The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to number in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
WeightSorting V6 / ForcebenchmarkPandaWeightSorting-v2
This release contains the 1,000 successful, physically paired demonstrations used for the 100k-step diffusion-policy experiments. There are 500 scene pairs: one light and one heavy rollout per scene. The task uses four masses (0.2, 0.4, 0.8, and 1.0 kg), balanced at 250 episodes each. The pair-disjoint split has 450 training pairs and 50 validation pairs. The reported 100k training jobs used all 500 pairs; the split is supplied for future analysis.
Dataset: HanLinqi/ForceBenchmark-WeightSorting-v6.
Files
| HF path | Contents | SHA-256 of H5 |
|---|---|---|
planning_data/forcebenchmarkpandaweightsorting_v2/trajectory_rgb.h5 |
18D state (qpos+qvel), RGB, action, causal wrist wrench, auxiliary labels |
e17010001cb5e47b64e84b93b9b371f45c96015bf74a2c73265459b68920227b |
planning_data_26d/forcebenchmarkpandaweightsorting_v2/trajectory_rgb.h5 |
Same rollouts with 26D state (qpos+qvel+TCP+gripper) |
1c10151e66cf3f8aadd9ddc4b8d5e0c6637547f36b15564a20f842ff8fe1f5d4 |
Each H5 has a matching trajectory_rgb.json. The state18 directory also has
pair_splits.json, decision_windows.json, and provenance/ with the raw
collection summary, audit and gate. phase_id, stage_id, scene
pair IDs, mass and route labels are auxiliary targets or audit metadata; they
are not policy observations. The raw audit state is not in either H5.
Task and data construction
Import task_force.forcebenchmark_panda_weight_sorting_v2 to register the
environment. The collector is
task_force/scripts/generate_weight_sorting_v2_physical_pairs_v6.py; its
campaign driver, audit, merge and conversion scripts are in task_force/scripts.
See task_force/docs/weightsorting_v6_physical_pairs.md for the full task
definition, collection protocol and physical assumptions.
The V2 action is a 7D increment to a persistent Cartesian reference. It is
incompatible with V1's instantaneous-TCP action semantics. The task uses an
ideal rigid grasp latch after physical finger contact and finite-precision
synthetic policy sensors; it does not represent ordinary friction-only
pinching or raw simulator proprioception. The same online sensors and
controller must be used for force and no-force policies. Online wrist wrench
settings are force_torque_source="incoming_joint",
force_substep_mean=True, and zero_force_on_reset=True.
Collection audited exact shared pre-decision actions and reference positions, causal wrench, sensor replay, physical pair separation and five-fold scene-grouped leakage probes. Collection accepted 1,000 episodes/500 pairs. The separate pilot used evaluation seeds 0–4, 20 episodes per seed. For each trained experiment, use five evaluation seeds ×20 episodes per seed, with evaluation scenes separate from collection scenes.
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