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Add rbf_kernel Function

Open tanannie22 opened this issue 10 months ago • 3 comments

Description

Issue: #2313

Changes Made:

  • Updated sklearnex/metrics/pairwise.py to utilize oneDAL for rbf_kernel.
  • Added tests in sklearnex/metrics/tests/test_metrics.py to validate correctness.
  • Added a benchmark notebook (examples/notebooks/benchmark_rbf_kernel.ipynb) to compare performance between sklearn and sklearnex.

PR should start as a draft, then move to ready for review state after CI is passed and all applicable checkboxes are closed. This approach ensures that reviewers don't spend extra time asking for regular requirements.

You can remove a checkbox as not applicable only if it doesn't relate to this PR in any way. For example, PR with docs update doesn't require checkboxes for performance while PR with any change in actual code should have checkboxes and justify how this code change is expected to affect performance (or justification should be self-evident).

Checklist to comply with before moving PR from draft:

PR completeness and readability

  • [x] I have reviewed my changes thoroughly before submitting this pull request.
  • [x] I have commented my code, particularly in hard-to-understand areas.
  • [x] I have updated the documentation to reflect the changes or created a separate PR with update and provided its number in the description, if necessary.
  • [x] Git commit message contains an appropriate signed-off-by string (see CONTRIBUTING.md for details).
  • [x] I have added a respective label(s) to PR if I have a permission for that.
  • [x] I have resolved any merge conflicts that might occur with the base branch.

Testing

  • [x] I have run it locally and tested the changes extensively.
  • [x] All CI jobs are green or I have provided justification why they aren't.
  • [x] I have extended testing suite if new functionality was introduced in this PR.

Performance

  • [x] I have measured performance for affected algorithms using scikit-learn_bench and provided at least summary table with measured data, if performance change is expected.
  • [x] I have provided justification why performance has changed or why changes are not expected.
  • [x] I have provided justification why quality metrics have changed or why changes are not expected.
  • [x] I have extended benchmarking suite and provided corresponding scikit-learn_bench PR if new measurable functionality was introduced in this PR.

tanannie22 avatar Mar 07 '25 16:03 tanannie22

Codecov Report

Attention: Patch coverage is 96.15385% with 1 line in your changes missing coverage. Please review.

Files with missing lines Patch % Lines
sklearnex/metrics/pairwise.py 96.15% 1 Missing :warning:
Flag Coverage Δ
azure 78.11% <92.30%> (+0.05%) :arrow_up:
github ?

Flags with carried forward coverage won't be shown. Click here to find out more.

Files with missing lines Coverage Δ
sklearnex/metrics/pairwise.py 96.55% <96.15%> (-3.45%) :arrow_down:

... and 43 files with indirect coverage changes

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codecov[bot] avatar Mar 07 '25 16:03 codecov[bot]

@tanannie22 would you like to continue working on it?

syakov-intel avatar Mar 26 '25 16:03 syakov-intel

@tanannie22 would you like to continue working on it?

Hi @syakov-intel, I'm still working on this, but I'm currently facing some challenges with enabling the function to compute on GPU. If you have any ideas on enabling the function to compute on GPU, it would really help me move faster. I’d appreciate any suggestions!

tanannie22 avatar Mar 27 '25 02:03 tanannie22