miniF2F
jaxtyping
miniF2F  jaxtyping  

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miniF2F

[D] Have their been any attempts to create a programming language specifically for machine learning?
That said, you *can* write down a desired type and have a system write down a ton of type annotations or generate a bunch of code to prove that the type you wrote down is satisfied by your program. There's been recent work on this in deep learning for theorem proving, such as this work which uses GPT for proving theorems in Lean, a dependently type programming language and theorem prover. A better approach though would be to combine this with an actual tree search algorithm to allow a more structured search over the space of proofs, instead of trying to generate full correct proofs in one shot. Hypertree Proof Search does this, using a variant of AlphaZero to search and finetune the neural net. Unfortunately it hasn't been opensourced though, and it's pretty compute intensive, so we can't use this for actual type inference yet. But yeah there's active interest in doing this kind of thing, both as a proving ground for using RL for reasoning tasks and from mathematicians for theoremproving.
 [D] First Author Interview: AI & formal math (Formal Mathematics Statement Curriculum Learning)
 [D] OpenAI tackles Math  Formal Mathematics Statement Curriculum Learning (Paper Explained Video)
 MiniF2F
jaxtyping

Writing Python like it's Rust
Try using [jaxtyping](https://github.com/google/jaxtyping).
It also supports numpy/pytorch/etc.

Writing Python like itâ€™s Rust
Since you mention ML usecases, you might like jaxtyping.

Scientific computing in JAX
jaxtyping: rich shape & dtype annotations for arrays and tensors (also supports PyTorch/TensorFlow/NumPy);

[D] Have their been any attempts to create a programming language specifically for machine learning?
Headsup that my newer jaxtyping project now exists.

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
What are some alternatives?
tensor_annotations  Annotating tensor shapes using Python types
torchtyping  Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.
einops  Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
MindsDB  The platform for customizing AI from enterprise data
diffrax  Numerical differential equation solvers in JAX. Autodifferentiable and GPUcapable. https://docs.kidger.site/diffrax/
FL  FL language specification and reference implementations
plum  Multiple dispatch in Python
dexlang  Research language for array processing in the Haskell/ML family
madtypes  Python Type that raise TypeError at runtime
hasktorch  Tensors and neural networks in Haskell
pytype  A static type analyzer for Python code