Front page › Forums › 🤖 🚗 AI Driving Olympics 🏆 › Embodied tasks › 600 Timeout when submit
This topic contains 5 replies, has 3 voices, and was last updated by heyt0ny 3 years, 6 months ago.
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November 8, 2018 at 6:27 pm #29618
Hi!
I’m getting 600 timeout error – https://challenges.duckietown.org/v3/humans/submissions/832
What may this mean?Thank you so much for answering the questions)
November 8, 2018 at 6:37 pm #29619I believe this is the same issue as your other post I answered this morning.
Can you post a link to the solution.py you are using?November 9, 2018 at 2:21 pm #29628So it’s really strange error and it’s not about solution file
So I have 2 models (A and B). They both return the same type and dimensions of action. The both run locally successfully.
But the model A is failed on step1-simulation. I dind’t change the architecture of model A for at least 1 week (I only changed weights). So I decided to use old weights from successful submits (~ 3 days ago) — and it still fails.
Then I decided to turn off weights load — and the model A is submitted successfully. But I’m 100% sure it’s not the problem with weights load, because model B uses the same code for weights load.
I’m really confused about it.
Is there any way I can download my submits to make sure I didn’t change anything.. ?
November 9, 2018 at 9:05 pm #29629Hey Tony, so my extremly wild guess would be that the docker image that your are using is using python2 and your weight were saved, using pickle, on python3.
If this is the case, you can fix it by changing the first line of your Dockerfile to
FROM pytorch/pytorch:0.4.1-cuda9-cudnn7-runtime
Cheers
November 10, 2018 at 9:45 pm #29872Thank you lavoiems, good point!
Tried it, but the same failure (
November 11, 2018 at 2:56 pm #29877seems like I was able to fix this, by adding frame skip:
nested_break = False try: cis.info('Reset environment') observation = env.reset() while True: action = model.predict(observation) if debug: env.render() for i in range(config['frame_skip']): observation, reward, done, info = env.step(action) if 'simulation_done' in info: cis.info('simulation_done received.') nested_break = True break if done: cis.info('Episode done; calling reset()') env.reset() break if nested_break: break finally: # release CPU/GPU resources, let's be friendly with other users that may need them cis.info('Releasing resources') try: model.close() except Exception as e: cis.error(e) msg = 'Could not call model.close():\n%s' % traceback.format_exc() cis.error(msg) cis.info('Graceful exit of solve()')
magic !
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