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[SymmMem] Add runtime detection of NVSHMEM #156291
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/156291
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit 6ba7684 with merge base 4d9d884 ( BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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| py::arg("module")); | ||
| #endif | ||
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| module.def( |
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Nit: this is a C++ keyword. Not good for future versions.
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Ah I see
In C++, module is a context-sensitive keyword introduced with C++20 for the modules feature, used in declarations like
export module MyModule;.
I guess this file needs a big refactor then.
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@pytorchbot merge |
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 |
Stack from ghstack (oldest at bottom):
so that we can pick the default backend for SymmetricMemory without
fully relying on env var
TORCH_SYMMMEM=CUDA | NVSHMEMOn Python side, the following API is added:
torch.distributed._symmetric_memory.is_nvshmem_available()cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k