Will post again after making more progress.
I don't want to put you off, but there's no substance at all here, I'd have assumed Claude wrote it based on the fact you've vendored in rules, but the code is so questionable, even an LLM from 2022 would do better. E.g. 'flattenData' from utils could just be [1] rather than a BFS, though I don't really get why your public API allows TensorData to be a single integer in the first place, 50% of your logic is to work around that.
But rant over. My point is, maybe post this when you've built even 5% of PyTorch, or learnt something of value, or have something tangible to impart upon us, rather than a library of ill-thought-out array utils.
1: flattenData = (x: TensorData) => Array.isArray(x) ? x.flat(Infinity) : [x]
2. It’s clear you didn’t read the rules folder because it’s a rule to tell cursor to teach me
3. You say you don’t understand why TensorData can be a single integer. Scalars are tensors too. I’m trying to support PyTorch’s spec and ops as much as possible which is why I’m supporting it. The obvious use cases are for reduction ops and scalar unary ops.
4. Fine I’ll post after I’ve made more progress.
13point5•1mo ago
primitivesuave•1mo ago
1. https://github.com/keshavsaharia/numbers/blob/dev/lib/nn/neu...
2. https://github.com/keshavsaharia/numbers/blob/dev/lib/cnn/cn... (still working on the visualization)
Hope you find these useful in your own learning journey!
13point5•1mo ago