Comments (1)
We pop from the online queue if it's not empty and otherwise uniformly sample from the buffer. So each batch gets first filled with the available online sequences (emptying the queue) and the remaining batch entries are filled up with uniform samples.
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Related Issues (20)
- How to generate the scores json files HOT 1
- Replay sample is waiting X seconds (too empty: 0 < 1) HOT 1
- Need some clarifications about details in Atari env HOT 1
- How to add dropout HOT 1
- [Question] Adding separate optimizers/loss functions per network HOT 2
- Invalid syntax `segment = prob[*path]` HOT 2
- Clarification on `carry` variable used during training
- AttributeError: type object 'Module' has no attribute '__annotations__' HOT 1
- Some confusion on the env steps HOT 1
- Slow operation for convolution HOT 5
- Question about integration of Plan2Explore HOT 1
- Outdated README for custom environment and mlp_keys/cnn_keys HOT 2
- Replay parameters
- Where is the actual evaluation reward?
- The 12M model sizes doesn't align with the paper
- Package structure
- Why is the posterior being sampled for the policy during inference?
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