The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ArrowInvalid
Message: Mismatching child array lengths
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 83, in _generate_tables
pa_table = _recursive_load_arrays(h5, self.info.features, start, end)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 267, in _recursive_load_arrays
arr = _recursive_load_arrays(obj, features[path], start, end)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 288, in _recursive_load_arrays
sarr = pa.StructArray.from_arrays(values, names=keys)
File "pyarrow/array.pxi", line 4385, in pyarrow.lib.StructArray.from_arrays
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: Mismatching child array lengthsNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
EmbodiChain research datasets
Versioned datasets directly usable by EmbodiChain research workflows. The repository groups releases by research type and method, with stable manifests and explicit per-artifact licenses. Dataset index.
Neural dynamics
| Dataset | Relative directory | Training transitions | Validation/test trajectories |
|---|---|---|---|
| NeRD Cartpole / Newton | neural_dynamics/nerd/cartpole/v1/ |
1,024,000 | 512 / 512 |
| NeRD Ant / Newton | neural_dynamics/nerd/ant/v1/ |
1,024,000 | 512 / 512 |
Each artifact has 10,240 training trajectories of 100 steps, a directly loadable HDF5 manifest and card, and Apache-2.0 LICENSE/NOTICE. State/contact/action fields and relative shard checksums are defined in its manifest. These data are generated by current Newton Featherstone, with the NeRD reference scene profile, not by the official historical Warp teacher. No training logs are hosted here.
Use snapshot_download(..., repo_type="dataset") for the desired artifact path and the EmbodiChain DynamicsWindowDataset loader. See each version's README for code and coordinate/physics contracts. The dataset is approximately the repository example's 1M training scale; it is smaller than the paper's stated 10M scale.
Adding another research dataset
Create <research-type>/<method>/<name>/<version>/ with a self-contained manifest, relative data paths, explicit splits, a concise README, checksums, provenance/coordinate schema and a version-specific license. Add its entry to index.json. Keep model weights, training histories, simulator binary packages, credentials and machine-specific paths outside the dataset package.
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