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zjt24
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so101_teleop_vials_rack_left

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Time-series

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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 66, 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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so101_teleop_vials_rack_left

This dataset is a TsFile conversion of the Hugging Face dataset sreetz-nv/so101_teleop_vials_rack_left. It contains the numeric LeRobot frame data for an SO-101 teleoperation task, stored as one Apache TsFile table.

Source Dataset

Original dataset: sreetz-nv/so101_teleop_vials_rack_left
LeRobot codebase version: v3.0
Robot type: so101_follower
Split: train (0:75)
Scale: 75 episodes, 18,250 frames, 1 task
Sampling rate: 30 fps
Source modalities: tabular time-series data and video

Converted Files

TsFile: data/so101_teleop_vials_rack_left.tsfile
Table name: so101_teleop_vials_rack_left
Rows: 18,250
Time precision: milliseconds
Metadata: meta/ mirrors the source metadata, with meta/info.json updated to describe the TsFile conversion.

Schema

Column	Role	Type	Notes
`Time`	TIME	INT64	`round(timestamp * 1000)` in milliseconds; restarts per episode.
`episode_index`	TAG	INT64	Original source episode index.
`task_index`	TAG	INT64	Original source task index.
`frame_index`	FIELD	INT64	Original source frame index.
`sample_index`	FIELD	INT64	Renamed from source column `index`.
`observation_state_0` ... `observation_state_5`	FIELD	FLOAT	Flattened from source vector column `observation.state`.
`action_0` ... `action_5`	FIELD	FLOAT	Flattened from source vector column `action`.

Conversion Notes

The source timestamp column is used to create Time and is not retained as a separate field, because it equals Time / 1000 seconds.
Vector columns are flattened by preserving the source column prefix, replacing . with _, and appending element indexes.
Source video features observation.images.ego and observation.images.external_D455 are not included in this converted repository. Videos remain in the original dataset under videos/.
The original source data path is data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet; the converted data path is data/so101_teleop_vials_rack_left.tsfile.

Usage

from tsfile import TsFileReader

path = "data/so101_teleop_vials_rack_left.tsfile"
reader = TsFileReader(path)
print(reader.get_all_table_schemas())

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