Comments (2)
mfe7
commented on August 15, 2024
- We didn't spend much time optimizing for computation speed. The CADRL policy in particular uses quite outdated custom NN implementations that likely contribute to slow runtime. If you have access to multiple machines or could run on a bunch of cloud/AWS machines in parallel, that would be one way to generate more samples faster.
- Changing this line to use your gpu should do it. In my experience, using CPU led to a higher number of samples per second, maybe because there were no images or conv layers in the NN architecture. But, I would be interested to hear about your experience on this.
from gym-collision-avoidance.
kmzdaniel
commented on August 15, 2024
Thank you very much for your answer, Mr. Everet.
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Related Issues (18)
- Code request HOT 2
- Loading weight problem HOT 2
- Training source HOT 2
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- ModuleNotFoundError: No module named 'rvo2' HOT 6
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- Problem with pip during installation HOT 5
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