FIX: Compatibility with sklearn v1.8#1128
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BenjaminBossan merged 1 commit intomasterfrom Dec 22, 2025
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There were two issues in skorch with sklearn v1.8 that are now fixed: __sklearn_is_fitted__ should return a bool. Instead, we were just raising or returning None. Not sure if this was already wrong when added (#1119) or if the API changed later. Moreover, sklearn was now raising an error when using the SkorchDoctor class because of missing __sklearn_tags__. This class now inherits from BaseEstimator, resolving this issue. For good measure, I also tested locally with sklearn 1.7 to ensure that these changes are backwards compatible. Unrelated changes: Remove an unnecessary import and trailing whitespace. Added __sklearn_is_fitted__ to SkorchDoctor too.
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PS: Interestingly, the CI installs scikit-learn v1.8 only for Python 3.11+ (because of this rule which I found surprising), so for the 3.10 runner, we still get v1.7: https://github.com/skorch-dev/skorch/actions/runs/20369283427/job/58531681371?pr=1128#step:4:34 This means that our CI tests both versions, which is nice I guess. |
thomasjpfan
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Dec 20, 2025
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Small nit, otherwise LGTM
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Resolves #1127.
There were two issues in skorch with sklearn v1.8 that are now fixed:
__sklearn_is_fitted__should return abool. Instead, we were just raising or returningNone. Not sure if this was already wrong when added (#1119) or if the API changed later.Moreover, sklearn was now raising an error when using the
SkorchDoctorclass because of missing__sklearn_tags__. This class now inherits fromBaseEstimator, resolving this issue.For good measure, I also tested locally with sklearn 1.7 to ensure that these changes are backwards compatible.
Unrelated changes:
Remove an unnecessary import and trailing whitespace. Added
__sklearn_is_fitted__toSkorchDoctortoo.