Use ubuntu:24.04 as base image for devel#166907
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tinglvv wants to merge 2 commits intopytorch:mainfrom
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Use ubuntu:24.04 as base image for devel#166907tinglvv wants to merge 2 commits intopytorch:mainfrom
tinglvv wants to merge 2 commits intopytorch:mainfrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/166907
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ✅ You can merge normally! (2 Unrelated Failures)As of commit 486eb0e with merge base 77da53a ( FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
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malfet
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Nov 3, 2025
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LGTM, but would be good to have a test plan of sorts (i.e. one can run container and build say flash attention inside) |
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Regarding test plan: Pass/Fail Criteria
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@pytorchbot rebase |
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@pytorchbot started a rebase job onto refs/remotes/origin/viable/strict. Check the current status here |
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Successfully rebased |
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@pytorchbot merge |
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
radeksm
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Feb 20, 2026
Issue - pytorch#166897 Currently the devel release image uses nvidia/cuda docker as base, we should not be blocked by the CUDA release process and should switch away from using nvidia/cuda docker as base. Pull Request resolved: pytorch#166907 Approved by: https://github.com/malfet, https://github.com/atalman
libohao1201
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Mar 2, 2026
Issue - pytorch#166897 Currently the devel release image uses nvidia/cuda docker as base, we should not be blocked by the CUDA release process and should switch away from using nvidia/cuda docker as base. Pull Request resolved: pytorch#166907 Approved by: https://github.com/malfet, https://github.com/atalman
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Issue - #166897
Currently the devel release image uses nvidia/cuda docker as base, we should not be blocked by the CUDA release process and should switch away from using nvidia/cuda docker as base.
cc @atalman @malfet @ptrblck @nWEIdia