Scheduler gets stuck in a loop if one or more workers terminate during client.scatter()

In my code, I have a large object which will be scattered using client.scatter to all workers (broadcast=True).
However, I have seen that the scheduler can get stuck in a loop, if one or more workers go down in the middle of client.scatter() call. The produced logs are as follows:
Communication with worker tcp://192.168.55.103:8002 failed during replication: OSError: Timed out trying to connect to tcp://192.168.55.103:8002 after 60 s
Communication with worker tcp://192.168.55.103:8002 failed during replication: OSError: Timed out trying to connect to tcp://192.168.55.103:8002 after 60 s
Communication with worker tcp://192.168.55.103:8002 failed during replication: OSError: Timed out trying to connect to tcp://192.168.55.103:8002 after 60 s
....

I investigate this and seems that this comes from scheduler's replicate() call, where data/tasks are copied to all workers in a while loop, where copying is done in scheduler's gather_on_workers() function. However, this function does not throw an error if connecting to a terminated worker fails. Hence, making the scheduler to retry after "timeout" seconds.
Here is the snippet from replicate() function:
```
while tasks:
gathers = defaultdict(dict)
for ts in list(tasks):
if ts._state == "forgotten":
# task is no longer needed by any client or dependant task
tasks.remove(ts)
continue
n_missing = n - len(ts._who_has & workers)
if n_missing <= 0:
# Already replicated enough
tasks.remove(ts)
continue

count = min(n_missing, branching_factor * len(ts._who_has))
assert count > 0

for ws in random.sample(workers - ts._who_has, count):
gathers[ws._address][ts._key] = [
wws._address for wws in ts._who_has
]

await asyncio.gather(
*(
# Note: this never raises exceptions
self.gather_on_worker(w, who_has)
for w, who_has in gathers.items()
)
)
```
Is there any option to limit the number of scheduler retries in replicate() call?