Comments (2)
Is it possible to move the rollout buffer completely to the GPU?
By saving, you mean that the data stored in on the cpu?
currently not, you would need to write a custom buffer (and probably update SB3, gym API assumes numpy arrays), you can also have a look at related issues on SB3 repo (#314 and all linked issues).
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Thank you for the fast response. Yes, I meant storing.
I think I will work on upgrading to support tensors.
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Related Issues (20)
- ValueError: could not broadcast input array from shape (23,) into shape (27,) HOT 2
- SAC model not properly saved HOT 5
- [Question] Pong environment with A2C not learning with example code HOT 1
- [Question] The error about DQN--ep_len_mean&ep_rew_mean output HOT 1
- [Question] How to access to rollout (logger) data in callback HOT 2
- [Feature Request] Allow users to define gradient steps as a fraction of rollout time-steps HOT 3
- SubprocVecEnv Sets Out-of-Range Seeds for My Environments (ScenarioNet Enviroment) HOT 8
- [Question] A error while using SAC and DDPG HOT 1
- [Question] LSTM and SAC - Am I understanding the docs correctly? HOT 3
- [Question] Why torch model in c++ got totally different output from python HOT 4
- [Bug]: Manually setting net_arch=None causes crash when loading model HOT 3
- [Question] Why resample SDE noise matrices in PPO optimzation? HOT 4
- [Question] SAC, a torch model becomes a bool somehow HOT 1
- [Question] Running Multi-threaded PPO training independently with no interference HOT 3
- Setting up seed in Custom Gym environment HOT 5
- What does the output of model.learn mean? HOT 3
- [Feature Request] Random Network Distillation with PPO (RND-PPO) HOT 1
- [Question] Optimization of memory usage HOT 8
- [Question] Relationship between n_step, episode, and advantage in episodic tasks HOT 4
- You must pass an environment when using `HerReplayBuffer`
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