File size: 1,109 Bytes
be4e27f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 |
from typing import Optional
import torch.distributed as dist
def get_rank(group: Optional[dist.ProcessGroup] = None):
return dist.get_rank(group) if dist.is_initialized() else 0
def get_world_size(group: Optional[dist.ProcessGroup] = None):
return dist.get_world_size(group) if dist.is_initialized() else 1
def barrier(group: Optional[dist.ProcessGroup] = None):
if dist.is_initialized():
dist.barrier(group)
class rank_gate:
'''
Execute the function on rank 0 first, followed by all other ranks. Useful when caches may need to be populated in a distributed environment.
'''
def __init__(self, func = None):
self.func = func
def __call__(self, *args, **kwargs):
rank = get_rank()
if rank == 0:
result = self.func(*args, **kwargs)
barrier()
if rank > 0:
result = self.func(*args, **kwargs)
return result
def __enter__(self, *args, **kwargs):
if get_rank() > 0:
barrier()
def __exit__(self, *args, **kwargs):
if get_rank() == 0:
barrier()
|