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

Add proper handling of NaN values in dpnp.unique implementation with axis not None #1989

Merged
merged 6 commits into from
Aug 16, 2024

Conversation

antonwolfy
Copy link
Contributor

@antonwolfy antonwolfy commented Aug 16, 2024

The PR addresses the comment from gh-1972 and implements a proper handling of NaN values in all use cases.

Note, that the result may vary towards numpy in case of complex dtype, because for complex all possible NaNs are considered equivalent (i.e. complex(nan, 1), complex(2, nan) and complex(nan, nan) are the same).

  • Have you provided a meaningful PR description?
  • Have you added a test, reproducer or referred to issue with a reproducer?
  • Have you tested your changes locally for CPU and GPU devices?
  • Have you made sure that new changes do not introduce compiler warnings?
  • Have you checked performance impact of proposed changes?
  • If this PR is a work in progress, are you filing the PR as a draft?

@antonwolfy antonwolfy self-assigned this Aug 16, 2024
Copy link
Contributor

github-actions bot commented Aug 16, 2024

View rendered docs @ https://intelpython.github.io/dpnp/index.html

Copy link
Collaborator

@vtavana vtavana left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thank you, @antonwolfy!

@antonwolfy antonwolfy merged commit 7387990 into master Aug 16, 2024
29 of 39 checks passed
@antonwolfy antonwolfy deleted the dpnp-unique-with-axis-and-nans branch August 16, 2024 15:27
github-actions bot added a commit that referenced this pull request Aug 16, 2024
…h axis not None (#1989)

* Align handling of NaN values for axis not None with numpy

* Add missing parametrize for test_sycl_queue.py::test_unique

* Remove obsolete test

* Applied black formating

* Add a test with NaNs and axis not None

* For complex dtype the result may vary 7387990
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants