code: def test_averaging_trigger():
      averagers = tuple(
          DecentralizedAverager(
              averaged_tensors=[torch.randn(3)],
              dht=dht,
              min_matchmaking_time=0.5,
              request_timeout=0.3,
              prefix="mygroup",
              initial_group_bits="",
              start=True,
          )
          for dht in launch_dht_instances(4)
      )
  
      controls = []
      for i, averager in enumerate(averagers):
          controls.append(
              averager.step(
                  wait=False,
                  scheduled_time=hivemind.get_dht_time() + 0.5,
                  weight=1.0,
                  require_trigger=i in (1, 2),
              )
          )
  
      time.sleep(0.6)
  
      c0, c1, c2, c3 = controls
      assert not any(c.done() for c in controls)
      assert c0.stage == AveragingStage.RUNNING_ALLREDUCE
      assert c1.stage == AveragingStage.AWAITING_TRIGGER
      assert c2.stage == AveragingStage.AWAITING_TRIGGER
      assert c3.stage == AveragingStage.RUNNING_ALLREDUCE
  
      c1.allow_allreduce()
      c2.allow_allreduce()
      time.sleep(0.5)
      assert all(c.stage == AveragingStage.FINISHED for c in controls)
      assert all(c.done() for c in controls)
  
      # check that setting trigger twice does not raise error
      c0.allow_allreduce()
  
imports: import random
  import time
  import numpy
  import pytest
  import torch
  import hivemind
  from hivemind.averaging import DecentralizedAverager
  from hivemind.averaging.allreduce import AveragingMode
  from hivemind.averaging.control import AveragingStage
  from hivemind.averaging.key_manager import GroupKeyManager
  from hivemind.averaging.load_balancing import load_balance_peers
  from hivemind.averaging.partition import AllreduceException
  from hivemind.p2p import PeerID
  from test_utils.dht_swarms import launch_dht_instances
label_desc: Use image node_id 16 for calling a global function with example usage: test_averaging_trigger() without return types