Closed Oakento closed 3 years ago
Hi, The program should run despite that "tornado application error" inside the docker. According to the authors of Arboreto, you can ignore those errors (https://github.com/aertslab/arboreto/issues/10). So long as the docker is running, the algorithm should be running. I'm assuming you are trying to run GENIE3 on a large-ish dataset (thousands of genes?), which will take a while to complete. If the docker exits without any output, then let me know. Best, Aditya
I encountered the same problem. How did you solve it in the end?
`distributed.comm.inproc - WARNING - Closing dangling queue in
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "/opt/conda/lib/python3.7/site-packages/tornado/ioloop.py", line 743, in _run_callback ret = callback() File "/opt/conda/lib/python3.7/site-packages/tornado/ioloop.py", line 767, in _discard_future_result future.result() File "/opt/conda/lib/python3.7/site-packages/distributed/deploy/spec.py", line 401, in _close await self._correct_state() File "/opt/conda/lib/python3.7/site-packages/distributed/deploy/spec.py", line 328, in _correct_state_internal await self.scheduler_comm.retire_workers(workers=list(to_close)) File "/opt/conda/lib/python3.7/site-packages/distributed/core.py", line 810, in send_recv_from_rpc comm = await self.live_comm() File "/opt/conda/lib/python3.7/site-packages/distributed/core.py", line 772, in live_comm **self.connection_args, File "/opt/conda/lib/python3.7/site-packages/distributed/comm/core.py", line 334, in connect _raise(error) File "/opt/conda/lib/python3.7/site-packages/distributed/comm/core.py", line 275, in _raise raise IOError(msg) OSError: Timed out trying to connect to 'inproc://172.17.0.2/9/1' after 10 s: Timed out trying to connect to 'inproc://172.17.0.2/9/1' after 10 s: connect() didn't finish in time `
Hi, I was trying to run grnbeeline/arboreto:base through BLRunner.py as the following command.
However, an error occurred and the program stuck.
The error is not stable that there is a probability of the error in different places in multiple attempts.
Additionally, the containers are running under docker's bridge network.