Datasets:

jzpeng
/

MsJNeko_so101_prac2

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.

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SO-101 Practice Run TsFile

This dataset is a compact Apache TsFile conversion of MsJNeko/so101_prac2, a LeRobot v2.1 SO-101 robot-manipulation practice run.

Modalities: Time-series and tabular. Numeric actions, robot state, frame timing, and episode/task metadata are stored in TsFile. Camera video remains in the source Hugging Face dataset.

Source dataset

Author/uploader: MsJNeko
License: Apache-2.0
Task: Pick up a bottle and put it back down.
Robot: so101; LeRobot codebase v2.1; sampling rate 30 FPS
Source page: https://huggingface.co/datasets/MsJNeko/so101_prac2
Scale: 50 episodes, 24,323 frames, 1 task, 1 source chunk
Source Parquet: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
Source video: videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4
Video stream: observation.images.phone (50 MP4 files, about 339 MB)

Converted files

TsFile: data/MsJNeko_so101_prac2.tsfile
Table: MsJNeko_so101_prac2
Rows: 24,323
Time precision: milliseconds
meta/ is mirrored from the source; meta/info.json documents the TsFile mapping.

Schema and encoding

Time = round(timestamp * 1000) milliseconds, restarting at zero per episode.

TAG columns (TsFile table/device identity): episode_index, task_index.

FIELD columns: frame_index (INT64), sample_index (INT64, renamed from index), action_0 ... action_5 (FLOAT), and observation_state_0 ... observation_state_5 (FLOAT).

The two vector columns are flattened from action[6] and observation.state[6], preserving the source prefixes (. becomes _). The redundant source timestamp field is dropped after Time synthesis; no rows or numeric dimensions are dropped. The compact writer uses GORILLA + LZ4 for FLOAT/DOUBLE and TS_2DIFF + LZ4 for INT32/INT64 and Time.

Videos

Videos are not uploaded with this conversion. They remain in the original videos/ tree under videos/chunk-000/observation.images.phone/. Numeric rows align to video frames through episode_index and frame_index.

Validation and usage

The local validation report confirms a non-empty TsFile and row-count equality with the staged Parquet: 24,323 rows.

from tsfile import TsFileReader
reader = TsFileReader("data/MsJNeko_so101_prac2.tsfile")
with reader.query_table("MsJNeko_so101_prac2", ["episode_index", "task_index", "frame_index", "action_0"], batch_size=65536) as result:
    print(result.read_arrow_batch().to_pandas().head())

Downloads last month: 5

Total file size:

498 kB