Source code for torch.distributed.elastic.timer.api

# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import abc
import logging
import threading
import time
from contextlib import contextmanager
from inspect import getframeinfo, stack
from typing import Any, Dict, List, Optional, Set

[docs]class TimerRequest: """ Data object representing a countdown timer acquisition and release that is used between the ``TimerClient`` and ``TimerServer``. A negative ``expiration_time`` should be interpreted as a "release" request. .. note:: the type of ``worker_id`` is implementation specific. It is whatever the TimerServer and TimerClient implementations have on to uniquely identify a worker. """ __slots__ = ["worker_id", "scope_id", "expiration_time"] def __init__(self, worker_id: Any, scope_id: str, expiration_time: float): self.worker_id = worker_id self.scope_id = scope_id self.expiration_time = expiration_time def __eq__(self, other): if isinstance(other, TimerRequest): return ( self.worker_id == other.worker_id and self.scope_id == other.scope_id and self.expiration_time == other.expiration_time ) return False
[docs]class TimerClient(abc.ABC): """ Client library to acquire and release countdown timers by communicating with the TimerServer. """
[docs] @abc.abstractmethod def acquire(self, scope_id: str, expiration_time: float) -> None: """ Acquires a timer for the worker that holds this client object given the scope_id and expiration_time. Typically registers the timer with the TimerServer. """ pass
[docs] @abc.abstractmethod def release(self, scope_id: str): """ Releases the timer for the ``scope_id`` on the worker this client represents. After this method is called, the countdown timer on the scope is no longer in effect. """ pass
class RequestQueue(abc.ABC): """ Consumer queue holding timer acquisition/release requests """ @abc.abstractmethod def size(self) -> int: """ Returns the size of the queue at the time this method is called. Note that by the time ``get`` is called the size of the queue may have increased. The size of the queue should not decrease until the ``get`` method is called. That is, the following assertion should hold: size = q.size() res = q.get(size, timeout=0) assert size == len(res) -- or -- size = q.size() res = q.get(size * 2, timeout=1) assert size <= len(res) <= size * 2 """ pass @abc.abstractmethod def get(self, size: int, timeout: float) -> List[TimerRequest]: """ Gets up to ``size`` number of timer requests in a blocking fashion (no more than ``timeout`` seconds). """ pass
[docs]class TimerServer(abc.ABC): """ Entity that monitors active timers and expires them in a timely fashion. This server is responsible for reaping workers that have expired timers. """ def __init__( self, request_queue: RequestQueue, max_interval: float, daemon: bool = True ): """ :param request_queue: Consumer ``RequestQueue`` :param max_interval: max time (in seconds) to wait for an item in the request_queue :param daemon: whether to run the watchdog thread as a daemon """ super().__init__() self._request_queue = request_queue self._max_interval = max_interval self._daemon = daemon self._watchdog_thread: Optional[threading.Thread] = None self._stop_signaled = False
[docs] @abc.abstractmethod def register_timers(self, timer_requests: List[TimerRequest]) -> None: """ Processes the incoming timer requests and registers them with the server. The timer request can either be a acquire-timer or release-timer request. Timer requests with a negative expiration_time should be interpreted as a release-timer request. """ pass
[docs] @abc.abstractmethod def clear_timers(self, worker_ids: Set[Any]) -> None: """ Clears all timers for the given ``worker_ids``. """ pass
[docs] @abc.abstractmethod def get_expired_timers(self, deadline: float) -> Dict[str, List[TimerRequest]]: """ Returns all expired timers for each worker_id. An expired timer is a timer for which the expiration_time is less than or equal to the provided deadline. """ pass
@abc.abstractmethod def _reap_worker(self, worker_id: Any) -> bool: """ Reaps the given worker. Returns True if the worker has been successfully reaped, False otherwise. If any uncaught exception is thrown from this method, the worker is considered reaped and all associated timers will be removed. """ def _reap_worker_no_throw(self, worker_id: Any) -> bool: """ Wraps ``_reap_worker(worker_id)``, if an uncaught exception is thrown, then it considers the worker as reaped. """ try: return self._reap_worker(worker_id) except Exception as e: logging.error( "Uncaught exception thrown from _reap_worker(), " "check that the implementation correctly catches exceptions", exc_info=e, ) return True def _watchdog_loop(self): while not self._stop_signaled: try: self._run_watchdog() except Exception as e: logging.error("Error running watchdog", exc_info=e) def _run_watchdog(self): batch_size = max(1, self._request_queue.size()) timer_requests = self._request_queue.get(batch_size, self._max_interval) self.register_timers(timer_requests) now = time.time() reaped_worker_ids = set() for worker_id, expired_timers in self.get_expired_timers(now).items(): f"Reaping worker_id=[{worker_id}]." f" Expired timers: {self._get_scopes(expired_timers)}" ) if self._reap_worker_no_throw(worker_id):"Successfully reaped worker=[{worker_id}]") reaped_worker_ids.add(worker_id) else: logging.error( f"Error reaping worker=[{worker_id}]. Will retry on next watchdog." ) self.clear_timers(reaped_worker_ids) def _get_scopes(self, timer_requests): return [r.scope_id for r in timer_requests] def start(self) -> None: f"Starting {type(self).__name__}..." f" max_interval={self._max_interval}," f" daemon={self._daemon}" ) self._watchdog_thread = threading.Thread( target=self._watchdog_loop, daemon=self._daemon )"Starting watchdog thread...") self._watchdog_thread.start() def stop(self) -> None:"Stopping {type(self).__name__}") self._stop_signaled = True if self._watchdog_thread:"Stopping watchdog thread...") self._watchdog_thread.join(self._max_interval) self._watchdog_thread = None else:"No watchdog thread running, doing nothing")
_timer_client = None
[docs]def configure(timer_client: TimerClient): """ Configures a timer client. Must be called before using ``expires``. """ global _timer_client _timer_client = timer_client"Timer client configured to: {type(_timer_client).__name__}")
[docs]@contextmanager def expires( after: float, scope: Optional[str] = None, client: Optional[TimerClient] = None ): """ Acquires a countdown timer that expires in ``after`` seconds from now, unless the code-block that it wraps is finished within the timeframe. When the timer expires, this worker is eligible to be reaped. The exact meaning of "reaped" depends on the client implementation. In most cases, reaping means to terminate the worker process. Note that the worker is NOT guaranteed to be reaped at exactly `` + after``, but rather the worker is "eligible" for being reaped and the ``TimerServer`` that the client talks to will ultimately make the decision when and how to reap the workers with expired timers. Usage:: torch.distributed.elastic.timer.configure(LocalTimerClient()) with expires(after=10): torch.distributed.all_reduce(...) """ if client is None: if _timer_client is None: raise RuntimeError("Configure timer client before using coundown timers.") client = _timer_client if scope is None: # grab the caller file + lineno caller = getframeinfo(stack()[1][0]) scope = f"{caller.filename}#{caller.lineno}" expiration = time.time() + after client.acquire(scope, expiration) try: yield finally: client.release(scope)


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