equinox
PixiJS
equinox | PixiJS | |
---|---|---|
31 | 116 | |
1,819 | 42,610 | |
- | 1.0% | |
9.2 | 9.9 | |
16 days ago | about 17 hours ago | |
Python | TypeScript | |
Apache License 2.0 | MIT License |
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.
equinox
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Ask HN: What side projects landed you a job?
I wrote a JAX-based neural network library (Equinox [1]) and numerical differential equation solving library (Diffrax [2]).
At the time I was just exploring some new research ideas in numerics -- and frankly, procrastinating from writing up my PhD thesis!
But then one of the teams at Google starting using them, so they offered me a job to keep developing them for their needs. Plus I'd get to work in biotech, which was a big interest of mine. This was a clear dream job offer, so I accepted.
Since then both have grown steadily in popularity (~2.6k GitHub stars) and now see pretty widespread use! I've since started writing several other JAX libraries and we now have a bit of an ecosystem going.
[1] https://github.com/patrick-kidger/equinox
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[P] Optimistix, nonlinear optimisation in JAX+Equinox!
The elevator pitch is Optimistix is really fast, especially to compile. It plays nicely with Optax for first-order gradient-based methods, and takes a lot of design inspiration from Equinox, representing the state of all the solvers as standard JAX PyTrees.
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JAX – NumPy on the CPU, GPU, and TPU, with great automatic differentiation
If you like PyTorch then you might like Equinox, by the way. (https://github.com/patrick-kidger/equinox ; 1.4k GitHub stars now!)
- Equinox: Elegant easy-to-use neural networks in Jax
- Show HN: Equinox (1.3k stars), a JAX library for neural networks and sciML
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Pytrees
You're thinking of `jax.closure_convert`. :)
(Although technically that works by tracing and extracting all constants from the jaxpr, rather than introspecting the function's closure cells -- it sounds like your trick is the latter.)
When you discuss dynamic allocation, I'm guessing you're mainly referring to not being able to backprop through `jax.lax.while_loop`. If so, you might find `equinox.internal.while_loop` interesting, which is an unbounded while loop that you can backprop through! The secret sauce is to use a treeverse-style checkpointing scheme.
https://github.com/patrick-kidger/equinox/blob/f95a8ba13fb35...
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Writing Python like it’s Rust
I'm a big fan of using ABCs to declare interfaces -- so much so that I have an improved abc.ABCMeta that also handles abstract instance variables and abstract class variables: https://github.com/patrick-kidger/equinox/blob/main/equinox/_better_abstract.py
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[D] JAX vs PyTorch in 2023
For the daily research, I use Equinox (https://github.com/patrick-kidger/equinox) as a DL librarry in JAX.
- [Machinelearning] [D] État actuel de JAX vs Pytorch?
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Training Deep Networks with Data Parallelism in Jax
It sounds like you're concerned about how downstream libraries tend to wrap JAX transformations to handle their own thing? (E.g. `haiku.grad`.)
If so, then allow me to make my usual advert here for Equinox:
https://github.com/patrick-kidger/equinox
This actually works with JAX's native transformations. (There's no `equinox.vmap` for example.)
On higher-order functions more generally, Equinox offers a way to control these quite carefully, by making ubiquitous use of callables that are also pytrees. E.g. a neural network is both a callable in that it has a forward pass, and a pytree in that it records its parameters in its tree structure.
PixiJS
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Release Radar • March 2024 Edition
If you're into video game dev, then PixiJS is something you need to know about. It's a HTML5 game engine that provides a lightweight 2D library across all devices. This latest update has a new package structure, custom builds, graphics API overhaul, and lots more. You can read about all these changes in the PixiJS Migration Guide. Also big congrats to PixiJS for being part of the open source community for ten years now! 😮.
- Ask HN: Tips to get started on my own server
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JavaScript Libraries That You Should Know
6. Pixi.js
- JSON Canvas – An open file format for infinite canvas data
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A Visual Interactive Guide to Bloom Filters
https://pixijs.com/ and https://gsap.com/. All of the source code for my posts can be found at https://github.com/samwho/visualisations :)
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My thought on different engines
For full web games (yeah, I come from the web, so I try to make my family proud), I will recommend PixiJS. It has great support for TypeScript and works very well with Vite. It's lighter than other game engines, so it's better for web games. But you will need to do a lot of things by yourself.
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Not only Unity...
PixiJS (MIT/TypeScript) https://github.com/pixijs/pixijs
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Rebuilding Isometric World
That approach works well for what I was trying to archive but I am planning on adding more functionality into the website. Hence in this article, let me rebuild the project using Pixi.js and it’s React binding, React Pixi.
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Ask HN: Possible to make a game engine in the browser?
https://openarena.live/
There's also a bunch of Javascript game engines: https://github.com/collections/javascript-game-engines
Of those, BabylonJS seems pretty powerful for 3D: https://www.babylonjs.com/games/
Or PixiJS for 2D: https://pixijs.com/
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Consider web technologies for game development
https://pixijs.com/ is more of a 2D rendering framework, but powerful and very fast
What are some alternatives?
flax - Flax is a neural network library for JAX that is designed for flexibility.
Konva - Konva.js is an HTML5 Canvas JavaScript framework that extends the 2d context by enabling canvas interactivity for desktop and mobile applications.
dm-haiku - JAX-based neural network library
Phaser - Phaser is a fun, free and fast 2D game framework for making HTML5 games for desktop and mobile web browsers, supporting Canvas and WebGL rendering. [Moved to: https://github.com/phaserjs/phaser]
torchtyping - Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.
react-canvas - High performance <canvas> rendering for React components
treex - A Pytree Module system for Deep Learning in JAX
A-Frame - :a: Web framework for building virtual reality experiences.
extending-jax - Extending JAX with custom C++ and CUDA code
Leaflet.PixiOverlay - Bring Pixi.js power to Leaflet maps
diffrax - Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
cocos2d-html5 - Cocos2d for Web Browsers. Built using JavaScript.