Datasets:

zjt24
/

eval3_90_permutation

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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eval3_90_permutation (TsFile)

This dataset is an Apache TsFile conversion of the Hugging Face dataset robot-learning-group47/eval3_90_permutation. The source dataset was created using LeRobot.

Modalities: Time-series. The original repository also contains a synchronized front-camera video stream; videos are not included in this converted repository.

Source Dataset

Original dataset: robot-learning-group47/eval3_90_permutation
License: apache-2.0
LeRobot codebase version: v3.0
Robot type: so_follower
Split: train (0:90)
Source scale from meta/info.json: 90 episodes, 20,221 frames, 3 tasks
Sampling rate: 15 fps
Source data layout: data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet
Source video layout: videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4

Tasks:

Place the coke on Taylor Swift.
Place the coke on Barack Obama.
Place the coke on Yann LeCun.

Converted Files

TsFile: data/eval3_90_permutation.tsfile
Converted rows: 20,221
TsFile table: eval3_90_permutation
Time precision: milliseconds
TAG columns: episode_index, task_index
TsFile size: 496,551 bytes

Schema

Time is synthesized as round(timestamp * 1000) in milliseconds. The source timestamp column is dropped because it is redundant with Time / 1000 seconds. At 15 fps, consecutive frames are spaced by about 67 ms.

TAG columns:

episode_index
task_index

FIELD columns:

frame_index
sample_index (renamed from source index)
action_0 to action_5
observation_state_0 to observation_state_5

Vector features are flattened by preserving the source feature name and replacing . with _. For example, observation.state becomes observation_state_0 to observation_state_5. The 6-element action and observation.state vectors use the source joint order: shoulder_pan.pos, shoulder_lift.pos, elbow_flex.pos, wrist_flex.pos, wrist_roll.pos, and gripper.pos.

Attachments

The evaluation permutation map is mirrored as-is from the source dataset:

eval3_episode_permutation_map.csv
eval3_episode_permutation_map.json

These files map each episode to the image triple and left/center/right permutation used during recording.

Video Policy

The source video feature observation.images.front is not converted into TsFile and is not uploaded here. Use the original dataset for videos: robot-learning-group47/eval3_90_permutation/videos.

Metadata

The source meta/ files are mirrored in this repository. meta/info.json is updated so data_path points to data/eval3_90_permutation.tsfile and includes a tsfile_conversion object documenting the Time mapping, TAG columns, flattened features, dropped fields, and video policy.

Validation

The converted TsFile was validated with the project pipeline and read back using the TsFile Python SDK:

staged Parquet rows: 20,221
TsFile metadata rows: 20,221
TsFile query rows: 20,221

Usage

from tsfile import TsFileReader

path = "data/eval3_90_permutation.tsfile"
with TsFileReader(path) as reader:
    schemas = reader.get_all_table_schemas()
    print(schemas.keys())

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Total file size:

4.53 MB