Handle cudf.pandas proxy objects properly
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galipremsagar
changed the title
cudf.pandas proxy objects properly
hcho3
approved these changes
Nov 22, 2024
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@trivialfis Can you review this? |
trivialfis
reviewed
Nov 23, 2024
python-package/xgboost/data.py
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| @@ -846,6 +846,22 @@ def _is_cudf_df(data: DataType) -> bool: | |||
| return lazy_isinstance(data, "cudf.core.dataframe", "DataFrame") | |||
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| def _is_cudf_pandas_df(data: DataType) -> bool: | |||
| return ( | |||
| str(type(data)) == "<class 'pandas.core.frame.DataFrame'>" | |||
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We have a lazy isinstance method in the compat module, can we use that?
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Yes! We can, Verified in local testing this works.
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Added this to the 2.1.3 release. Will push some changes at Monday for |
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Changes from my commit:
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Please help test and review the change. |
Can confirm this works locally. |
trivialfis
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Nov 25, 2024
--------- Co-authored-by: Hyunsu Cho <phcho@nvidia.com> Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
trivialfis
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Nov 26, 2024
--------- Co-authored-by: GALI PREM SAGAR <sagarprem75@gmail.com> Co-authored-by: Hyunsu Cho <phcho@nvidia.com>
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cudf.pandasproxy objects will not passis_cudf....checks and rather they tend to only passis_pandas.... But the pandas code-flows have manyto_numpycalls that are introducing slow-downs incase ofcudf.pandasobjects. This PR bypasses this problem by introducing a mechanism to extract propercudfobjects out ofcudf.pandasobjects. That way there is no slow-down.