Handle nullable types and empty partitions before Dask-ML predict #799
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sarahyurick
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ayushdg,
charlesbluca and
galipremsagar
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sarahyurick
commented
Sep 22, 2022
sarahyurick
commented
Sep 22, 2022
sarahyurick
commented
Sep 22, 2022
Codecov Report
@@ Coverage Diff @@
## main #799 +/- ##
==========================================
- Coverage 74.88% 74.54% -0.35%
==========================================
Files 71 71
Lines 3588 3630 +42
Branches 748 759 +11
==========================================
+ Hits 2687 2706 +19
- Misses 771 786 +15
- Partials 130 138 +8
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sarahyurick
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sarahyurick
commented
Sep 30, 2022
sarahyurick
commented
Oct 4, 2022
| @@ -183,7 +184,16 @@ def convert(self, rel: "LogicalPlan", context: "dask_sql.Context") -> DataContai | |||
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| delayed_model = [delayed(model.fit)(x_p, y_p) for x_p, y_p in zip(X_d, y_d)] | |||
| model = delayed_model[0].compute() | |||
| model = ParallelPostFit(estimator=model) | |||
| if "sklearn" in model_class: | |||
| output_meta = np.array([]) | |||
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@VibhuJawa I wanted to ask your opinion on this check?
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I think we should handle this in https://github.com/dask-contrib/dask-sql/pull/832/files PR and follow dask/dask-ml#912 for a clean fix. I dont think we should fix it here.
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OK, I've moved these changes into #832. |
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@VibhuJawa
Re-opening #783 here.