pytorch-lightning
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Update tests that mock cuda availability and extend it for mps
Proposed refactor
We have tests that fail locally on MPS supported devices because their mocking of CUDA does not extend to MPS. After #13947 landed, the availability check actually works now and we need to update some tests. These are mainly the tests that have this combination of settings:
- has
accelerator="gpu"
(which includes both cuda and mps) - has function mocks like
torch.cuda.is_available
as True ortorch.cuda.device_count > 0
.
An example of such a test:
https://github.com/Lightning-AI/lightning/blob/e6a8283e9cd9df53fb661c64bbf2037e1391a16d/tests/tests_pytorch/trainer/connectors/test_accelerator_connector.py#L245-L262
Motivation
Let MPS users run the tests locally (me).
Pitch
Extend the mocking to MPS where applicable. In some tests it may make sense to actually only test for cuda, in which case we should change accelerator="gpu"
to "cuda"
. Some other tests may need to be skipped entirely on MPS.
Note that simply slapping a RunIf(min_cuda=x)
on top of these tests is not an option, as for most of the tests we want to run them with mocks on the CPU.
Additional context
Rather do this sooner than later. Right now, I can't differentiate from tests failing because of bugs in my branch vs. them failing due to this.
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cc @borda @akihironitta @justusschock
I'd like to help with this; I am on an M1 series mac and have some experience writing tests (for flash).
Thanks @JustinGoheen. Let me know if you have any questions.
apologies, I'm no longer able to work this.