shwina
commented
6 months ago Thanks for reporting @paulsbrookes!
The isinstance checks against np.ndarray failing is a significant, but known limitation currently. Ideally, more code would accept "array-like" objects rather than do hard instancechecks against np.ndarray. This can be done by e.g., checking for the __array_interface__ attribute, or using try-except with a call to np.asarray. But, I know a lot of third-party code is not written this way. We hope to have a resolution for this soon.
The other isinstance check against BaseOffset seems a bug. I'll investigate and report back.
paulsbrookes
Describe the bug Some type checks fail with cuDF pandas objects.
Steps/Code to reproduce bug The following examples fail with assertion errors:
Both of these examples pass if we remove the
cudf.pandas.install()line.Expected behavior I expected the code blocks above to run so that I could use the accelerated version of pandas with zero code changes. The errors I'm facing make it difficult to work with cuDF pandas and other libraries (e.g. https://github.com/Nixtla/statsforecast).
Environment overview (please complete the following information)
Environment details
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