Datasets:

---

Beilinghamburger

/

so100_vla_dataset_1216

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 ({'fps', 'robot_type', 'codebase_version', 'data_files_size_in_mb', 'total_frames', 'chunks_size', 'data_path', 'video_files_size_in_mb', 'total_tasks', 'video_path', 'total_episodes', 'features', 'splits'}) and 107 missing columns ({'stats/observation.state/q90', 'stats/task_index/mean', 'stats/episode_index/q01', 'stats/index/std', 'stats/timestamp/q90', 'stats/frame_index/q10', 'stats/timestamp/q10', 'stats/episode_index/mean', 'stats/frame_index/mean', 'stats/observation.images.front/std', 'stats/observation.state/min', 'stats/observation.images.front/min', 'stats/episode_index/q10', 'stats/observation.images.wrist/max', 'stats/index/q10', 'data/chunk_index', 'stats/observation.state/mean', 'stats/observation.images.front/q10', 'stats/observation.state/std', 'stats/action/q90', 'videos/observation.images.front/file_index', 'stats/observation.images.wrist/min', 'stats/timestamp/q99', 'stats/observation.state/q10', 'stats/frame_index/q99', 'tasks', 'stats/observation.images.wrist/mean', 'stats/observation.images.front/max', 'stats/observation.images.wrist/std', 'stats/observation.images.front/mean', 'stats/timestamp/count', 'stats/task_index/q90', 'stats/timestamp/q50', 'stats/task_index/q99', 'videos/observation.images.wrist/file_index', 'videos/observation.images.front/chunk_index', 'stats/action/q50', 'stats/frame_index/min', 'stats/timestamp/q01', 'stats/frame_index/count', 'videos/observation.images.wrist/from_timestamp', 'stats/episode_index/q50', 'stats/observation.images.front/q99', 'stats/index/q50', 'stats/observation.images.wrist/q90', 'stats/episode_index/std', 'stats/frame_index/max', 'stats/episode_index/q90', 'stats/task_index/q01', 'dataset_to_index', 'stats/observation.images.front/q50
...
t/count', 'stats/task_index/std', 'stats/task_index/min', 'stats/observation.images.wrist/q10', 'stats/action/q99', 'stats/observation.state/count', 'meta/episodes/file_index', 'stats/action/std', 'stats/task_index/max', 'stats/frame_index/q90', 'stats/episode_index/max', 'stats/index/q90', 'length', 'data/file_index', 'stats/frame_index/q01', 'stats/index/q01', 'stats/frame_index/std', 'stats/frame_index/q50', 'stats/index/q99', 'dataset_from_index', 'stats/action/q01', 'stats/index/min', 'stats/action/max', 'videos/observation.images.front/from_timestamp', 'stats/episode_index/count', 'stats/action/mean', 'videos/observation.images.wrist/to_timestamp', 'videos/observation.images.front/to_timestamp', 'stats/observation.images.front/count', 'stats/task_index/q50', 'videos/observation.images.wrist/chunk_index', 'stats/episode_index/min', 'stats/observation.state/q50', 'stats/observation.state/q01', 'stats/action/q10', 'meta/episodes/chunk_index', 'stats/index/count', 'episode_index', 'stats/observation.images.front/q01', 'stats/observation.images.front/q90', 'stats/index/max', 'stats/task_index/q10', 'stats/action/count', 'stats/timestamp/std', 'stats/observation.images.wrist/q99', 'stats/timestamp/max', 'stats/timestamp/mean', 'stats/task_index/count', 'stats/observation.state/q99', 'stats/observation.images.wrist/q01', 'stats/observation.images.wrist/q50', 'stats/timestamp/min', 'stats/index/mean', 'stats/observation.state/max', 'stats/episode_index/q99', 'stats/action/min'}).

This happened while the json dataset builder was generating data using

hf://datasets/Beilinghamburger/so100_vla_dataset_1216/meta/info.json (at revision 20a9bc0ac4440a6f8b7e5e45f22311d1efcc6c59)

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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              codebase_version: string
              robot_type: string
              total_episodes: int64
              total_frames: int64
              total_tasks: int64
              chunks_size: int64
              data_files_size_in_mb: int64
              video_files_size_in_mb: 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>>, observati (... 1023 chars omitted)
                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, 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 2, observation.images.front: 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: int64
                    child 2, names: list<item: string>
                        child 0, item: string
                    child 3, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is (... 75 chars omitted)
                        child 0, video.height: int64
                        chil
              ...
              d 3, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is (... 75 chars omitted)
                        child 0, video.height: int64
                        child 1, video.width: int64
                        child 2, video.codec: string
                        child 3, video.pix_fmt: string
                        child 4, video.is_depth_map: bool
                        child 5, video.fps: int64
                        child 6, video.channels: int64
                        child 7, has_audio: bool
                child 4, timestamp: 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, frame_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, episode_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 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
              to
              {'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': Value('int64'), 'data/chunk_index': Value('int64'), 'data/file_index': Value('int64'), 'dataset_from_index': Value('int64'), 'dataset_to_index': Value('int64'), 'videos/observation.images.front/chunk_index': Value('int64'), 'videos/observation.images.front/file_index': Value('int64'), 'videos/observation.images.front/from_timestamp': Value('float64'), 'videos/observation.images.front/to_timestamp': Value('float64'), 'videos/observation.images.wrist/chunk_index': Value('int64'), 'videos/observation.images.wrist/file_index': Value('int64'), 'videos/observation.images.wrist/from_timestamp': Value('float64'), 'videos/observation.images.wrist/to_timestamp': Value('float64'), 'stats/action/min': List(Value('float64')), 'stats/action/max': List(Value('float64')), 'stats/action/mean': List(Value('float64')), 'stats/action/std': List(Value('float64')), 'stats/action/count': List(Value('int64')), 'stats/observation.state/min': List(Value('float64')), 'stats/observation.state/max': List(Value('float64')), 'stats/observation.state/mean': List(Value('float64')), 'stats/observation.state/std': List(Value('float64')), 'stats/observation.state/count': List(Value('int64')), 'stats/observation.images.front/min': List(List(List(Value('float64')))), 'stats/observation.images.front/max': List(List(List(Value('float64')))), 'stats/observation.images.front/mean': List(List(List(Value('float64')))), 'stats/observation.images
              ...
              'float64')))), 'stats/observation.images.wrist/q10': List(List(List(Value('float64')))), 'stats/observation.images.wrist/q50': List(List(List(Value('float64')))), 'stats/observation.images.wrist/q90': List(List(List(Value('float64')))), 'stats/observation.images.wrist/q99': List(List(List(Value('float64')))), 'stats/timestamp/q01': List(Value('float64')), 'stats/timestamp/q10': List(Value('float64')), 'stats/timestamp/q50': List(Value('float64')), 'stats/timestamp/q90': List(Value('float64')), 'stats/timestamp/q99': List(Value('float64')), 'stats/frame_index/q01': List(Value('float64')), 'stats/frame_index/q10': List(Value('float64')), 'stats/frame_index/q50': List(Value('float64')), 'stats/frame_index/q90': List(Value('float64')), 'stats/frame_index/q99': List(Value('float64')), 'stats/episode_index/q01': List(Value('float64')), 'stats/episode_index/q10': List(Value('float64')), 'stats/episode_index/q50': List(Value('float64')), 'stats/episode_index/q90': List(Value('float64')), 'stats/episode_index/q99': List(Value('float64')), 'stats/index/q01': List(Value('float64')), 'stats/index/q10': List(Value('float64')), 'stats/index/q50': List(Value('float64')), 'stats/index/q90': List(Value('float64')), 'stats/index/q99': List(Value('float64')), 'stats/task_index/q01': List(Value('float64')), 'stats/task_index/q10': List(Value('float64')), 'stats/task_index/q50': List(Value('float64')), 'stats/task_index/q90': List(Value('float64')), 'stats/task_index/q99': List(Value('float64'))}
              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 1339, 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 972, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, 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 ({'fps', 'robot_type', 'codebase_version', 'data_files_size_in_mb', 'total_frames', 'chunks_size', 'data_path', 'video_files_size_in_mb', 'total_tasks', 'video_path', 'total_episodes', 'features', 'splits'}) and 107 missing columns ({'stats/observation.state/q90', 'stats/task_index/mean', 'stats/episode_index/q01', 'stats/index/std', 'stats/timestamp/q90', 'stats/frame_index/q10', 'stats/timestamp/q10', 'stats/episode_index/mean', 'stats/frame_index/mean', 'stats/observation.images.front/std', 'stats/observation.state/min', 'stats/observation.images.front/min', 'stats/episode_index/q10', 'stats/observation.images.wrist/max', 'stats/index/q10', 'data/chunk_index', 'stats/observation.state/mean', 'stats/observation.images.front/q10', 'stats/observation.state/std', 'stats/action/q90', 'videos/observation.images.front/file_index', 'stats/observation.images.wrist/min', 'stats/timestamp/q99', 'stats/observation.state/q10', 'stats/frame_index/q99', 'tasks', 'stats/observation.images.wrist/mean', 'stats/observation.images.front/max', 'stats/observation.images.wrist/std', 'stats/observation.images.front/mean', 'stats/timestamp/count', 'stats/task_index/q90', 'stats/timestamp/q50', 'stats/task_index/q99', 'videos/observation.images.wrist/file_index', 'videos/observation.images.front/chunk_index', 'stats/action/q50', 'stats/frame_index/min', 'stats/timestamp/q01', 'stats/frame_index/count', 'videos/observation.images.wrist/from_timestamp', 'stats/episode_index/q50', 'stats/observation.images.front/q99', 'stats/index/q50', 'stats/observation.images.wrist/q90', 'stats/episode_index/std', 'stats/frame_index/max', 'stats/episode_index/q90', 'stats/task_index/q01', 'dataset_to_index', 'stats/observation.images.front/q50
              ...
              t/count', 'stats/task_index/std', 'stats/task_index/min', 'stats/observation.images.wrist/q10', 'stats/action/q99', 'stats/observation.state/count', 'meta/episodes/file_index', 'stats/action/std', 'stats/task_index/max', 'stats/frame_index/q90', 'stats/episode_index/max', 'stats/index/q90', 'length', 'data/file_index', 'stats/frame_index/q01', 'stats/index/q01', 'stats/frame_index/std', 'stats/frame_index/q50', 'stats/index/q99', 'dataset_from_index', 'stats/action/q01', 'stats/index/min', 'stats/action/max', 'videos/observation.images.front/from_timestamp', 'stats/episode_index/count', 'stats/action/mean', 'videos/observation.images.wrist/to_timestamp', 'videos/observation.images.front/to_timestamp', 'stats/observation.images.front/count', 'stats/task_index/q50', 'videos/observation.images.wrist/chunk_index', 'stats/episode_index/min', 'stats/observation.state/q50', 'stats/observation.state/q01', 'stats/action/q10', 'meta/episodes/chunk_index', 'stats/index/count', 'episode_index', 'stats/observation.images.front/q01', 'stats/observation.images.front/q90', 'stats/index/max', 'stats/task_index/q10', 'stats/action/count', 'stats/timestamp/std', 'stats/observation.images.wrist/q99', 'stats/timestamp/max', 'stats/timestamp/mean', 'stats/task_index/count', 'stats/observation.state/q99', 'stats/observation.images.wrist/q01', 'stats/observation.images.wrist/q50', 'stats/timestamp/min', 'stats/index/mean', 'stats/observation.state/max', 'stats/episode_index/q99', 'stats/action/min'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/Beilinghamburger/so100_vla_dataset_1216/meta/info.json (at revision 20a9bc0ac4440a6f8b7e5e45f22311d1efcc6c59)
              
              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)