Comments (2)
@8JasonStatham8 Hi, thank you for using d3rlpy. When increasing the batch size, the computational cost also grows. So, it sounds sane to me. Also, if the observation dimension is small, you can't maximize GPU utility either.
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@takuseno Thank you.
But when I set batch_size to 1024, that my Volatile GPU-Util is just 16%. It 's not grow very high, I think it may be not the reason .
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Related Issues (20)
- [BUG] Scorer freezes HOT 4
- [BUG] Error for `gym` with version 0.26.2 HOT 2
- [QUESTION] Using n_frames for Tabular data HOT 2
- [BUG] Question / Possible bug - observation data changing when loaded into TransitionMiniBatch() HOT 9
- [BUG] CQL Crashing HOT 3
- [Question] Question about log parameters HOT 2
- [BUG] current overwriting of transitions in the buffer causes problems in to_mdp_dataset() HOT 7
- [QUESTION] Early stopping HOT 2
- [REQUEST] Vectorized / multiple env support HOT 2
- [BUG] Error in fitted q evaluation example HOT 3
- [REQUEST] How can I use Transformer to be a Encoder? HOT 3
- [QUESTION] What's meaning about discounted_sum_of_advantage_scorer? HOT 4
- [REQUEST] Adding Cal-QL HOT 2
- [Question] - Increasing model capacity HOT 2
- Models' Logits return, HOT 2
- [Question] How to append online transitions with pre-existing d4rl buffer in finetuning training? HOT 10
- [REQUEST] For next release, add the option to specify the ensemble reduction method as parameter of QFunc Factory
- Discrete version of MOPO / COMBO
- [REQUEST] Multi dimensional action space HOT 9
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