combine pip install calls in wheel-testing scripts #4701
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jameslamb
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In addition to codeowners, I'd like to get your opinion on this too @alexbarghi-nv |
KyleFromNVIDIA
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Oct 10, 2024
alexbarghi-nv
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Oct 10, 2024
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Ok cool, thank you both! |
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/merge |
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Oct 23, 2024
…e dependency (#230) While working on adding CI for `wholegraph` in the new `cugraph-gnn` repo (rapidsai/cugraph-gnn#58), I noticed a few issues here. * `pylibwholegraph` imports `numpy` at runtime, but its wheels and conda package don't declare a runtime dependency on `numpy` * wheel runtime and testing dependencies are not being managed by `rapids-dependency-file-generator` * `wholegraph_binding` Cython code imports NumPy but doesn't use it * the wheel-testing CI environment is built up with a sequence of `pip install` calls instead of a single one to get all dependencies (see rapidsai/cugraph#4701) This proposes fixes for those things. ## Notes for Reviewers ### Where is the NumPy runtime dependency coming from? https://github.com/rapidsai/wholegraph/blob/0efba33835d6e4e104b5d7101a91e0ea55a6ca53/python/pylibwholegraph/pylibwholegraph/torch/data_loader.py#L14 Authors: - James Lamb (https://github.com/jameslamb) Approvers: - Kyle Edwards (https://github.com/KyleFromNVIDIA) URL: #230
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Summary
Follow-up to #4690.
Proposes consolidating stuff like this in CI scripts:
Into this:
Benefits of these changes
Reduces the risk of creating a broken environment with incompatible packages. Unlike
conda,pipdoes not evaluate the requirements of all installed packages when you runpipinstall.Installing
torchandcugraph-dglat the same time, for example, gives us a chance to find out about packaging issues like "cugraph-dglandtorchhave conflicting requirements on{other_package}" at CI time.Similar change from
cudf: rapidsai/cudf#16575