Validate precomputed pairwise kernel shapes by fallintoplace · Pull Request #8441 · NVIDIA/cuml

fallintoplace · 2026-08-03T23:00:02Z

Summary

Validate that precomputed self-kernels are square.
Validate that precomputed cross-kernels have matching indexed-sample counts.
Add regression coverage for valid and invalid precomputed shapes.

The previous validation compared feature widths before recognizing metric="precomputed", allowing malformed kernel matrices through or rejecting valid cross-kernel shapes with misleading errors.

Testing

pre-commit run --files python/cuml/cuml/metrics/pairwise_kernels.py python/cuml/tests/test_kernel_ridge.py
python3 -m py_compile python/cuml/cuml/metrics/pairwise_kernels.py python/cuml/tests/test_kernel_ridge.py

copy-pr-bot · 2026-08-03T23:00:06Z

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coderabbitai · 2026-08-03T23:03:04Z

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python/cuml/tests/test_kernel_ridge.py

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python/cuml/tests/test_kernel_ridge.py

📝 Walkthrough

Summary by CodeRabbit

Bug Fixes
- Improved validation for precomputed pairwise kernels with clear error messages.
- Dimensional mismatches between kernel matrices now raise descriptive errors.
- Valid cross-kernel inputs are accepted and returned unchanged.
Documentation
- Added shape requirements documentation for precomputed kernels.
Tests
- Added coverage for valid and invalid precomputed kernel scenarios.

Walkthrough

pairwise_kernels now validates precomputed kernel dimensions against Y. Non-precomputed metrics retain feature-dimension validation. Kernel ridge tests cover valid and invalid shapes.

Changes

Precomputed kernel validation

Layer / File(s)	Summary
Precomputed shape validation `python/cuml/cuml/metrics/pairwise_kernels.py`	Documentation defines precomputed input shapes. Precomputed kernels validate indexed dimensions before returning `X`. Non-precomputed metrics retain feature-dimension validation.
Shape validation regression tests `python/cuml/tests/test_kernel_ridge.py`	Tests cover non-square inputs, valid cross-kernels, incompatible indexed dimensions, and mismatched linear-kernel feature dimensions.

Estimated code review effort: 2 (Simple) | ~10 minutes

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly describes the main change: validating precomputed pairwise kernel shapes.
Description check	✅ Passed	The description accurately explains the shape validation changes, validation order correction, regression tests, and testing performed.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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Inline comments:
In `@python/cuml/cuml/metrics/pairwise_kernels.py`:
- Around line 286-297: Update the pairwise_kernels docstring’s
metric="precomputed" section to document that omitted Y requires square X, while
supplied Y permits X shaped (n_queries, n_indexed) with X.shape[1] equal to
Y.shape[0]. State that validation uses only Y.shape[0], and remove the claim
that Y is ignored.

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Verify each finding against current code. Fix only still-valid issues, skip the
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Inline comments:
In `@python/cuml/cuml/metrics/pairwise_kernels.py`:
- Around line 209-220: Update the Y parameter documentation in the
pairwise-kernel API to state that the feature-array restriction applies only to
non-precomputed metrics; for metric="precomputed", document that Y is used only
for its first dimension to validate rectangular X inputs, without constraining
its values or second dimension.

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viclafargue

Thanks! Just one non-blocking request. Otherwise looks good to me.

viclafargue · 2026-08-04T09:45:31Z

+    if X.shape[1] != Y.shape[1]:
+        raise ValueError("X and Y have different dimensions.")


Could we add a regression test confirming that non-precomputed kernels still reject X and Y with different feature dimensions? This check was moved by the PR and isn’t currently covered.

csadorf · 2026-08-04T13:56:08Z

@viclafargue Can you add appropriate labels, please?

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Inline comments:
In `@python/cuml/tests/test_kernel_ridge.py`:
- Line 139: Update the pytest.raises match pattern in the kernel ridge test to
escape the final period, using a raw regular-expression string so the assertion
matches the literal error message.

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Validate precomputed pairwise kernel shapes

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fallintoplace requested a review from a team as a code owner August 3, 2026 23:00

fallintoplace requested a review from csadorf August 3, 2026 23:00

github-actions Bot added the Cython / Python Cython or Python issue label Aug 3, 2026

github-actions Bot assigned fallintoplace Aug 3, 2026

coderabbitai Bot reviewed Aug 3, 2026

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Comment thread python/cuml/cuml/metrics/pairwise_kernels.py

Document precomputed kernel shape validation

11b250e

coderabbitai Bot reviewed Aug 3, 2026

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Comment thread python/cuml/cuml/metrics/pairwise_kernels.py Outdated

Clarify precomputed kernel Y documentation

52104bb

viclafargue approved these changes Aug 4, 2026

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csadorf removed their request for review August 4, 2026 13:56

Add feature dimension regression test

fc9b3ac

coderabbitai Bot reviewed Aug 4, 2026

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Comment thread python/cuml/tests/test_kernel_ridge.py Outdated

Escape kernel dimension test regex

a1c4d90

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Validate precomputed pairwise kernel shapes - #8441

Validate precomputed pairwise kernel shapes#8441
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fallintoplace:fix/precomputed-kernel-shape

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		if X.shape[1] != Y.shape[1]:
		raise ValueError("X and Y have different dimensions.")

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fallintoplace commented Aug 3, 2026

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