jaxtyping
dex-lang
jaxtyping | dex-lang | |
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7 | 25 | |
941 | 1,538 | |
3.9% | 0.3% | |
8.3 | 8.8 | |
13 days ago | about 15 hours ago | |
Python | Haskell | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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jaxtyping
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Writing Python like it's Rust
Try using [jaxtyping](https://github.com/google/jaxtyping).
It also supports numpy/pytorch/etc.
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Writing Python like it’s Rust
Since you mention ML use-cases, you might like jaxtyping.
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Scientific computing in JAX
jaxtyping: rich shape & dtype annotations for arrays and tensors (also supports PyTorch/TensorFlow/NumPy);
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[D] Have their been any attempts to create a programming language specifically for machine learning?
Heads-up that my newer jaxtyping project now exists.
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Returning to snake's nest after a long journey, any major advances in python for science ?
As other folks have commented, type hints are now a big deal. For static typing the best checker is pyright. For runtime checking there is typeguard and beartype. These can be integrated with array libraries through jaxtyping. (Which also works for PyTorch/numpy/etc., despite the name.)
- Type annotations and runtime checking for shape and dtype
dex-lang
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Thinking in an Array Language
A really nice approach to this I've seen recently is Google's research on [Dex](https://github.com/google-research/dex-lang).
- Function Composition in Programming Languages – Conor Hoekstra – CppNorth 2023 [video]
- Dex Lang: Research language for array processing in the Haskell/ML family
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[D] Have their been any attempts to create a programming language specifically for machine learning?
Dex
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[D] PyTorch 2.0 Announcement
Have you tried Dex? https://github.com/google-research/dex-lang It is in a relatively early stage, but it is exploring some interesting parts of the design space.
- Mangle, a programming language for deductive database programming
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Looking for languages that combine algebraic effects with parallel execution
I think [Dex](https://github.com/google-research/dex-lang) might be along the lines of what you're looking for, although its focus is on SIMD GPU-style parallelism rather than thread-level parallelism.
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“Why I still recommend Julia”
Dex proves indexing correctness without a full dependent type system, including loops.
See: https://github.com/google-research/dex-lang/pull/969
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Haskell for Artificial Intelligence?
In case you want to see one research direction that's combining practical machine learning and functional programming, one of the authors of JAX (and the main author of its predecessor, Autograd) is writing Dex (https://github.com/google-research/dex-lang), a functional language for array processing. The compiler itself is written in Haskell. JAX is one of the most popular libraries for doing a lot of machine learning these days, along with Tensorflow and PyTorch. You might also want to see the bug in the JAX repo about adding Haskell support, for some context: https://github.com/google/jax/issues/185
What are some alternatives?
torchtyping - Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
MindsDB - The platform for customizing AI from enterprise data
futhark - :boom::computer::boom: A data-parallel functional programming language
diffrax - Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
julia - The Julia Programming Language
plum - Multiple dispatch in Python
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
madtypes - Python Type that raise TypeError at runtime
hasktorch - Tensors and neural networks in Haskell
pytype - A static type analyzer for Python code
CIPs