The dataset viewer is not available for this subset.
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.
G1 Dex3 Grasp Square Dataset TsFile
This repository is an Apache TsFile conversion of unitreerobotics/G1_Dex3_GraspSquare_Dataset, a LeRobot v3 robot-manipulation dataset. It contains numeric trajectories and metadata; camera videos remain in the original Hugging Face dataset.
Source dataset
- Original dataset: unitreerobotics/G1_Dex3_GraspSquare_Dataset
- Original uploader/contributors: Henry-Ellis and lv-1; hosted by Unitree Robotics.
- License: Apache-2.0. The source card provides no paper or formal citation.
- Task: stack three 5 cm cubic blocks from bottom to top in red, yellow, blue order on black tape.
- Robot: 7-DOF dual-arm
Unitree_G1with three-finger dexterous hands. - Sampling: 30 Hz; 301 episodes, 281,196 frames, one task, one source Parquet shard.
- Source numeric layout:
data/chunk-000/file-000.parquet.
Converted files
- TsFile:
data/g1_dex3_graspsquare_dataset_train.tsfile - Table:
g1_dex3_graspsquare_dataset_train - Rows: 281,196; devices: 301 (one per
episode_index/task_indexTAG combination). - Time precision: milliseconds;
Time = round(timestamp * 1000)and restarts at the first frame of each episode. - Size: source Parquet 63,247,041 bytes; flattened/staged Parquet 74,725,871 bytes; TsFile 51,443,386 bytes. The TsFile is smaller than both source and staged representations.
TsFile schema
| Role | Columns | Source/type |
|---|---|---|
| TIME | Time |
int64, milliseconds from timestamp |
| TAG/device | episode_index, task_index |
source int64, stored by TsFile device/tag mechanism as string segments |
| FIELD | frame_index, sample_index |
int64; sample_index is renamed from source index |
| FIELD | observation_state_0 … observation_state_27 |
28 FLOAT dimensions from observation.state |
| FIELD | action_0 … action_27 |
28 FLOAT dimensions from action |
Vector names retain their source prefix (. becomes _) and are flattened row-major to scalar fields. frame_index is preserved for video/frame alignment. The redundant source timestamp column is dropped after deriving Time; no numeric rows or vector dimensions are dropped. The four video columns are intentionally omitted from TsFile.
Encoding and compression
| TsFile type | Encoding | Compression |
|---|---|---|
| FLOAT/DOUBLE | GORILLA | LZ4 |
| INT32/INT64 | TS_2DIFF | LZ4 |
| Time | TS_2DIFF | LZ4 |
| BOOLEAN (if present) | RLE | LZ4 |
| TAG | TsFile device/tag mechanism | TsFile-managed |
Videos and frame alignment
Videos are not copied or uploaded with this TsFile dataset. The original repository's videos/ tree is about 9.12 GB and contains four streams:
The source path template is videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4. Numeric rows remain frame-aligned through episode_index and frame_index, with episode metadata under meta/episodes/.
Validation
Local validation read the TsFile with the bundled TsFile Python SDK and compared it with the staged Parquet: 281,196 metadata rows and 281,196 query rows, 301 devices, unique (episode_index, task_index, Time) keys, monotonic Time within each episode, and all 28 action plus 28 observation-state dimensions present. Detailed local reports are validation_report.json and VALIDATION.md.
Usage
from tsfile import TsFileReader
path = "data/g1_dex3_graspsquare_dataset_train.tsfile"
reader = TsFileReader(path)
table = "g1_dex3_graspsquare_dataset_train"
columns = ["episode_index", "task_index", "frame_index", "sample_index", "action_0", "observation_state_0"]
with reader.query_table(table, columns, batch_size=65536) as result:
batch = result.read_arrow_batch()
print(batch.to_pandas().head())
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