Comments (4)
The RAM usage keeps increasing during training until it reaches the limit and stopped. There must be something wrong.
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This might be the replay buffer growing as expected. How much RAM do you have? Does it work if you use the debug
config (which specifies a tiny replay buffer)?
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My RAM is 32GB, but I tried other tasks like dmc_vision dmc_walker_walk
and it works just fine even after 3M steps.
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@danijar Yes I notice the increasing RAM usage for all tasks.
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Related Issues (20)
- Ask about jit in ninjax.py HOT 1
- (Maybe) a small bug in replay buffer implementation HOT 1
- Lambda Return Calculation Bug? HOT 2
- Checkpoint loading - memory doubles HOT 1
- Confusion about the initial states of RSSM HOT 2
- [Question] How is symlog used in training?
- Dockerfile CUDA Image Version, COPY Path, and Execution Instructions Need Updates HOT 4
- Calling JAXAgent train gets stuck if using larger image sizes (inside Ninjax) HOT 3
- Scaling encoder and decoder MLP sizes? HOT 3
- Meaning of `is_last` and `is_terminal` and their effect on the value function HOT 2
- [Question] Question about the implementation of the Critic in "Mastering Diverse Domains through World Models" HOT 2
- Addition of "tree_map(np.asarray, value)" to "_convert_inps" function in "JAXAgent" HOT 1
- Dict based action space HOT 3
- Extremely large gradient and vanishing images when using jax.precision=float32 HOT 2
- Weight Initialization HOT 1
- Scaling laws in low-data regime
- How to optimize trade-offs in Scaling Laws HOT 1
- DreamerV3-Obstacle Tower HOT 1
- Crafter-model size HOT 1
- details about SAC used in the paper HOT 1
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