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Fix/cudf api updates #1044
Fix/cudf api updates #1044
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Thanks! However, it doesn't seem safe to merge this, because it requires cudf version 22.02.00 released only five days ago, and thus releasing datashader with these changes would mean people could use only the very latest cudf, which isn't always practical given the driver versions people have installed. Since the updates are to address deprecated API, is there a minimum version of cudf supporting this API that isn't quite so new? Otherwise we'll have to park this PR and revisit it in the following rather than the upcoming Datashader release. |
@jbednar, that makes sense. So the minimum version the new api supports is 21.12, which was released a couple of months ago (Dec 3, 2021). How old a version of cudf do you think would be practical to merge? Another option could be using api on the current installed version of cudf, for e.g: 22.04 to be released will have removed the older version, so we can just check the user installed version and use the corresponding api: if cudf_version >= Version("22.02"):
return df.to_cupy()
else:
return df.as_gpu_matrix() Does the above work? |
I have pushed some changes, and reverted the minimum cudf version update (although the recommended version would always be the latest stable release) |
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Thanks @AjayThorve! The December release is still pretty recent, what's the driver compatibility for cuDF 21.12? I guess all of the recent versions require CUDA 11.x + Driver v450.80.02+? In that case I'm okay with this. Do we need to make similar updates in HoloViews? |
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yes, CUDA 11.x + Driver v450.80.02+ since atleast the June,2020 release.
I am open to helping out replace all the deprecated cudf code across holoviews projects, I think hvplot uses it? |
Okay great, I'm happy to see this merged! hvPlot indeed uses HoloViews to generate the plots, help updating it would be hugely appreciated! |
This PR replaces deprecated methods in cudf, related to conversion to a cupy array from cudf.DataFrame and cudf.Series. The new methods also provide performance improvements as demonstrated here: https://docs.rapids.ai/api/cudf/nightly/user_guide/10min-cudf-cupy.html#Converting-a-cuDF-Series-to-a-CuPy-Array
Finally, also updating the minimum version of cudf's last stable release (22.02)
(tested locally with the latest rapids libraries)