Comments (8)
Your efficient response touched me.
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Fixed in e898f75
Also there are some warnings that do not affect performance of the algorithm.
I will fix them closer to the 0.5.0 release.
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@ikostrikov I think the performance is affected in version 0.4.0
python3 main.py --env-name "PongDeterministic-v4" --num-processes 16
Time 00h 00m 09s, num steps 5031, FPS 519, episode reward -21.0, episode length 812
Time 00h 01m 10s, num steps 35482, FPS 501, episode reward -2.0, episode length 100
Time 00h 02m 11s, num steps 66664, FPS 505, episode reward -2.0, episode length 100
Time 00h 03m 13s, num steps 97058, FPS 503, episode reward -2.0, episode length 100
Time 00h 04m 14s, num steps 128517, FPS 504, episode reward -2.0, episode length 108
Time 00h 05m 24s, num steps 163141, FPS 502, episode reward -21.0, episode length 764
Time 00h 06m 34s, num steps 200426, FPS 508, episode reward -21.0, episode length 764
Time 00h 07m 57s, num steps 245725, FPS 514, episode reward -21.0, episode length 1942
Time 00h 09m 16s, num steps 284730, FPS 511, episode reward -21.0, episode length 1324
Time 00h 10m 41s, num steps 325153, FPS 507, episode reward -21.0, episode length 1324
Time 00h 12m 01s, num steps 361563, FPS 501, episode reward -21.0, episode length 1324
Time 00h 13m 28s, num steps 406910, FPS 503, episode reward -21.0, episode length 1964
Time 00h 14m 53s, num steps 450836, FPS 505, episode reward -21.0, episode length 1964
Time 00h 16m 22s, num steps 493876, FPS 503, episode reward -21.0, episode length 1964
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How many cores do you have on your machine?
Is seems to start learning something since the length of the episodes goes up.
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Number of Processors: 1
Total Number of Cores: 2
I will test that on 64 cores machine.
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On 2 core machine it will just take a lot of time. I would expect a decent reward after 1h of training on Pong.
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I'm using pytorch-cpu 0.4.1 and Python3.7 in Windows7.
Still see this error "TypeError: multinomial() missing 1 required positional arguments: "num_samples""
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@ph-dev-2016 Try with the most recent version of this repository.
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Related Issues (20)
- gradient share problem HOT 1
- GAE parameter name should be lambda not tau. And why is default 1.0? HOT 4
- What's the difference between environment 'Pong-v4' and 'PongDeterministic-v4'
- Reward Smoothing
- Multi-processing or multi-threading HOT 1
- The while True loop of function train?
- NotImplementedError HOT 6
- [Question] Does a2c support distributed processing?
- Question in train.py
- with respect to how to choose an action
- How does A3C aggregate the model from different learner? HOT 1
- Why do we reverse rewards? HOT 1
- Dependency list not provided (environment.yml file)
- Stuck in 'p.join()' HOT 1
- After some steps, all the NNs always output same action HOT 1
- Scepticism about the correctness of the use of the LSTMCell
- Can you provide the python, pytorch, numpy and other versions used in the project?
- TypeError: tuple indices must be integers or slices, not tuple
- if there's no "if shared_param.grad is not None: return" what will happen? HOT 1
- where see the result?
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