hebigo
jax
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hebigo | jax | |
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21 | 82 | |
21 | 27,509 | |
- | 3.8% | |
1.9 | 10.0 | |
12 months ago | 1 day ago | |
Python | Python | |
Mozilla Public License 2.0 | Apache License 2.0 |
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hebigo
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What is the point of the if __name__ == "__main__":, i.e. why use a file as both script and module?
The Lissp transpiler incrementally compiles and executes each top-level form to Python. It needs to do this in case there's a macro definition that might affect the compilation of a subsequent form. If it's only executing definitions, this is harmless, but if you want to precompile the main module, it needs the guard, or the side effects will happen too.
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What's the most hilarious use of operator overloading you've seen?
If you want Python to be as customizable as Lissp, check out Hissp (and Hebigo).
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Want cleaner code? Use the rule of six
Python's lambdas can have as many lines as you want. Just wrap parens around it. Hissp uses this form as a compilation target. Its REPL shows the Python compilation. Play around with it til you get it: https://github.com/gilch/hissp
- What would be your “perfect” programming language?
- Kamby – A programming language based on Lisp that doesn't seems like Lisp
- Wisp: Whitespace to Lisp
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Is ECMAScript really a dialect of Lisp?
The original Lisp's S-expression syntax was just supposed to be an intermediate language used by the compiler when processing the real language based on M-expressions, which kind of never took off. Numerous alternatives to S-expressions have been proposed, and some retain homoiconicity, another feature diagnostic of a Lisp (and one that ECMAScript lacks). For example, see Hebigo's readme, which shows a direct correspondence between its Python-like syntax and that of Hissp's default reader (Lissp), which uses the S-expressions. Julia can also be written in S-expressions, but this usually only used in macro definitions.
- Why Hy?
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Land of Lisp
I think LoL is too CL-specific. If you know both languages first, you can pretty much translate, but since they'd be trying to learn Lisp in the first place, this is a bad idea.
On the other hand, [Hissp][1] has a pretty good tutorial for anyone coming from a Python background.
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Interesting or distinctive lisps?
Hebigo: a whitespaceLisp isomorphic to Hissp that looks like Python.
jax
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The Elements of Differentiable Programming
The dual numbers exist just as surely as the real numbers and have been used well over 100 years
https://en.m.wikipedia.org/wiki/Dual_number
Pytorch has had them for many years.
https://pytorch.org/docs/stable/generated/torch.autograd.for...
JAX implements them and uses them exactly as stated in this thread.
https://github.com/google/jax/discussions/10157#discussionco...
As you so eloquently stated, "you shouldn't be proclaiming things you don't actually know on a public forum," and doubly so when your claimed "corrections" are so demonstrably and totally incorrect.
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Julia GPU-based ODE solver 20x-100x faster than those in Jax and PyTorch
On your last point, as long as you jit the topmost level, it doesn't matter whether or not you have inner jitted functions. The end result should be the same.
Source: https://github.com/google/jax/discussions/5199#discussioncom...
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Apple releases MLX for Apple Silicon
The design of MLX is inspired by frameworks like NumPy, PyTorch, Jax, and ArrayFire.
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MatX: Efficient C++17 GPU numerical computing library with Python-like syntax
>
Are they even comparing apples to apples to claim that they see these improvements over NumPy?
> While the code complexity and length are roughly the same, the MatX version shows a 2100x over the Numpy version, and over 4x faster than the CuPy version on the same GPU.
NumPy doesn't use GPU by default unless you use something like Jax [1] to compile NumPy code to run on GPUs. I think more honest comparison will mainly compare MatX running on same CPU like NumPy as focus the GPU comparison against CuPy.
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JAX – NumPy on the CPU, GPU, and TPU, with great automatic differentiation
Actually that never changed. The README has always had an example of differentiating through native Python control flow:
https://github.com/google/jax/commit/948a8db0adf233f333f3e5f...
The constraints on control flow expressions come from jax.jit (because Python control flow can't be staged out) and jax.vmap (because we can't take multiple branches of Python control flow, which we might need to do for different batch elements). But autodiff of Python-native control flow works fine!
Development seems not to have dropped at all from the contributions page: https://github.com/google/jax/graphs/contributors
Don’t know about usage and uptake though.
You're right! Maybe we should revise that... I made https://github.com/google/jax/pull/17851, comments welcome!
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Julia and Mojo (Modular) Mandelbrot Benchmark
For a similar "benchmark" (also Mandelbrot) but took place in Jax repo discussion: https://github.com/google/jax/discussions/11078#discussionco...
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Functional Programming 1
2. https://github.com/fantasyland/fantasy-land (A bit heavy on jargon)
Note there is a python version of Ramda available on pypi and there’s a lot of FP tidbits inside JAX:
3. https://pypi.org/project/ramda/ (Worth making your own version if you want to learn, though)
4. For nested data, JAX tree_util is epic: https://jax.readthedocs.io/en/latest/jax.tree_util.html and also their curry implementation is funny: https://github.com/google/jax/blob/4ac2bdc2b1d71ec0010412a32...
Anyway don’t put FP on a pedestal, main thing is to focus on the core principles of avoiding external mutation and making helper functions. Doesn’t always work because some languages like Rust don’t have legit support for currying (afaik in 2023 August), but in those cases you can hack it with builder methods to an extent.
Finally, if you want to understand the middle of the midwit meme, check out this wiki article and connect the free monoid to the Kleene star (0 or more copies of your pattern) and Kleene plus (1 or more copies of your pattern). Those are also in regex so it can help you remember the regex symbols. https://en.wikipedia.org/wiki/Free_monoid?wprov=sfti1
The simplest example might be {0}^* in which case
0: “” // because we use *
- Codon: Python Compiler
What are some alternatives?
Numba - NumPy aware dynamic Python compiler using LLVM
functorch - functorch is JAX-like composable function transforms for PyTorch.
julia - The Julia Programming Language
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Cython - The most widely used Python to C compiler
jax-windows-builder - A community supported Windows build for jax.
mesh-transformer-jax - Model parallel transformers in JAX and Haiku
dex-lang - Research language for array processing in the Haskell/ML family
tensorflow - An Open Source Machine Learning Framework for Everyone
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️
brax - Massively parallel rigidbody physics simulation on accelerator hardware.
stan - Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.