Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
schema_version: int64
created_at: string
source_sha256: string
source_size_bytes: int64
policy: string
num_silos: int64
total_episodes: int64
total_frames: int64
silos: list<item: struct<silo_index: int64, sha256: string, source_episode_indices: list<item: int64>, epis (... 97 chars omitted)
child 0, item: struct<silo_index: int64, sha256: string, source_episode_indices: list<item: int64>, episode_count: (... 85 chars omitted)
child 0, silo_index: int64
child 1, sha256: string
child 2, source_episode_indices: list<item: int64>
child 0, item: int64
child 3, episode_count: int64
child 4, frame_count: int64
child 5, filename: string
child 6, hf_repo_id: string
child 7, hf_file_ref: string
source_repo_id: string
source_file: string
source_hf_file_ref: string
source_dataset: string
source_revision: string
heldout_split_policy: struct<policy: string, purpose: string, silos: list<item: struct<participant_id: string, heldout_sou (... 104 chars omitted)
child 0, policy: string
child 1, purpose: string
child 2, silos: list<item: struct<participant_id: string, heldout_source_episode_indices: list<item: int64>, train_s (... 42 chars omitted)
child 0, item: struct<participant_id: string, heldout_source_episode_indices: list<item: int64>, train_source_episo (... 30 chars omitted)
child 0, participant_id: string
child 1, heldout_source_episode_indices: list<item: int64>
child 0, item: int64
child 2, train_source_episode_indices: list<item: int64>
child 0, item: int64
child 3, note: string
blocker: null
min_windows_per_silo: int64
generated_at: string
dataset_repo_id: string
participant_count: int64
window_steps: int64
to
{'schema_version': Value('int64'), 'generated_at': Value('string'), 'window_steps': Value('int64'), 'min_windows_per_silo': Value('int64'), 'participant_count': Value('int64'), 'silos': List({'participant_id': Value('string'), 'data_source': Value('string'), 'data_format': Value('string'), 'episode_count': Value('int64'), 'window_count': Value('int64'), 'dataset_root': Value('string'), 'dataset_commitment_schema_version': Value('int64'), 'hash_algorithm': Value('string'), 'wmcp_version': Value('string'), 'embodiment_ids': List(Value('string')), 'action_spec': {'embodiment_id': Value('string'), 'kind': Value('string'), 'dim': Value('int64'), 'low': List(Value('float64')), 'high': List(Value('float64')), 'num_classes': Value('null'), 'units': List(Value('string')), 'wmcp_version': Value('string')}, 'observation_shape': List(Value('int64')), 'action_shape': List(Value('int64')), 'hf_file_ref': Value('string')}), 'blocker': Value('null'), 'dataset_repo_id': Value('string'), 'source_repo_id': Value('string'), 'source_file': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
schema_version: int64
created_at: string
source_sha256: string
source_size_bytes: int64
policy: string
num_silos: int64
total_episodes: int64
total_frames: int64
silos: list<item: struct<silo_index: int64, sha256: string, source_episode_indices: list<item: int64>, epis (... 97 chars omitted)
child 0, item: struct<silo_index: int64, sha256: string, source_episode_indices: list<item: int64>, episode_count: (... 85 chars omitted)
child 0, silo_index: int64
child 1, sha256: string
child 2, source_episode_indices: list<item: int64>
child 0, item: int64
child 3, episode_count: int64
child 4, frame_count: int64
child 5, filename: string
child 6, hf_repo_id: string
child 7, hf_file_ref: string
source_repo_id: string
source_file: string
source_hf_file_ref: string
source_dataset: string
source_revision: string
heldout_split_policy: struct<policy: string, purpose: string, silos: list<item: struct<participant_id: string, heldout_sou (... 104 chars omitted)
child 0, policy: string
child 1, purpose: string
child 2, silos: list<item: struct<participant_id: string, heldout_source_episode_indices: list<item: int64>, train_s (... 42 chars omitted)
child 0, item: struct<participant_id: string, heldout_source_episode_indices: list<item: int64>, train_source_episo (... 30 chars omitted)
child 0, participant_id: string
child 1, heldout_source_episode_indices: list<item: int64>
child 0, item: int64
child 2, train_source_episode_indices: list<item: int64>
child 0, item: int64
child 3, note: string
blocker: null
min_windows_per_silo: int64
generated_at: string
dataset_repo_id: string
participant_count: int64
window_steps: int64
to
{'schema_version': Value('int64'), 'generated_at': Value('string'), 'window_steps': Value('int64'), 'min_windows_per_silo': Value('int64'), 'participant_count': Value('int64'), 'silos': List({'participant_id': Value('string'), 'data_source': Value('string'), 'data_format': Value('string'), 'episode_count': Value('int64'), 'window_count': Value('int64'), 'dataset_root': Value('string'), 'dataset_commitment_schema_version': Value('int64'), 'hash_algorithm': Value('string'), 'wmcp_version': Value('string'), 'embodiment_ids': List(Value('string')), 'action_spec': {'embodiment_id': Value('string'), 'kind': Value('string'), 'dim': Value('int64'), 'low': List(Value('float64')), 'high': List(Value('float64')), 'num_classes': Value('null'), 'units': List(Value('string')), 'wmcp_version': Value('string')}, 'observation_shape': List(Value('int64')), 'action_shape': List(Value('int64')), 'hf_file_ref': Value('string')}), 'blocker': Value('null'), 'dataset_repo_id': Value('string'), 'source_repo_id': Value('string'), 'source_file': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Lensemble Phase 2 SO-100 Participant Silos
This dataset contains two LeRobot-H5 participant silo files prepared for the Lensemble Phase 2 federated LeWorldModel evidence stream. The source file is abdelstark/so100-pickplace-lewm-ready/svla_so100_pickplace.h5 at Hub revision c210cb2f37b42954d31a17027e142c4cbdc7f7f8; the upstream source dataset recorded inside the HDF5 attrs is lerobot/svla_so100_pickplace at revision 3d6d687a25cdf1565cdf24550814f72d999a861d. The upstream Hub dataset is public, ungated, and tagged license:apache-2.0.
Files
phase2-so100-silo0.h5: source episodes with even episode indices.phase2-so100-silo1.h5: source episodes with odd episode indices.phase2_silo_manifest.json: deterministic split manifest with source/output SHA-256 hashes, selected source episode ids, frame counts, and file refs.phase2_dataset_smoke.json: Lensemble Phase 2 smoke report with participant ids, Merkle roots, action specs, window counts, and first-window tensor shapes.
Split Policy
The split is deterministic episode-level modulo assignment: source episode k goes to silo k % 2. Frames are not duplicated across silos, complete source episodes are preserved, and each output episode_index is remapped to local 0-based ids.
Declared Held-Out Policy
For Phase 2 downstream evaluation (#206), the final local episode in each silo is reserved as held-out data: source episode 48 for phase2-so100-a and source episode 49 for phase2-so100-b. The HDF5 files retain all episodes for traceability; train/eval reports must record whether they honor or intentionally override this declared split.
Smoke Evidence
The smoke gate was run with window_steps=4 after splitting:
phase2-so100-a: 25 episodes, 3149 windows, dataset rootdf4dceed9ee55b95f2827f8b02ec3aa6b86a02421052eb84cfd96b41d7947c0a.phase2-so100-b: 25 episodes, 3210 windows, dataset rootce6a42bab6edbdefd47f53f4cfc306cb4ed3db84d9f8ac8f7fcb2adc103c7b52.
These files contain raw robot observations/actions and are intended to be mounted read-only inside participant trust boundaries for Lensemble HF Jobs. The JSON reports contain only metadata, hashes, scalar counts, and shapes.
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