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fix(dataset): use conservative bounds for quantile aggregation instead of incorrect weighted mean (#3804)

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* fix(stats): use conservative bounds for quantile aggregation instead of incorrect weighted mean

* docs: add --overwrite/--skip-images/--root options to augment_dataset_quantile_stats usage

* fix(dataset): clarify quantile aggregation semantics

* fix(augment): handle quantile stats edge cases
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Hiroaki.Ishikawa
2026-08-07 01:39:01 +09:00
committed by GitHub
parent b1bf24f565
commit 31fedfd9dd
6 changed files with 308 additions and 88 deletions
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docs/source/molmoact2.mdx
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@@ -242,6 +242,17 @@ python src/lerobot/scripts/augment_dataset_quantile_stats.py \
--repo-id=your_dataset
```
Recording, resuming, and merging aggregate quantiles from per-episode summaries, so `meta/stats.json` ends up holding a conservative envelope (`min` for `q <= 50`, `max` for `q > 50`) rather than whole-dataset quantiles. To estimate the latter, scan every episode with a running histogram:
```bash
python src/lerobot/scripts/augment_dataset_quantile_stats.py \
--repo-id=your_dataset \
--overwrite \
--skip-images
```
`--skip-images` keeps the existing image statistics and avoids video decoding when only `STATE`/`ACTION` need recomputing, and `--root` reads a local dataset instead of the Hub. These values are histogram estimates, subject to discretization and rebinning error, so they can differ from the conservative ones — which changes MolmoAct2's normalized targets and therefore its loss scale. Statistics already saved inside an existing checkpoint are not affected.
Alternatively, train MolmoAct2 with mean/std normalization:
```bash