Comments (1)
It seems you could try more cpu and gpu actors, such as --cpu_actor 14 --gpu_actor 20
. Since you have 4 RTX6000 and each RTX6000 has more than 20GB of memory, I think the original bash file train.sh
is runnable on your machine.
Hope this can help you :)
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Related Issues (20)
- EfficientZero high memory consumption / keeps increasing after replay buffer is full HOT 7
- The first selfplay worker uses the same seed for all parallel environments HOT 2
- reproduce results for other environment
- Clarification on the atari environment?
- Envs seem not to work in parallel
- Cannot reproduce Breakout results
- Question about the transform between true reward and value prefix HOT 1
- Question about the index of pad_child_visits_lst in selfplay_worker.py HOT 2
- Question about the effect of state encoding indentity connection in dynamics network HOT 1
- Question about the effect of state encoding indentity connection in dynamics network
- Question about getting zero test score when I try to run EfficientZero on BabyAI grid environment HOT 2
- In reanalyze_worker GPU worker, why prepare policy targets and value targets separately? HOT 2
- Question about whether need to train multiple agents for different games HOT 1
- WSL2 NVIDIA 3090 or M1 MBP correct environment
- How to use with SLURM
- Question about the effect of discount factor and done mask when calculating the target value?
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- ray warning HOT 1
- Code for continuous action space HOT 1
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