Datasets:

jzpeng
/

siyavash_so101_test

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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SO101 Test TsFile

Apache TsFile edition of siyavash/so101_test, a LeRobot v2.1 SO101 dataset for grasping a servo box and putting it on the zirlivani. The numeric trajectories are stored in one table-model TsFile.

Source and attribution

Original author, repository owner, and uploader: siyavash. The source card does not provide a separate personal name.
License: Apache-2.0.
The source card does not provide a homepage, paper, or completed BibTeX citation.
Split: train; 50 episodes; 22,350 frame rows; one task; 30 FPS; 50 source Parquet shards.
Task 0: Grasp a servo box and put it on the zirlivani.

Data layout

The table is siyavash_so101_test and contains 22,350 rows across 50 TAG devices. The source Parquet shards total 1,164,037 bytes; the TsFile is 393,788 bytes (33.8% of the source Parquet size).

Column	TsFile role	Type	Meaning
`Time`	TIME	INT64 milliseconds	`round(timestamp * 1000)`, restarting at zero per episode
`episode_index`	TAG	STRING from source INT64	Source episode identity
`task_index`	TAG	STRING from source INT64	Source task identity
`frame_index`	FIELD	INT64	Frame position within the episode
`sample_index`	FIELD	INT64	Source `index`, renamed for clarity
`action_0` ... `action_5`	FIELD	FLOAT	Flattened `action[6]`
`observation_state_0` ... `observation_state_5`	FIELD	FLOAT	Flattened `observation.state[6]`

timestamp is not retained as a separate FIELD because it is represented by Time / 1000 seconds. The vector column names preserve their source prefixes, with dots changed to underscores. No trajectory row, episode, task, action dimension, or state dimension is removed.

Encoding and compression

TIME, INT32, and INT64: TS_2DIFF + LZ4
FLOAT and DOUBLE: GORILLA + LZ4
BOOLEAN, when present: RLE + LZ4
TAG values: TsFile table-model device/tag storage

Videos and alignment

The 100 source AV1 videos are not included here. They remain under videos/chunk-000 in the original repository:

observation.images.laptop: 50 files, 241,192,699 bytes
observation.images.wrist: 50 files, 128,928,559 bytes

The source template is videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4. Use episode_index and frame_index to align each numeric row with both 30 FPS video streams.

Read example

from tsfile import TsFileReader

reader = TsFileReader("data/siyavash_so101_test.tsfile")
with reader.query_table(
    "siyavash_so101_test",
    ["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()

Downloads last month: 28

Total file size:

516 kB