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Swap CUDA 10.1 and CPU CI for windows #57493
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💊 CI failures summary and remediationsAs of commit bf65dd8 (more details on the Dr. CI page): 💚 💚 Looks good so far! There are no failures yet. 💚 💚 This comment was automatically generated by Dr. CI (expand for details).Follow this link to opt-out of these comments for your Pull Requests.Please report bugs/suggestions to the (internal) Dr. CI Users group. |
@janeyx99 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
@janeyx99 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
Hm, given how many cuda-related PRs and especially builds are broken on windows only, I'm afraid it will increase churn a lot. |
Does this mean no CI will be running for CUDA+Windows for PR? I feel worried about it as in the past Windows CI has been useful. (I saw Windows only failures ~twice last month) |
If I understand it correctly, Windows CI would only be triggered after the PR was merged into the master branch? |
I think based on our current cost for running Windows gpu executors it's just not tenable to run Windows CUDA tests on every PR. After this PR lands I'll do a follow up PR to add a CI label that we can use to trigger windows CUDA testing on PRs if requested. It'll be similar to #54018 |
@janeyx99 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
If failures on Windows CUDA checks do not usually result from the fact that Windows CUDA CI checks use a Tesla T4 GPU (SM_75), whereas Linux CUDA CI checks use an SM_52 GPU, how about also having a (regular) Windows CI check with an SM_52 GPU, if an executor with an SM_52 GPU is significantly cheaper than an executor with an SM_75 GPU? In that case, @seemethere can make two labels for Windows CUDA CI checks - one each for executors with an SM_52 & an SM_75 GPU respectively, so that one can choose the SM_52 one (cheaper), if the difference in CUDA Compute Capability would be deemed to not be a source of potential failures for an in-progress PR. |
Summary: This change temporarily disables CUDA testing on PRs, but keeps it on master. This is likely to increase the number of reverts, but this is necessary as a stop-gap measure to cap the CI costs growth. Pull Request resolved: pytorch#57493 Reviewed By: seemethere Differential Revision: D28162697 Pulled By: janeyx99 fbshipit-source-id: 1bc529a405f7d63c07f4bd9f8ceca8da450743fc
This change temporarily disables CUDA testing on PRs, but keeps it on master.
This is likely to increase the number of reverts, but this is necessary as a stop-gap measure to cap the CI costs growth.