do not send cancel

hivemind/optim/experimental/optimizer.py

@@ -682,15 +682,6 @@ class Optimizer(torch.optim.Optimizer):
                 if not scheduled_round.triggered:
                     scheduled_round.weight = 0
                     scheduled_round.allow_allreduce()
-        for scheduled_round in self.scheduled_grads, self.scheduled_state:
-            if scheduled_round is not None and not scheduled_round.done():
-                try:
-                    time_to_deadline = scheduled_round.deadline - get_dht_time()
-                    scheduled_round.result(timeout=max(0.0, time_to_deadline))
-                except BaseException as e:
-                    logger.log(self.status_loglevel, f"Caught {e} while averaging gradients")
-                if not scheduled_round.done():
-                    scheduled_round.cancel()
         self.scheduled_grads = self.scheduled_state = None
 
     def state_dict(self) -> dict: