The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 342, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, 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 4645, 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 2866, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3073, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2581, in _iter_arrow
yield from 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/json/json.py", line 345, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 291, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
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: JSON parse error: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
DVIDIA arm interfaces v0.1
Three native CPU simulation interfaces: PiPER, SO-101, and UR5e with Robotiq 2F-85.
54 fixed unloaded mechanics attempts were numerically valid. This is not 54 successful manipulation tasks. All traces are retained: 21,654 state rows, 1,260 commands and 21 offline compute-budget exceedances. An independent audit reconstructed 648 RMS/max values without a mismatch. Deterministic repeats measure timing variability, not unseen-task generalization.
Arm error is in radians. Each gripper retains its actual command units: PiPER single-finger metres, SO-101 hinge radians, and Robotiq native 0–255. These are not interchangeable jaw gaps or calibrated force readings. Terminal-frame tracking is not calibrated fingertip accuracy. The interactive shared host is not a real-time test rig.
Run locally
The 0.1.3.dev3 preview provides dvidia-arm list, describe, check, install, inspect, run, benchmark, task-template and assess-task.
Install the preview · Source and commands · Research · Skillspaces
Only the existing PiPER learned block policy has a runner in this installer. Its frozen held-out placement result remains 5/12; this dataset does not train a new model. The policy is rejected on the other arms. Setup needs network access; local simulation uses CPU and verified assets without a CUDA requirement. Hardware minimums and physical transfer remain unqualified.
Evidence
arm-interfaces-v01-evidence.zip: every native trace, commands, results, fixed protocol, source snapshots, independent auditor, portable verifier and upstream notices.summary.json: all 27 condition summaries and measurement scope.independent-audit.json: read-only numerical and digest verification.installation-smoke.json: isolated installed-wheel validation; one selected simulation example passed, but is not a new held-out benchmark. Its full control-step compute p95 was 34.924 ms with 179/1,000 nominal 20 ms budgets exceeded on the shared host; no real-time qualification.
Extract the evidence ZIP and run its verify.py to check the inventory and numerical audit. native_step_compute_s measures the complete observed-step wrapper, including snapshots and reference forward kinematics; it is not isolated physics cost.
The task-feasibility command is a data-only planning assessment. Caller-declared reach, object width, mass/friction uncertainty, force budget, calibration, freshness and test-lift status produce blocked/probe/test-lift/ready-for-simulated-transport decisions. It performs no sensing or motion and is not integrated into the learned controller.
Rights and limits
Original DVIDIA tooling and synthetic records are MIT. The archive preserves distinct upstream PiPER MIT, SO-101 Apache-2.0, UR5e BSD-3-Clause and Robotiq BSD-2-Clause notices. No raw human footage, downloaded robot meshes, credentials or new learned weights are included. There is no hardware adapter, physical skill qualification or automatic cross-arm transfer.
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