I was struggling with the fairness of your comment because the libraries are not used as a replacement to NumPy, but to ease dealing with the data. This made me check and it turns out that:
"Yes, the comment you mentioned is fair and reflects a common perspective in the programming and data science communities regarding the usage of "pure" implementations. When someone refers to a "pure X implementation," the typical expectation is that the implementation will rely solely on the functionalities of library X, without introducing dependencies from other libraries or frameworks."
I don’t see a PyTorch import, and the transformers import is just for the tokenizer which I don’t really consider a nontrivial part of mamba
So it’s just numpy and einops, which is pretty cool. I guess you could probably rewrite all the einops stuff in pure numpy if you want to trade readable code for eliminating the einops dependency
Edit: found the torch import, but it’s just for a single torch.load to deserialize some data
"Yes, the comment you mentioned is fair and reflects a common perspective in the programming and data science communities regarding the usage of "pure" implementations. When someone refers to a "pure X implementation," the typical expectation is that the implementation will rely solely on the functionalities of library X, without introducing dependencies from other libraries or frameworks."
TIL.