Dataset Viewer
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 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 Test Trimmed TsFile

This Apache TsFile dataset converts the numeric trajectories from arulloomba/so100_test_trimmed, a LeRobot v2.1 SO100 dataset for the task "Grasp a block and put it in the bin."

Source Dataset

  • Repository owner and uploader: arulloomba
  • License: Apache-2.0
  • Robot: so100; LeRobot codebase version: v2.1
  • Split: train; sampling rate: 30 fps
  • Numeric data: 50 episode Parquet files, 600 rows each, 30,000 rows total
  • Task count: 1; task index 0: "Grasp a block and put it in the bin."
  • Source frame layout: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
  • Source video layout: videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4
  • Paper/citation: the source card supplies neither a paper nor a completed citation

The source meta/info.json and meta/episodes.jsonl retain pre-trim counters totaling 37,316 frames. The actual Parquet snapshot contains 30,000 rows, so the TsFile and converted meta/info.json use the actual Parquet row count.

TsFile Data

  • File: data/arulloomba_so100_test_trimmed_train.tsfile
  • Table: arulloomba_so100_test_trimmed_train
  • Rows/devices: 30,000 rows across 50 episode/task TAG combinations
  • Size: 0.29 MiB
  • Time: round(timestamp * 1000) milliseconds, ranging from 0 to 19,967 ms in each episode

Schema roles:

Source TsFile columns Role Type
timestamp Time TIME INT64 milliseconds
episode_index episode_index TAG STRING device segment
task_index task_index TAG STRING device segment
frame_index frame_index FIELD INT64
index sample_index FIELD INT64
action[6] action_0 ... action_5 FIELD FLOAT
observation.state[6] observation_state_0 ... observation_state_5 FIELD FLOAT

Vector names retain the source prefix with . replaced by _. The six action and state dimensions are, in order, main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, and main_gripper. The source timestamp field is omitted after Time synthesis because it equals Time / 1000; every numeric row and every other numeric dimension is retained.

Encoding uses GORILLA + LZ4 for FLOAT/DOUBLE, TS_2DIFF + LZ4 for INT32/INT64 and Time, and RLE + LZ4 for BOOLEAN fields. The dataset has no BOOLEAN field. episode_index and task_index use the TsFile table-model TAG/device mechanism.

Videos

Videos are not included here. They remain in the source repository as 100 MP4 files totaling 354,247,499 bytes, split into two 50-file camera streams:

The upstream spelling detatched_arm is preserved. The numeric rows align to the first 600 frames of each episode video through episode_index and frame_index.

Read Example

from tsfile import TsFileReader

reader = TsFileReader("data/arulloomba_so100_test_trimmed_train.tsfile")
columns = ["episode_index", "task_index", "frame_index", "action_0", "observation_state_0"]
with reader.query_table("arulloomba_so100_test_trimmed_train", columns, batch_size=65536) as result:
    print(result.read_arrow_batch().to_pandas().head())
reader.close()

Attribution

The source card identifies the Hugging Face repository owner/uploader as arulloomba and provides no separate formal author, paper, or citation. Cite the original dataset and its owner when using this conversion.

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