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name: "libero-conversion" description: "Guides conversion of LIBERO HDF5 task demonstrations into LeRobot datasets and safely evaluates optional simulator-based regeneration, including task discovery, state/action schemas, image resolution, execution controls, and failure recovery." disable-model-invocation: true metadata: disco-role: operating license: MIT

LIBERO conversion

Use this route when a user has LIBERO task-suite HDF5 files and wants a local or Hub-backed LeRobot dataset, or asks whether the files must be regenerated before conversion. This route covers the LIBERO-specific contract only. For executor lifecycle, temporary aggregation, and shared adapter behavior, load generic-conversion.

Safety boundary

• Treat conversion as a data-writing operation. First inventory source files, output roots, temporary roots, and any resume log directory.
• Prefer --executor local and --debug for a first structural smoke test. Do not start Ray, upload to the Hub, or regenerate through a simulator without explicit approval and a verified environment.
• The converter reads HDF5 and writes LeRobot data; it does not create missing camera modalities or resize images safely on its own. Never silently reshape 128x128 frames to the declared 256x256 feature shape.
• Simulator regeneration is reference-only in this skill. It requires external LIBERO, robosuite, task assets, off-screen rendering, and potentially a large HDF5 rewrite; it must not be run as part of planning or validation.

Route checklist

1. Confirm the source directories, desired output root, LeRobot format/version, and whether multiple suites/directories should be merged.
2. Inspect only direct children matching *.hdf5; derive the task instruction from each filename and reject or separately review files that do not match the supported naming convention. See workflows.
3. Validate every selected file's data group and each demo's required obs datasets before scheduling conversion. Check lengths, dtypes, image shapes, and finite numeric values using a read-only structural probe.
4. Confirm that RGB frames are 256x256x3, or stop and choose the explicit 128x128 handling/regeneration path in data formats.
5. Use the conversion flags and merge rules in workflows. Keep local execution as the baseline; use Ray only after its dependencies and cluster ownership are confirmed.
6. After conversion, inspect feature metadata, episode/task counts, image dimensions, action range, and state widths before any Hub push.
7. When a failure occurs, use troubleshooting and preserve the source and logs. Do not retry by deleting an unrelated output or by changing schemas to make validation pass.

LIBERO-specific data transformation

Each demo is emitted frame-by-frame with its task instruction attached. The six-dimensional end-effector pose is concatenated with the two-dimensional LIBERO gripper state to form the eight-dimensional observation.state. The seven-dimensional action keeps the first six values and transforms the final command with 1 - clip(value, 0, 1), preserving the repository's gripper inversion convention. This is a semantic conversion, not a generic numeric normalization; record it in provenance.

Do not route RLDS/TFDS input, RoboCasa files, or LeRobot version migrations through this sub-skill. Choose the corresponding sibling route at the root. Do not treat a successful file open as proof that the task is convertible: shape, frame alignment, and feature-version checks are required before the writer is started.

For a synthetic smoke case, use a two-frame data/demo_0 fixture with all required arrays and verify only key presence, widths, image dimensions, and the final action component. This gives coverage of the difficult schema path without invoking a converter, codec, Ray, Hub, or simulator.

The standard feature contract is two RGB video streams (agentview_rgb and eye_in_hand_rgb) at 256x256x3, an 8-wide combined state, separate 6-wide end-effector, 7-wide joint, and 2-wide gripper state streams, and a 7-wide action. The canonical defaults are 20 FPS and Franka. Do not infer a different robot or FPS merely from a directory name.

Handoff

Report selected files, skipped filename mismatches, source shape/dtype checks, transformation choices, executor and safety flags, output metadata checks, and whether regeneration was not run. Preserve unresolved optional-dependency or schema gaps explicitly.

Evidence for this route was distilled from the repository's LIBERO README, libero_h5.py, and regenerate_libero_dataset.py; those artifacts are provenance only and are not runtime dependencies.