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View Code? Open in Web Editor NEWPyTorch Implementation of Distributed Prioritized Experience Replay(Ape-X)
PyTorch Implementation of Distributed Prioritized Experience Replay(Ape-X)
Maybe we could make a copy of replay buffer and sample k batches on that copy to avoid requiring block every time we sample a batch?
https://github.com/belepi93/Ape-X/blob/f414a667f84f2c2bb4ca22a0517217c06ea1f8d4/wrapper.py#L284
실제 동작과는 관련없지만, ImageToPyTorch 의 observation_space는 unwrapped env의 observation space와 shape만 다르고, low / high / dtype은 같아야 할 것 같습니다.
이 부분은 정확하지 않은데, env를 래핑할 때 FrameStack 후에 ImageToPyTorch를 씌우면 LazyFrame이 np.array로 바뀌면서 메모리 공유가 해제되는 것 같습니다.
Thanks to share the code~
Do you deal with the items in you TODOs?
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