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README pointed at scripts/train_*.sh; the scripts live under scripts/train/. docs/training.md already had the correct paths. docs/data_configuration.md Steps 3 and 4 described a DATASET_REGISTRY shape and a dataset_config: YAML list that configs/dataset_info.py and BeingH/dataset/base_dataset.py do not accept. Update both to match the registry/info split and the parallel-list YAML used by configs/posttrain/libero/libero_all.yaml.
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Two small documentation fixes.
Summary
scripts/train_libero_example.sh; the scripts live underscripts/train/.docs/training.mdalready gives the correct paths.docs/data_configuration.mdSteps 3 and 4 describe a schema the code does not accept. Steps 1, 2and 5 were already accurate and are unchanged.
Root Cause
1. README paths.
2. Dataset-registration schema.
Step 3 shows
DATASET_REGISTRYentries as dicts withpathanddata_configkeys. Inconfigs/dataset_info.py,DATASET_REGISTRYmaps a dataset group name to a dataset class(
LeRobotIterableDataset), and the paths live in a separateDATASET_INFOdict under{group: {dataset_name: {'dataset_path': ...}}}.Step 4 shows the YAML as a
dataset_config:list of{dataset_name, data_config, weight}entries.BeingH/train/train.pyloads the YAML andBeingH/dataset/base_dataset.pyreads it as a top-levelgroup name whose value carries parallel lists
dataset_names/data_config_names/embodiment_tags, plus sampling options — the shape used byconfigs/posttrain/libero/libero_all.yaml.Following the documented schema produces a config the loader cannot read. The updated text matches
configs/dataset_info.pyand the shipped YAML.Test plan
The corrected Step 3/4 schema was used verbatim to register and train on a LIBERO dataset (10-step
run on
libero_spatial, 1×H100), and the documented Step 5 verification command works as written.