# Worker times out while preparing for training

**URL:** <https://discuss.ray.io/t/worker-times-out-while-preparing-for-training/2704>\
**Category:** Ray Tune\
**Created:** [June 29, 2021, 3:49pm UTC](https://discuss.ray.io/t/worker-times-out-while-preparing-for-training/2704 "2021-06-29T15:49:31Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![eg4l](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/eg4l/32/1150_2.png) [@eg4l](https://discuss.ray.io/u/eg4l)\
**Post date:** [June 29, 2021, 3:49pm UTC](https://discuss.ray.io/t/worker-times-out-while-preparing-for-training/2704/1 "2021-06-29T15:49:31Z")

</div>

Function I provide to tune.run does some preparations before it launches actual training.  
It happens that this preparation sometimes takes long enough for a timeout to occur with the following output:

```auto
(pid=303) 2021-06-29 08:34:50,334	ERROR trial_runner.py:748 -- Trial start_training_with_trainer_62d4f6f8: Error processing event.
(pid=303) Traceback (most recent call last):
(pid=303) File "/home/ray/anaconda3/lib/python3.7/site-packages/ray/tune/trial_runner.py", line 718, in _process_trial
(pid=303) results = self.trial_executor.fetch_result(trial)
(pid=303) File "/home/ray/anaconda3/lib/python3.7/site-packages/ray/tune/ray_trial_executor.py", line 688, in fetch_result
(pid=303) result = ray.get(trial_future[0], timeout=DEFAULT_GET_TIMEOUT)
(pid=303) File "/home/ray/anaconda3/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 62, in wrapper
(pid=303) return func(*args, **kwargs)
(pid=303) File "/home/ray/anaconda3/lib/python3.7/site-packages/ray/worker.py", line 1496, in get
(pid=303) raise value
(pid=303) ray.exceptions.RayActorError: The actor died unexpectedly before finishing this task.

```

Right now I don’t think I can avoid this preparation that takes sometimes above 60 seconds.  
Is there some easy way to avoid this that I am missing?