FIX utils.multiclass.type_of_target with numpy 1.24 dev #24044
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The scipy-dev build fails since there are still some errors to fix there, but there are no more errors like the one below which shows that the fix works for numpy 1.24dev: |
thomasjpfan
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Jul 29, 2022
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I do not think we actually support jagged arrays as a target. After the jagged array is created, I think we always raise a more detailed error. Some of this behavior is tested in test_raise_value_error_multilabel_sequences.
As a quick fix, I am okay with this PR.
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Thanks @lesteve |
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…#24044) Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
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Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
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…#24044) Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
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Seen in #23626.
In numpy 1.24dev,
np.array([[1], [1, 2]])raises aValueErroryou need to specifydtype=objectexplicitly.See https://numpy.org/neps/nep-0034-infer-dtype-is-object.html for more details.
I think this was an oversight in #18423.
Not super familiar with the
sklearn.utils.multicass.type_of_target/is_multilabeldetails, but I am wondering whether we could simplify the code and usey = np.asarray(y, dtype=object). Maybe we rely on the inferred dtype in the non-ragged array-like case. Edit: looks like we are sincepytest sklearn/utils/tests/test_multiclass.pyfails when trying to use my naive simplification.