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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
episode_index: int64
task: string
num_frames: int64
stride: int64
anchors: list<item: struct<frame: int64, progress: double>>
child 0, item: struct<frame: int64, progress: double>
child 0, frame: int64
child 1, progress: double
progress_per_frame: list<item: double>
child 0, item: double
predictions: list<item: struct<id: string, episode_index: int64, frame: int64, task: string, image: list<item: st (... 52 chars omitted)
child 0, item: struct<id: string, episode_index: int64, frame: int64, task: string, image: list<item: string>, pred (... 40 chars omitted)
child 0, id: string
child 1, episode_index: int64
child 2, frame: int64
child 3, task: string
child 4, image: list<item: string>
child 0, item: string
child 5, pred: string
child 6, progress: double
child 7, hop: double
total_episodes: int64
total_frames: int64
total_tasks: int64
fps: int64
splits: struct<train: string>
child 0, train: string
data_files_size_in_mb: int64
video_path: string
chunks_size: int64
codebase_version: string
robot_type: string
features: struct<observation.images.exterior_1_left: struct<dtype: string, shape: list<item: int64>, names: li (... 1373 chars omitted)
child 0, observation.images.exterior_1_left: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height (... 157 chars omitted)
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item:
...
pe: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 7, index: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 8, task_index: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 9, reward: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 10, progress_delta_15: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 11, progress_t: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 12, progress_t_plus_15: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
data_path: string
video_files_size_in_mb: int64
to
{'codebase_version': Value('string'), 'fps': Value('int64'), 'features': {'observation.images.exterior_1_left': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}, 'observation.images.wrist_left': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}, 'observation.state': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': {'axes': List(Value('string'))}}, 'action': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': {'axes': List(Value('string'))}}, 'timestamp': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'frame_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'episode_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'task_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'reward': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'progress_delta_15': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'progress_t': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'progress_t_plus_15': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}}, 'total_episodes': Value('int64'), 'total_frames': Value('int64'), 'total_tasks': Value('int64'), 'chunks_size': Value('int64'), 'data_files_size_in_mb': Value('int64'), 'video_files_size_in_mb': Value('int64'), 'data_path': Value('string'), 'video_path': Value('string'), 'robot_type': Value('string'), 'splits': {'train': Value('string')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
episode_index: int64
task: string
num_frames: int64
stride: int64
anchors: list<item: struct<frame: int64, progress: double>>
child 0, item: struct<frame: int64, progress: double>
child 0, frame: int64
child 1, progress: double
progress_per_frame: list<item: double>
child 0, item: double
predictions: list<item: struct<id: string, episode_index: int64, frame: int64, task: string, image: list<item: st (... 52 chars omitted)
child 0, item: struct<id: string, episode_index: int64, frame: int64, task: string, image: list<item: string>, pred (... 40 chars omitted)
child 0, id: string
child 1, episode_index: int64
child 2, frame: int64
child 3, task: string
child 4, image: list<item: string>
child 0, item: string
child 5, pred: string
child 6, progress: double
child 7, hop: double
total_episodes: int64
total_frames: int64
total_tasks: int64
fps: int64
splits: struct<train: string>
child 0, train: string
data_files_size_in_mb: int64
video_path: string
chunks_size: int64
codebase_version: string
robot_type: string
features: struct<observation.images.exterior_1_left: struct<dtype: string, shape: list<item: int64>, names: li (... 1373 chars omitted)
child 0, observation.images.exterior_1_left: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height (... 157 chars omitted)
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item:
...
pe: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 7, index: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 8, task_index: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 9, reward: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 10, progress_delta_15: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 11, progress_t: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 12, progress_t_plus_15: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
data_path: string
video_files_size_in_mb: int64
to
{'codebase_version': Value('string'), 'fps': Value('int64'), 'features': {'observation.images.exterior_1_left': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}, 'observation.images.wrist_left': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}, 'observation.state': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': {'axes': List(Value('string'))}}, 'action': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': {'axes': List(Value('string'))}}, 'timestamp': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'frame_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'episode_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'task_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'reward': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'progress_delta_15': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'progress_t': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}, 'progress_t_plus_15': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null')}}, 'total_episodes': Value('int64'), 'total_frames': Value('int64'), 'total_tasks': Value('int64'), 'chunks_size': Value('int64'), 'data_files_size_in_mb': Value('int64'), 'video_files_size_in_mb': Value('int64'), 'data_path': Value('string'), 'video_path': Value('string'), 'robot_type': Value('string'), 'splits': {'train': Value('string')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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