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| license: mit |
| tags: [world-model, dream-drift, atari, evaluation, dreamerv3] |
| pretty_name: dream-drift DreamerV3 eval frames |
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| # dream-drift · DreamerV3 evaluation frames |
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| Raw dream-vs-reality frame dumps behind the DreamerV3 rows of the [dream-drift](https://github.com/iwillsolvehardestproblem/dream-drift) benchmark. Re-score every published number without a GPU. |
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| One file per game and protocol. `<game>id.npz` = in-distribution (the model's own replay trajectories); `<game>.npz` = cross-policy (expert DIAMOND-policy trajectories, the "confident healing" regime). |
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| Arrays per file: |
| - `real` uint8 (32, 50, 64, 64, 3): ground-truth frames (HWC), 32 start states x 50 steps |
| - `dream` uint8 (32, 4, 50, 64, 64, 3): 4 dream samples per start, same recorded actions, open loop |
| - `starts` (32,): start indices into the source trajectory; `game`, `burnin` (=4), `seed` (=0) scalars |
| - `rrew`, `drew` (32, 50) / (32, 4, 50): real and predicted rewards (predicted are raw; threshold |r|<0.5 to 0, then sign) |
| - `rend`, `dend`: real and predicted termination flags |
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| Scoring: `python harness/dreamer_score.py <dir-with-raw_frames.npz>` in the dream-drift repo reproduces `summary.json`, `drift.png`, and the videos. |
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