Datasets:

---

AdleBens

/

task_index

like 0

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 13 new columns ({'robot_type', 'codebase_version', 'total_tasks', 'total_frames', 'features', 'total_videos', 'total_chunks', 'chunks_size', 'splits', 'video_path', 'total_episodes', 'fps', 'data_path'}) and 3 missing columns ({'length', 'tasks', 'episode_index'}).

This happened while the json dataset builder was generating data using

hf://datasets/AdleBens/task_index/meta/info.json (at revision 63295ff59ade6e86d0d28307cac3f99fcfe16a8a)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              robot_type: string
              codebase_version: string
              total_episodes: int64
              total_frames: int64
              total_tasks: int64
              total_videos: int64
              total_chunks: int64
              chunks_size: int64
              fps: int64
              splits: struct<train: string>
                child 0, train: string
              data_path: string
              video_path: string
              features: struct<action: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>, timestamp: struct<dtype: string, shape: list<item: int64>, names: null>, episode_index: struct<dtype: string, shape: list<item: int64>, names: null>, frame_index: struct<dtype: string, shape: list<item: int64>, names: null>, task_index: struct<dtype: string, shape: list<item: int64>, names: null>, index: struct<dtype: string, shape: list<item: int64>, names: null>, observation.state: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>, observation.images.main: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video_fps: int64, video_codec: string, video_pix_fmt: string, video_is_depth_map: bool, has_audio: bool>>>
                child 0, action: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: list<item: string>
                        child 0, item: string
                child 1, timestamp: struct<dtype: string, shape: list<item: int64>, names: null>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
              ...
              ist<item: int64>
                        child 0, item: int64
                    child 2, names: null
                child 4, 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 5, 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 6, observation.state: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: list<item: string>
                        child 0, item: string
                child 7, observation.images.main: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video_fps: int64, video_codec: string, video_pix_fmt: string, video_is_depth_map: bool, has_audio: bool>>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: list<item: string>
                        child 0, item: string
                    child 3, info: struct<video_fps: int64, video_codec: string, video_pix_fmt: string, video_is_depth_map: bool, has_audio: bool>
                        child 0, video_fps: int64
                        child 1, video_codec: string
                        child 2, video_pix_fmt: string
                        child 3, video_is_depth_map: bool
                        child 4, has_audio: bool
              to
              {'episode_index': Value(dtype='int64', id=None), 'tasks': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'length': Value(dtype='int64', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1420, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1052, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 13 new columns ({'robot_type', 'codebase_version', 'total_tasks', 'total_frames', 'features', 'total_videos', 'total_chunks', 'chunks_size', 'splits', 'video_path', 'total_episodes', 'fps', 'data_path'}) and 3 missing columns ({'length', 'tasks', 'episode_index'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/AdleBens/task_index/meta/info.json (at revision 63295ff59ade6e86d0d28307cac3f99fcfe16a8a)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)