Files
pytorch/torch/distributed/constants.py
Edward Z. Yang ef3be6726f Make distributed modules importable even when backend not built (#159889)
This PR is greatly simplified now that it stacked on top of a PR that builds with distributed always. We only need to stub functions that may not be defined due to a backend not being enabled.

Signed-off-by: Edward Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/159889
Approved by: https://github.com/wconstab
ghstack dependencies: #160449
2025-09-04 20:05:50 +00:00

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Python

from datetime import timedelta
from typing import Optional
# Import from centralized fallback module - no ImportError handling needed
from torch.distributed._distributed_c10d import (
_DEFAULT_PG_NCCL_TIMEOUT,
_DEFAULT_PG_TIMEOUT,
)
__all__ = ["default_pg_timeout", "default_pg_nccl_timeout"]
# Default process group wide timeout, if applicable.
# This only applies to the non-nccl backends
# To make an attempt at backwards compatibility with THD, we use an
# extraordinarily high default timeout, given that THD did not have timeouts.
default_pg_timeout: timedelta = _DEFAULT_PG_TIMEOUT
# Separate timeout for PGNCCL mainly because it's always been that way in the C++ layer, but until recently
# there was one default that applied across all backends in the python layer.
# Later, we could consider merging them back together at the c++ layer if we can align on a same value.
# (only if TORCH_NCCL_BLOCKING_WAIT or TORCH_NCCL_ASYNC_ERROR_HANDLING is set to 1).
default_pg_nccl_timeout: Optional[timedelta] = _DEFAULT_PG_NCCL_TIMEOUT