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.
SO101 Pen Touch Test 1 TsFile
This is an Apache TsFile conversion of bjb7/so101_pen_touch_test_1 (https://huggingface.co/datasets/bjb7/so101_pen_touch_test_1), a LeRobot v2.1 SO101 dataset for Touch the pen. Numeric trajectory data are in one table-model TsFile; videos remain in the original repository.
Source and provenance
- Original author/uploader: Brian Blankenau (bjb7), https://huggingface.co/bjb7
- License: Apache-2.0; no paper or completed citation is supplied by the source card.
- Robot: so101; LeRobot codebase: v2.1; split: train; sampling rate: 30 fps.
- 100 episodes, 21,648 frame rows, one task (task_index=0: Touch the pen.), 100 source Parquet shards, and 200 source MP4 files.
- Source frame path: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
Converted files
- TsFile: data/so101_pen_touch_test_1.tsfile
- Table: so101_pen_touch_test_1
- Rows: 21,648; devices/episodes: 100
- Original source Parquet bytes (100 shards): 1,105,996; TsFile bytes: 337,278 (30.50% of source, 69.50% smaller).
- The normalized single-file staging Parquet is 327,182 bytes; the small 10,096-byte TsFile difference is table/TAG metadata overhead, not duplicated measurements.
Schema
Time is INT64 milliseconds computed as round(timestamp * 1000) and restarts from zero within each episode. The source timestamp is dropped because it equals Time / 1000 seconds.
TAG/device columns:
- episode_index
- task_index
FIELD columns:
- frame_index
- sample_index
- action_0
- action_1
- action_2
- action_3
- action_4
- action_5
- observation_state_0
- observation_state_1
- observation_state_2
- observation_state_3
- observation_state_4
- observation_state_5
Vector flattening preserves source names: action[6] becomes action_0 ... action_5; observation.state[6] becomes observation_state_0 ... observation_state_5 (FLOAT32). index is renamed to sample_index; frame_index is retained.
Encoding and compression
The generated schema was verified after writing. The configured compact profile is:
- time_encoding: TS_2DIFF
- time_compression: LZ4
- float_encoding: GORILLA
- float_compression: LZ4
- double_encoding: GORILLA
- double_compression: LZ4
- int32_encoding: TS_2DIFF
- int32_compression: LZ4
- int64_encoding: TS_2DIFF
- int64_compression: LZ4
- boolean_encoding: RLE
- boolean_compression: LZ4
- tag_storage: TsFile table-model device/tag columns
TAG values use TsFile table-model device/tag storage. No numeric trajectory rows or state/action dimensions are dropped.
Videos and alignment
Videos are not included in this TsFile repository. The original Hugging Face dataset keeps 200 MP4 files (100 per stream, about 562,260,333 bytes / 536.21 MiB):
- observation.images.camera_2: https://huggingface.co/datasets/bjb7/so101_pen_touch_test_1/tree/main/videos/chunk-000/observation.images.camera_2
- observation.images.camera_4: https://huggingface.co/datasets/bjb7/so101_pen_touch_test_1/tree/main/videos/chunk-000/observation.images.camera_4 Each episode numeric rows remain frame-aligned through episode_index and frame_index.
Validation
Local validation status: PASS. Staged Parquet and TsFile metadata both contain 21,648 rows; the schema exposes 14 FIELD columns and 2 TAG columns. The detailed JSON/Markdown report remains in the local workdir and is not part of the upload set.
Minimal read example
from tsfile import TsFileReader
reader = TsFileReader("data/so101_pen_touch_test_1.tsfile")
with reader.query_table("so101_pen_touch_test_1", ["episode_index", "task_index", "frame_index", "sample_index", "action_0", "observation_state_0"], batch_size=1024) as result:
batch = result.read_arrow_batch()
print(batch.to_pandas().head())
reader.close()
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