Tests: improve CUDA support detection #985
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* implicitly skip any test that implicitly uses CUDA on a non-CUDA box * add a `requires_cuda` fixture
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Titus-von-Koeller
merged commit f1c7574
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bitsandbytes-foundation:main
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Looks good to me! Thanks for another useful contribution. Just out of curiosity, of course you don't have to answer, what led you to work with BNB, if you're not running Linux with a GPU? Are you involved with the Apple Silicon cross platform work? |
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Ah, you said you're on Linux :D |
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@Titus-von-Koeller Let's just say I have my contributing fingers here and there in the GenAI ecosystem 😁 |
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Most of the tests require CUDA capabilities; only some of them were previously marked as such and skipped when no CUDA was available, the rest of them were left to fail.
This PR adds a pytest hook that turns the Torch
Torch not compiled with CUDA enabledassertion error intopytest.skip, and a Pytest fixture that a test can use to assert that CUDA support is available too.On a machine where
make cpuonlypasses (namely in alinux/amd64Docker box), running tests onmain(53f8af8) results inWith this PR, the result is a more sensible
(though whether
test_nvidia_transformshould (partially) succeed on a machine with no CUDA is anybody's guess).Related to discussion in #984.