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OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 16.04.6 LTS (GCP)
Ray installed from (source or binary): source
Ray version: 0.6.4
Python version: 3.6.8
Describe the problem
I tested atari-a2c with tuned parameter(/tuned_examples/atari-a2c.yaml)
It showed great result for atari breakout.
However if "use_pytorch": true was added, the result is quite different. (I used "atari-a2c-pytorch.yaml" in the 'Source code / logs' section)
It was very slow and it seems that there was no improvement.
I guess there's some performance issue on pytorch a2c, but are there any necessary options for pytorch a2c?
We haven't spent time tuning the torch vision models, so this is probably expected. Also, PyTorch needs explicit tensor.cuda() calls to support GPU acceleration, which is not implemented as well (help here would be welcome)!
pong-a3c-pytorch.yaml might still work ok though, cc @richardliaw
System information
Describe the problem
I tested atari-a2c with tuned parameter(/tuned_examples/atari-a2c.yaml)
It showed great result for atari breakout.
However if "use_pytorch": true was added, the result is quite different. (I used "atari-a2c-pytorch.yaml" in the 'Source code / logs' section)
It was very slow and it seems that there was no improvement.
I guess there's some performance issue on pytorch a2c, but are there any necessary options for pytorch a2c?
Source code / logs
atari-a2c.yaml
atari-a2c-pytorch.yaml
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