Implicit distributed backend selection #516
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Contributor
booxter
commented
Apr 30, 2025
booxter
commented
- chore: bump pytorch to 2.6.0+
- feat: Rely on implicit detection of distributed backend
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E2E (NVIDIA L40S x4) workflow launched on this PR: View run |
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e2e workflow succeeded on this PR: View run, congrats! |
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@tiran any particular concerns with this bump of minimal pytorch to 2.6.0+ for training library? (It's already 2.6.0+ in ilab so I'd not expect any, but better double-check...) |
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As confirmed by Doug H, this won't change versions used downstream. ilab already pulls 2.6.0+ for all flavors. |
RobotSail
approved these changes
May 20, 2025
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This pull request has merge conflicts that must be resolved before it can be |
This is in line with ilab repo. There are some features in later pytorch releases that we may want to have access to. Signed-off-by: Ihar Hrachyshka <[email protected]>
From the official docs, ``` Since 2.6, if backend is not provided, c10d will use a backend registered for the device type indicated by the device_id kwarg (if provided). ``` and: ``` If neither backend nor device_id is provided, c10d will detect the accelerator on the run-time machine and use a backend registered for that detected accelerator (or cpu). ``` While the library is still cuda centric, this is one tiny step towards a more agnostic implementation. Signed-off-by: Ihar Hrachyshka <[email protected]>
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