Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Support for numpy >= 2.0 #358

Open
charleslparker opened this issue Sep 26, 2024 · 3 comments
Open

Support for numpy >= 2.0 #358

charleslparker opened this issue Sep 26, 2024 · 3 comments
Labels
enhancement New feature or request

Comments

@charleslparker
Copy link

I've done some casual testing and based on the results I'm assuming support for numpy 2.0 and above isn't present yet. Are there plans to support it in the near future?

@ryan-wolbeck ryan-wolbeck added the enhancement New feature or request label Oct 16, 2024
@ryan-wolbeck
Copy link
Collaborator

@charleslparker yes it will be something we support in the future. If you want to accelerate that ask I'd be happy to review a PR.

@charleslparker
Copy link
Author

Thanks, @ryan-wolbeck . I'm a bit swamped right now but if I have a free moment I'll take a look. Thanks for excellent library!

@jerome-f
Copy link

+1 on this Score -> grad np.linalg.solve fails because 2.0

Changed in version 2.0: The b array is only treated as a shape (M,) column vector if it is exactly 1-dimensional. In all other instances it is treated as a stack of (M, K) matrices. Previously b would be treated as a stack of (M,) vectors if b.ndim was equal to a.ndim - 1.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

3 participants