ENH Array Api support for linear, polynomial and sigmoid kernels #29475
Conversation
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The CUDA run was green: https://github.com/scikit-learn/scikit-learn/actions/runs/10451046790/job/28936627899 but the status was removed from the list once I added the "waiting for reviewer" label. |
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There was a random 403 error calling |
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@betatim this one should be quick to review and merge and would unblock the other linked PR. |
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@adrinjalali Could you kindly review this PR? I think it should be quick review. |
| @@ -1537,14 +1537,16 @@ def sigmoid_kernel(X, Y=None, gamma=None, coef0=1): | ||
| array([[0.76..., 0.76...], | ||
| [0.87..., 0.93...]]) | ||
| """ | ||
| xp, _ = get_namespace(X, Y) | ||
| X, Y = check_pairwise_arrays(X, Y) | ||
| if gamma is None: | ||
| gamma = 1.0 / X.shape[1] | ||
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| K = safe_sparse_dot(X, Y.T, dense_output=True) |
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I'm confused, safe_sparse_dot seems to support array API, but at the end we have
But I can't find toarray in the array API standard. So what am I missing?
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That part of the code only runs for sparse arrays. So it isn't linked to the array api.
…kit-learn#29475) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
Reference Issues/PRs
Towards #26024
What does this implement/fix? Explain your changes.
sklearn.pairwiseAny other comments?
CC: @ogrisel @adrinjalali @betatim
Note: I did check that the CUDA tests seem to pass.