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: TypeError
Message: Couldn't cast array of type int64 to null
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 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2152, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2014, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type int64 to nullNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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pc_gpu_ram — 200 demonstrations (assembly.pc_gpu_ram.franka.osc)
Generated by the CoSiGen data_gen ladder (gen_o50_v3): {'scene': 5, 'strategy': 20, 'phase': 50} -> physics set of
200 episodes, every one replay-verified (200/200): the recorded
actions, fed back open-loop into the rebuilt world under the recorded control law, reproduce the
task's success. Seed solution: CoSiGen_Solutions/assembly/pc_gpu_ram/franka/osc@8d74c75.
- scenes/cells: 5 scene variants, 15 cells (scene/strategy[/phase]); sources under
scenes/ - sim dt 0.004166666666666667 s, decimation 16; controller FrankaRobot with leaves [{'class': 'OperationalSpaceController', 'control_period': 16}, {'class': 'JointController', 'control_period': 16}]
- episode length: 570 / 2400 / 2850 control steps (min / median / max)
- renders: 600/600 items = 3 looks x 200 episodes; cameras ['front', 'high', 'wrist']
- size: 19.4 GB
Layout
physics_set.json the 200 delivered episodes (paths below); scene/strategy/phase_set.json = the nested rungs
episodes.jsonl one row per episode (path, cell, steps, seed, replay_verified, physical_params, videos, ...)
render_manifest.json per (episode, look) render record
data/<batch>/ep_NNNN/
meta.json cell, seed, steps, success_step, controller (the law the episode ran under), controller_changes, noise, replay verdict
traj.npz per-step arrays, one row per control step, state recorded BEFORE the step:
['action', 'robot/controller/0/prev_action', 'robot/joint_effort_target', 'robot/joint_pos', 'robot/joint_pos_target', 'robot/joint_vel', 'robot/root', 'scene/card', 'scene/case', 'scene/grasp_held', 'scene/grasp_rel_p', 'scene/grasp_rel_q', 'scene/ram_0', 'scene/ram_1']
`action` (8-dim) is the commanded action at that step
imgs/<camera>.mp4, <camera>_draw1.mp4, <camera>_draw2.mp4 the episode rendered under each look
imgs/render_<camera>[_drawN].json render parameters of that video
Reading an episode
import json, numpy as np
meta = json.load(open("data/<batch>/ep_0000/meta.json"))
tr = dict(np.load("data/<batch>/ep_0000/traj.npz"))
tr["action"].shape, tr["robot/joint_pos"].shape # (T, 8), (T, n_joints)
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