ai-content-maker/.venv/Lib/site-packages/torch/distributed/rpc/_utils.py

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2024-05-03 04:18:51 +03:00
from contextlib import contextmanager
from typing import cast
import logging
from . import api
from . import TensorPipeAgent
logger = logging.getLogger(__name__)
@contextmanager
def _group_membership_management(store, name, is_join):
token_key = "RpcGroupManagementToken"
join_or_leave = "join" if is_join else "leave"
my_token = f"Token_for_{name}_{join_or_leave}"
while True:
# Retrieve token from store to signal start of rank join/leave critical section
returned = store.compare_set(token_key, "", my_token).decode()
if returned == my_token:
# Yield to the function this context manager wraps
yield
# Finished, now exit and release token
# Update from store to signal end of rank join/leave critical section
store.set(token_key, "")
# Other will wait for this token to be set before they execute
store.set(my_token, "Done")
break
else:
# Store will wait for the token to be released
try:
store.wait([returned])
except RuntimeError:
logger.error("Group membership token %s timed out waiting for %s to be released.", my_token, returned)
raise
def _update_group_membership(worker_info, my_devices, reverse_device_map, is_join):
agent = cast(TensorPipeAgent, api._get_current_rpc_agent())
ret = agent._update_group_membership(worker_info, my_devices, reverse_device_map, is_join)
return ret