Datasets:

THULab
/

so101_single_arrange_yrpblock_top2bottom

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 68, 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 Single Arrange YRP Block Top2Bottom (TsFile)

Apache TsFile version of skkuprism/SO101-single-arrange_YRPblock_top2bottom.

The source dataset is a LeRobot v3.0 SO-101 follower robot dataset. Its original dataset card does not declare a license. This repository stores the numeric time-series features as Apache TsFile and keeps visual streams in the original Hugging Face dataset.

Modalities: Time-series. The converted table includes robot state/action, end-effector pose, gripper state, skill metadata, task index, frame metadata, and episode tags.

Source Dataset

Original dataset: skkuprism/SO101-single-arrange_YRPblock_top2bottom
Codebase version: LeRobot v3.0
Robot type: so101_follower
Split: train (0:30)
Episodes: 30
Frames: 25,478
Sampling rate: 30 fps
Tasks: 1
Source frame shards: 30 Parquet files
Source data path: data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet
Source video path: videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4

Converted Files

TsFile: data/so101_single_arrange_yrpblock_top2bottom.tsfile
Rows: 25,478
Table name: so101_single_arrange_yrpblock_top2bottom
Time precision: milliseconds
Mirrored metadata: meta/, with meta/info.json updated for the TsFile artifact

Schema

Time is generated as round(timestamp * 1000) milliseconds. Time restarts within each episode, and devices are identified by the original LeRobot tag columns.

TAG columns: episode_index, task_index
FIELD metadata columns: frame_index, sample_index
FIELD scalar skill columns: skill_natural_language, skill_verification_question, skill_type, skill_progress
FIELD scalar robot columns: observation_gripper_binary, skill_goal_position_gripper
FIELD vectors: observation_state_0..5, action_0..5, observation_ee_pos_robot_xyzrpy_0..5, observation_radian_state_0..5, observation_radian_action_0..5, observation_radian_state_urdf0_0..5, observation_radian_action_urdf0_0..5, skill_goal_position_joint_0..5, skill_goal_position_world_xyzrpy_0..5, and skill_goal_position_robot_xyzrpy_0..5

The 6-element joint vectors use the source SO-101 joint order: shoulder_pan.pos, shoulder_lift.pos, elbow_flex.pos, wrist_flex.pos, wrist_roll.pos, and gripper.pos.

Conversion Notes

The source timestamp column is dropped after being mapped to Time; it is recoverable as Time / 1000 seconds.
The source index column is renamed to sample_index.
Vector/list columns are flattened by preserving the full source column name, replacing . with _, and appending the element index.
Source video features are not uploaded here: observation.images.realsense and observation.images.innomaker. Use the original dataset's videos/ tree for the visual streams.
Aside from the redundant timestamp column and omitted video files, no numeric time-series rows are intentionally dropped.

Read Example

from tsfile import TsFileReader

path = "data/so101_single_arrange_yrpblock_top2bottom.tsfile"

with TsFileReader(path) as reader:
    tables = reader.get_all_table_schemas()
    print(tables.keys())

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Total file size:

2.46 MB