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Add CUDA libs in Python Conda, Consolidate Conda CI installs & use rapids-dask-dependency
#513
Add CUDA libs in Python Conda, Consolidate Conda CI installs & use rapids-dask-dependency
#513
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Am seeing errors like this in the C++ tests. However we really haven't changed anything on the C++ side
@madsbk do you have thoughts on what may be happening here? |
Hmm, I cannot reproduce locally. Let me try some CI debugging :) |
Trying to debug in CI: #562. The gtests works when running them directly, but fails when running through ctest:
Are we running a old cmake?
|
Thanks Mads! 🙏 Yep that's the issue We have a newer
Think this is because we install the environment and then later install KvikIO packages into the environment. Fixing this likely involves consolidating those 2 install steps on CI |
Sometimes the progress bar and other output activity causes issues in CI logs. It isn't necessary to include as we output the environment produced at the end. So quiet these install steps.
Also drop the YAML anchor as this is only used in one place.
That seems to have cleared up those errors. Saw some new errors)
This is happening as we are getting a really old copy of Dask, which is incompatible with NumPy 2
It looks like we were just setting a lower bound on Dask and using that to test Line 370 in 3d2ab00
However everywhere else in RAPIDS we use So have pushed a similar change here to address this issue |
rapids-dask-dependency
Looks like that last change fixed. CI now passes! 🥳 |
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Changes look fine to me. Are the -q
flags for conda/mamba meant to fix all the blank lines that appear from the download progress bars? We may want a tracking issue so we can apply that consistently. Perhaps something should go in the CI images’ base conda config?
Thanks Bradley! 🙏 Yes exactly Good ideas. Filed upstream issue: rapidsai/build-planning#126 Please add anything else needed over there |
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Thanks @jakirkham
Do we want this is |
I think yes. But I am okay with it going to 25.02. It definitely improves CI correctness. |
/merge |
Thanks Bradley and Mads! 🙏 |
Explicitly include dependencies on
libcufile*
and*cudart*
in the Python Conda package. These seem to be pulled in implicitly by the C++ package. However as they are dependencies of the Python built shared objects, they should also be listed here.Also consolidate the Conda environment creation and installation of nightly dependencies into one step. By doing this in one step, we guarantee that all of our constraints are taken into account during environment creation.
Lastly switch from using
dask
directly torapids-dask-dependency
to align Dask installation and pinning with the rest of RAPIDS.xref: rapidsai/build-planning#22
xef: #378