Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'test' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: FileNotFoundError
Message: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7f15a3674b90>'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from 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/xml/xml.py", line 67, in _generate_tables
with open(file, encoding=self.config.encoding, errors=self.config.encoding_errors) as f:
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 967, in xopen
return open(main_hop, mode, *args, **kwargs)
FileNotFoundError: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7f15a3674b90>'Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
RoboVerse Data
Robot Asset Dependency Rules
These rules apply to robot assets under robots/. They are meant for robot description packages and composed robot models, not for all dataset assets.
- Keep shared upstream robot description packages as sibling directories under
robots/, and treat those directories as authoritative. A composed robot should reference them with repo-relative paths instead of copying their meshes into its own folder. - Keep each composed robot directory minimal. It should contain only the public entry files such as
.urdf,.xml/MJCF, and.usd, plus local meshes that are genuinely modified for that composition, such as adapters, mounts, trimmed links, or replacement collision pieces. - Do not keep simulator-converter scratch output, legacy variants, nested generated packages, cache folders, temporary USD layers, or duplicated upstream packages in the composed robot directory unless they are the supported public artifact. Stale
*_generated/,*_bimanual_*, copied upstream robot folders, and obsolete hand-description folders should be removed before publishing. - Use portable repo-relative references only. Robot description files must not contain absolute paths, user home directories, machine names,
/tmppaths, server paths, or references to obsolete dependency packages. - Robot USD files should either be standalone, with no external sublayers/assets, or should reference only stable repo-relative dependencies that are part of the published robot package. If a USD is advertised as standalone, verify that it has no unresolved dependencies, external asset attributes, or stale layer metadata.
- Before publishing a robot package, verify the directory from the consumer's point of view: parse URDF/MJCF mesh references, confirm every referenced file exists in the dataset, inspect USD dependencies with USD/PXR tools, grep for forbidden path fragments, and make sure the remote repository contains exactly the intended robot files with no stale leftovers.
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