The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Dataset 'names' has length 5 but expected 7
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/hdf5/hdf5.py", line 76, in _generate_tables
num_rows = _check_dataset_lengths(h5, self.info.features)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 355, in _check_dataset_lengths
raise ValueError(f"Dataset '{path}' has length {dset.shape[0]} but expected {num_rows}")
ValueError: Dataset 'names' has length 5 but expected 7Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
3DWM training datasets
Demonstration data converted to the point-cloud dataset format used by the 3DWM
world model, i.e. the layout its maniskill loader expects:
<dataset>/<split>/<scenario>/demo_N/
phases_dict.pkl {'cannonical_points': {geom: (P, 3)}} canonical local-frame points
0.h5 .. (T-1).h5 transforms/<geom> (4, 4), action (7,), names, tcp_pose (7,)
Points are stored once per geom in its local frame, with a 4x4 local-to-world transform per timestep, which gives point-to-point correspondence across time, clean part segmentation and complete surfaces. Velocity features are computed by differencing corresponding points, so these are not sensor point clouds and a raw depth capture cannot be substituted.
Contents
StackCube-v1-demos/— ManiSkill 3 StackCube, unpacked per-demo directories.Franka-pickplace-1000demos-v2.tar.gz— 74 MB, md523decfb43157934b6a4cfa1871dac1af. kinder MuJoCoFrankaPickPlace3D-o1: 1000 train + 10 test demos, 111,181 files, 1.3 GB unpacked. Shipped as a tarball because ~110k files of ~12 KB each is a poor fit for per-file hosting.
hf download Flashkernel/3dwm-kinder-data Franka-pickplace-1000demos-v2.tar.gz \
--repo-type dataset --local-dir .
tar xzf Franka-pickplace-1000demos-v2.tar.gz -C data/
Sanity check after extracting — part names, order and counts must match what the
training config lists as env_keys:
import pickle
d = pickle.load(open('data/Franka-pickplace-1000demos-v2/train/pickplace/demo_0/phases_dict.pkl','rb'))
pts = d['cannonical_points']
print(list(pts.keys()))
print([v.shape[0] for v in pts.values()]) # [300, 38,38,38,38, 37,37,37,37]
Franka pickplace provenance
Converted from the raw demos with
data_generation/kindergarden/convert_sweep_to_3dwm.py --pads 300 --cube 300,
which selects the gripper pads and the cube and sets their point budgets. Actions
are normalized with pos_scale=0.1 and rot_scale=-0.1 (note the sign) and
clipped to [-1, 1]; real end-effector motion is ~14 mm per step.
Earlier stages of the chain — the raw kindergarden demo pickles and the packed
canonical HDF5 — are under franka_pickplace/ in
Flashkernel/Kinder-worldmodel.
The world model trained on this data is at
Flashkernel/3dwm-franka-pickplace-mppi,
whose card documents which kindergarden commit the environment must be pinned to
(it matters, and getting it wrong fails silently).
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