Datasets:
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 "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.
SO100 LEGO TsFile
This dataset is an Apache TsFile conversion of
aaronsu11/so100_lego, a LeRobot v2.1 SO100
robot-manipulation dataset for grasping a LEGO block and placing it on a plate.
It contains numeric trajectories, timing, and episode/task tags. Videos remain
in the original Hugging Face repository.
Source Dataset and Attribution
- Original dataset:
aaronsu11/so100_lego - Original author, repository owner, uploader, and sole commit author:
Aaron Su (
aaronsu11) - License: Apache-2.0
- Task: "Grasp a lego block and put it on the plate."
- Robot:
so100; LeRobot version:v2.1 - Split:
train; sampling rate: 30 fps - Scale: 100 episodes, 55,617 frames, 1 task
- Source shards: 100 Parquet files totaling 2,835,956 bytes
- Source frame layout:
data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet - Paper, external homepage, and completed citation: not provided by the source card.
The source README embeds an older 20-episode copy of meta/info.json, and
meta/stats.json contains stale ranges from an earlier partial snapshot. The
current meta/info.json, 100 source Parquet files, meta/episodes.jsonl, and
the pinned repository tree consistently describe the 100-episode dataset and
are authoritative for this conversion.
Schema and Mapping
Time = round(timestamp * 1000) milliseconds. Time starts at zero and is
strictly increasing inside every episode. The source timestamp is dropped
afterward because it is represented by Time / 1000 seconds at the selected
precision.
| TsFile column | Role | Type | Source mapping |
|---|---|---|---|
Time |
TIME | TIMESTAMP | round(timestamp * 1000) ms |
episode_index |
TAG | STRING | Original INT64 episode index |
task_index |
TAG | STRING | Original INT64 task index |
frame_index |
FIELD | INT64 | Preserved |
sample_index |
FIELD | INT64 | Renamed from index |
action_0 ... action_5 |
FIELD | FLOAT | Flattened from action[6] |
observation_state_0 ... observation_state_5 |
FIELD | FLOAT | Flattened from observation.state[6] |
The six vector dimensions are main_shoulder_pan, main_shoulder_lift,
main_elbow_flex, main_wrist_flex, main_wrist_roll, and main_gripper.
Dots in source names are replaced by underscores. No numeric row, episode,
task, state dimension, or action dimension is dropped.
Encodings and Compression
- FLOAT/DOUBLE: GORILLA + LZ4
- INT32/INT64: TS_2DIFF + LZ4
- Time: TS_2DIFF + LZ4
- BOOLEAN: RLE + LZ4 (the source contains no BOOLEAN field)
- TAG: TsFile table/device TAG storage
The physical table schema, every field codec, TAG roles, and all 55,617 rows were read back with the Apache TsFile Java API.
Videos
Videos are not included in this TsFile repository. The pinned source contains 200 frame-aligned AV1 MP4 files (1,341,588,267 bytes), 640x480 at 30 fps with no audio, in two streams with 100 episode files each:
The source layout is
videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4.
Use episode_index, frame_index, and meta/episodes.jsonl to align numeric
rows with the original video frames.
Minimal Read Example
from tsfile import TsFileReader
reader = TsFileReader("data/aaronsu11_so100_lego.tsfile")
with reader.query_table(
"aaronsu11_so100_lego",
["episode_index", "task_index", "frame_index", "sample_index",
"action_0", "observation_state_0"],
batch_size=65536,
) as result:
batch = result.read_arrow_batch()
print(batch.to_pandas().head())
reader.close()
Citation
The source card provides no paper or completed citation. Cite the original
Hugging Face dataset and Aaron Su (aaronsu11) when using this conversion.
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