code: 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
      ``time.now() + 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 countdown 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)
  
imports: 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
label_desc: Use image node_id 2 for calling a global function with example usage: expires(after, scope, client) without return types