do with memory management.
- Coroutines in C
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Uv: Python Packaging in Rust
Congrats!
> Similarly, uv does not yet generate a platform-agnostic lockfile. This matches pip-tools, but differs from Poetry and PDM, making uv a better fit for projects built around the pip and pip-tools workflows.
Do you expect to make the higher level workflow independent of requirements.txt / support a platform-agnostic lockfile? Being attached to Rye makes me think "no".
Without being platform agnostic, to me this is dead-on-arrival and unable to meet the "Cargo for Python" aim.
> uv supports alternate resolution strategies. By default, uv follows the standard Python dependency resolution strategy of preferring the latest compatible version of each package. But by passing --resolution=lowest, library authors can test their packages against the lowest-compatible version of their dependencies. (This is similar to Go's Minimal version selection.)
> uv allows for resolutions against arbitrary target Python versions. While pip and pip-tools always resolve against the currently-installed Python version (generating, e.g., a Python 3.12-compatible resolution when running under Python 3.12), uv accepts a --python-version parameter, enabling you to generate, e.g., Python 3.7-compatible resolutions even when running under newer versions.
This is great to see though!
I can understand it being a flag on these lower level, directly invoked dependency resolution operations.
While you aren't onto the higher level operations yet, I think it'd be useful to see if there is any cross-ecosystem learning we can do for my MSRV RFC: https://github.com/rust-lang/rfcs/pull/3537
How are you handling pre-releases in you resolution? Unsure how much of that is specified in PEPs. Its something that Cargo is weak in today but we're slowly improving.
- RFC: Rust Has Provenance
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The bane of my existence: Supporting both async and sync code in Rust
In the early days of Rust there was a debate about whether to support "green threads" and in doing that require runtime support. It was actually implemented and included for a time but it creates problems when trying to do library or embedded code. At the time Go for example chose to go that route, and it was both nice (goroutines are nice to write and well supported) and expensive (effectively requires GC etc). I don't remember the details but there is a Rust RFC from when they removed green threads:
https://github.com/rust-lang/rfcs/blob/0806be4f282144cfcd55b...
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Why stdout is faster than stderr?
I did some more digging. By RFC 899, I believe Alex Crichton meant PR 899 in this repo:
https://github.com/rust-lang/rfcs/pull/899
Still, no real discussion of why unbuffered stderr.
- Go: What We Got Right, What We Got Wrong
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Ask HN: What's the fastest programming language with a large standard library?
Rust has had a stable SIMD vector API[1] for a long time. But, it's architecture specific. The portable API[2] isn't stable yet, but you probably can't use the portable API for some of the more exotic uses of SIMD anyway. Indeed, that's true in .NET's case too[3].
Rust does all this SIMD too. It just isn't in the standard library. But the regex crate does it. Indeed, this is where .NET got its SIMD approach for multiple substring search from in the first place[4]. ;-)
You're right that Rust's standard library is conservatively vectorized though[5]. The main thing blocking this isn't the lack of SIMD availability. It's more about how the standard library is internally structured, and the fact that things like substring search are not actually defined in `std` directly, but rather, in `core`. There are plans to fix this[6].
[1]: https://doc.rust-lang.org/std/arch/index.html
[2]: https://doc.rust-lang.org/std/simd/index.html
[3]: https://github.com/dotnet/runtime/blob/72fae0073b35a404f03c3...
[4]: https://github.com/dotnet/runtime/pull/88394#issuecomment-16...
[5]: https://github.com/BurntSushi/memchr#why-is-the-standard-lib...
[6]: https://github.com/rust-lang/rfcs/pull/3469
What are some alternatives?
rust-ndarray - ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations
rust - Empowering everyone to build reliable and efficient software.
clblast-rs - clblast bindings for rust
bubblewrap - Low-level unprivileged sandboxing tool used by Flatpak and similar projects
autograph - Machine Learning Library for Rust
crates.io - The Rust package registry
are-we-learning-yet - How ready is Rust for Machine Learning?
polonius - Defines the Rust borrow checker.
justrunmydebugger - just run my debugger. see package here: https://build.opensuse.org/package/show/home:ila.embsys:justrunmydebugger/justrunmydebugger
Rust-for-Linux - Adding support for the Rust language to the Linux kernel.
tractjs - Run ONNX and TensorFlow inference in the browser.
rust-gc - Simple tracing (mark and sweep) garbage collector for Rust