Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
tsfile.exceptions.FileOpenError: 28:
The above exception was the direct cause of the following exception:
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/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
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 71, 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.
Distribute Chocolate Pies (TsFile)
Source: skkuprism/distribute_chocolatepies, revision c64b143fe95db04814b0da22ad3722cb5aa4b0dd.
This is a numeric time-series conversion of the LeRobot dataset for task distribute chocolate pies to each plate. The source metadata records an so101_follower robot and includes high-level skill state alongside robot observations and actions.
- Modalities: Time-series
- Split: train
- Sampling rate: 30 fps
- Scale: 47 episodes, 20,622 frames, 47 source frame Parquet files
- Converted layout: 1 TsFile with 20,622 rows
TsFile schema
The table is distribute_chocolatepies_train.
| Role | Columns | Representation |
|---|---|---|
| Time | Time |
INT64 milliseconds; round(timestamp * 1000) |
| TAG | episode_index, task_index |
Source episode and task dimensions |
| FIELD | frame_index, sample_index |
Source scalar frame identifiers |
| FIELD | observation_gripper_binary, skill_type, skill_progress, skill_goal_position_gripper |
Scalar observation and skill fields |
| FIELD | observation_state_0 ... _5, action_0 ... _5 |
Flattened 6-element FLOAT state and action vectors |
| FIELD | observation_ee_pos_robot_xyzrpy_0 ... _5 |
6 FLOAT end-effector pose values |
| FIELD | skill_goal_position_joint_0 ... _5 |
6 FLOAT joint goal values |
| FIELD | skill_goal_position_world_xyzrpy_0 ... _5 |
6 FLOAT world-frame goal values |
| FIELD | skill_goal_position_robot_xyzrpy_0 ... _5 |
6 FLOAT robot-frame goal values |
Conversion notes
- Dots in scalar source names become underscores, including
skill.typetoskill_typeandskill.progresstoskill_progress. - The source
timestampis omitted because it is represented byTimein milliseconds. - The source
indexis renamed tosample_index. - Every numeric vector element, every skill field, and all 20,622 source rows are retained.
- Source metadata is mirrored under
meta/; itsdata_pathpoints to the TsFile and records the conversion mapping. - Videos are not downloaded or uploaded. They remain in the original dataset videos, where they preserve frame alignment with the numeric rows.
Reading
from tsfile import TsFileReader
path = "data/distribute_chocolatepies_train.tsfile"
reader = TsFileReader(path)
table = "distribute_chocolatepies_train"
columns = ["episode_index", "task_index", "frame_index", "skill_type", "skill_progress"]
with reader.query_table(table, columns, batch_size=1024) as result:
batch = result.read_arrow_batch()
print(batch.to_pandas().head())
Source & license
The pinned source metadata does not declare a license, task category, paper, or citation. No license or task category is asserted here; users should review the source repository before reuse.
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