miniF2F
torchtyping
miniF2F  torchtyping  

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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
torchtyping

[D] Have their been any attempts to create a programming language specifically for machine learning?
Not really an answer to your question, but there are Python packages that try to solve the problem of tensor shapes that you mentioned, e.g. https://github.com/patrickkidger/torchtyping or https://github.com/deepmind/tensor_annotations

What's New in Python 3.11?
I disagree. I've had a serious attempt at array typing using variadic generics and I'm not impressed. Python's type system has numerous issues... and now they just apply to any "ArrayWithNDimensions" type as well as any "ArrayWith2Dimenensions" type.
Variadic protocols don't exist; many operations like stacking are inexpressible; the synatx is awful and verbose; etc. etc.
I've written more about this here as part of my TorchTyping project: [0]
[0] https://github.com/patrickkidger/torchtyping/issues/37#issu...

Can anyone point out the mistakes in my input layer or dimension?
also https://github.com/patrickkidger/torchtyping

[D] Anyone using named tensors or a tensor annotation lib productively?
FWIW I'm the author of torchtyping so happy to answer any questions about that. :) I think people are using it!

[D] Ideal deep learning library
The one thing I really *really* wish got more attention was named tensors and the tensor type system. Tensor misalignment errors are a constant source of silentlyfailing bugs. While 3rd party libraries have attempted to fill this gap, it really needs better native support. In particular it seems like bad form to me for programmers to have to remember the specific alignment and broadcasting rules, and then have to apply them to an often poorly documented order of tensor indices. I'd really like to see something like tsalib's warp operator made part of the main library and generalized to arbitrary function application, like a namedtensor version of fold. But preferably using notation closer to that of torchtyping.

[P] torchtyping  documentation + runtime type checking of tensor shapes (and dtypes, ...)
Yes it does work with numerical literals! It support using integers to specify an absolute size, strings to specify names for dimensions that should all be consistently sized (and optionally also checks named tensors), "..." to indicate batch dimensions, and so on. See the full list here.
What are some alternatives?
tensor_annotations  Annotating tensor shapes using Python types
jaxtyping  Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/
einops  Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
equinox  Elegant easytouse neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
FL  FL language specification and reference implementations
tsalib  Tensor Shape Annotation Library (numpy, tensorflow, pytorch, ...)
dexlang  Research language for array processing in the Haskell/ML family
mypy  Optional static typing for Python
functorch  functorch is JAXlike composable function transforms for PyTorch.
hasktorch  Tensors and neural networks in Haskell