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Ignore cudf's __dataframe__ deprecation. #6229
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Ignore cudf's __dataframe__ deprecation. #6229
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/ok to test |
Help on this PR is welcome! Please feel free to push if you can fix any of the remaining test failures. |
@@ -218,6 +218,8 @@ def test_predict_large_n_classes(datatype): | |||
assert array_equal(y_hat.astype(np.int32), y_test.astype(np.int32)) | |||
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# Ignore FutureWarning: Using `__dataframe__` is deprecated | |||
@pytest.mark.filterwarnings("ignore::FutureWarning") |
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This makes sure we only ignore the dataframe warning and not all FutureWarnings
. Also remvose the need for the comment I'd say
@pytest.mark.filterwarnings("ignore::FutureWarning") | |
@pytest.mark.filterwarnings("ignore:Support for loading dataframes via the `__dataframe__` interchange protocol is deprecated") |
(same for the other occurrence)
Looking at the failed CI jobs I see a lot of:
Which makes me think that somewhere in |
rapidsai/rmm#1775 would cause this warning, but we searched the RAPIDS code base extensively to make sure there were no internal uses of this that would trigger deprecations... I am looking now to see what we might have missed. |
I still don't see anything and can't reproduce locally. I am trying to rerun. |
I'm taking a look too. |
Seems like rerunning CI has fixed the problem. I suspect there was some intermediate state where the RMM PR had been merged but not all artifacts / dependencies agreed on how it was supposed to be used until the dependency tree (notably cudf) was rebuilt? Not sure. |
Currently CI is failing due to rapidsai/cudf#17736.
The
__dataframe__
protocol appears to be used internally by scikit-learn: https://github.com/scikit-learn/scikit-learn/blob/311bf6badd74bb69081eb90e2643f15706d3473c/sklearn/utils/validation.py#L389Errors look like:
This PR ignores the
FutureWarning
to allow CI to pass.