[BUG] Type checks fail with cuDF pandas objects #14674
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paulsbrookes
added
Needs Triage
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Thanks for reporting @paulsbrookes! The The other |
shwina
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python
Python
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Thanks @shwina! One workaround I've found for dealing with situations where third-party libraries do not know how to deal with a cuDF pandas DataFrame is to recreate the dataframe as follows: The code block above passes without an assertion error. If I understand correctly this creates a regular pandas dataframe from the cudf pandas dataframe which can then be used by third party libraries as normal. @shwina do you know of any alternatives to this? |
Correct - it also means that third-party libraries won't be able to leverage the GPU in any way.
No - that's right. The |
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I opened #14678, which addresses the first issue you raised (instancechecks against |
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Thanks @shwina! |
…ts against `BaseOffset` (#14678) Addresses part of #14674. This PR makes `cudf.pandas` aware of the `BaseOffset` type. Because of the way `isinstance()` checks work on proxy types*, we will now pass instance checks like: ```python freq = "D" assert isinstance(pd.tseries.frequencies.to_offset(freq), pd.tseries.offsets.BaseOffset) ``` *proxy types appear to be related to each other in the same way as their corresponding slow types. So if `A` inherits from `B`, then `ProxyA` _appears_ to inherit from `ProxyB` even though they are not _actually_ related by inheritance. Authors: - Ashwin Srinath (https://github.com/shwina) - Vyas Ramasubramani (https://github.com/vyasr) Approvers: - Vyas Ramasubramani (https://github.com/vyasr) URL: #14678
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Closing this issue since it's now a duplicate of #14537 |
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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