The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
attempt_id: string
family_id: string
initial_observation_accepted: bool
intrusion_side: string
note: string
pose_id: string
row_sha256: string
schema_version: string
selected_seed: struct<seed_u32: int64, seed_u64: double>
child 0, seed_u32: int64
child 1, seed_u64: double
source_format: string
episode_count: int64
rows: list<item: struct<attempt_id: string, cell: string, converted_episode_sha256: string, episode_index: (... 163 chars omitted)
child 0, item: struct<attempt_id: string, cell: string, converted_episode_sha256: string, episode_index: int64, fam (... 151 chars omitted)
child 0, attempt_id: string
child 1, cell: string
child 2, converted_episode_sha256: string
child 3, episode_index: int64
child 4, family_id: string
child 5, intrusion_side: string
child 6, pose_id: string
child 7, row_dir: string
child 8, row_sha256: string
child 9, source_row_dir: string
child 10, source_trajectory_sha256: string
to
{'episode_count': Value('int64'), 'rows': List({'attempt_id': Value('string'), 'cell': Value('string'), 'converted_episode_sha256': Value('string'), 'episode_index': Value('int64'), 'family_id': Value('string'), 'intrusion_side': Value('string'), 'pose_id': Value('string'), 'row_dir': Value('string'), 'row_sha256': Value('string'), 'source_row_dir': Value('string'), 'source_trajectory_sha256': Value('string')}), 'schema_version': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
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 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
attempt_id: string
family_id: string
initial_observation_accepted: bool
intrusion_side: string
note: string
pose_id: string
row_sha256: string
schema_version: string
selected_seed: struct<seed_u32: int64, seed_u64: double>
child 0, seed_u32: int64
child 1, seed_u64: double
source_format: string
episode_count: int64
rows: list<item: struct<attempt_id: string, cell: string, converted_episode_sha256: string, episode_index: (... 163 chars omitted)
child 0, item: struct<attempt_id: string, cell: string, converted_episode_sha256: string, episode_index: int64, fam (... 151 chars omitted)
child 0, attempt_id: string
child 1, cell: string
child 2, converted_episode_sha256: string
child 3, episode_index: int64
child 4, family_id: string
child 5, intrusion_side: string
child 6, pose_id: string
child 7, row_dir: string
child 8, row_sha256: string
child 9, source_row_dir: string
child 10, source_trajectory_sha256: string
to
{'episode_count': Value('int64'), 'rows': List({'attempt_id': Value('string'), 'cell': Value('string'), 'converted_episode_sha256': Value('string'), 'episode_index': Value('int64'), 'family_id': Value('string'), 'intrusion_side': Value('string'), 'pose_id': Value('string'), 'row_dir': Value('string'), 'row_sha256': Value('string'), 'source_row_dir': Value('string'), 'source_trajectory_sha256': Value('string')}), 'schema_version': 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.
PACT place V10.10 episodes
This dataset contains 144 retained expert episodes from the V10.10 four-object static-pendant pick-and-place environment. The collection covers 24 registered cells (4 clutter families × 2 intrusion sides × 3 pendant poses), with six retained rows per cell.
Layout
Rows are organized under:
pact_place_corridor_v10_10/
manifest.json
rows/
000_<source-row-hash>/
episode_00000000_sensors_depth8_heatmap.mp4
episode_00000000_wrist_camera.mp4
episode_00000000_wrist_camera_depth.mp4
initial_observation_accepted.json
result.json
trajectory.h5
trajectory.json
The numeric prefix is the stable index of the corresponding converted training
row. The suffix is the source V10.10 row identifier. manifest.json binds each
row to its source trajectory SHA-256, converted-episode SHA-256, cell, family,
side, and pendant pose. The converted ACT-style files used during training
are not duplicated at the repository root; their SHA-256 values remain in the
manifest for lineage, and the raw rows can be converted with the project
tooling when needed.
trajectory.h5 is the original V10.10 raw trajectory (the traj_0 recording
with actions, observations, scene metadata, environment state, rewards, and
termination flags). trajectory.json is a compact, explicitly derived index
of that HDF5 file; it is not a duplicate full step-by-step JSON trajectory.
initial_observation_accepted.json is likewise a compact derived boundary
index. The V10.10 collector did not emit the V5 recovery-format sidecars, so
these files do not claim telemetry that was not recorded.
The V10.10 scene has four live household objects (two bottles and two plates) and a compiled-static two-lobe pendant. The pendant has no joint, free joint, or mocap degree of freedom. The row videos are the original source-row renders.
These are data artifacts. Environment code and deterministic scene/config definitions are published separately in Jdvakil/molmospaces#2.
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