Datasets:

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lerobot

/

behavior1k-task0000

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LeRobot 3.56k

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 16 new columns ({'total_episodes', 'fps', 'total_frames', 'data_path', 'chunks_size', 'metainfo_path', 'total_videos', 'total_tasks', 'video_files_size_in_mb', 'annotation_path', 'features', 'video_path', 'splits', 'data_files_size_in_mb', 'codebase_version', 'robot_type'}) and 5 missing columns ({'data_folder', 'skill_annotation', 'task_name', 'meta_data', 'primitive_annotation'}).

This happened while the json dataset builder was generating data using

hf://datasets/lerobot/behavior1k-task0000/meta/info.json (at revision 1caa106f6f08e572c0660e0fb1f49e9d503be067)

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
              fps: int64
              splits: struct<train: string>
                child 0, train: string
              data_path: string
              video_path: string
              metainfo_path: string
              annotation_path: string
              features: struct<observation.images.rgb.left_wrist: struct<dtype: string, shape: list<item: int64>, names: lis (... 3302 chars omitted)
                child 0, observation.images.rgb.left_wrist: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.fps: d (... 158 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.fps: double, video.height: int64, video.width: int64, video.channels: int64, video.code (... 76 chars omitted)
                        child 0, video.fps: double
                        child 1, video.height: int64
                        child 2, video.width: int64
                        child 3, video.channels: int64
                        child 4, video.codec: string
                        child 5, video.pix_fmt: string
                        child 6, video.is_depth_map: bool
                        child 7, has_audio: bool
                child 1, observation.images.rgb.right_wrist: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.fps: d (... 158 chars omitted)
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, n
              ...
              ld 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
                    child 3, fps: int64
                child 12, index: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
                    child 3, fps: int64
                child 13, task_index: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
                    child 3, fps: int64
                child 14, observation.cam_rel_poses: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
                    child 3, fps: int64
                child 15, observation.state: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
                    child 3, fps: int64
                child 16, observation.task_info: struct<dtype: string, shape: list<item: int64>, names: null, fps: int64>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
                    child 3, fps: int64
              data_files_size_in_mb: int64
              video_files_size_in_mb: int64
              total_videos: int64
              to
              {'task_name': Value('string'), 'data_folder': Value('string'), 'meta_data': {'task_duration': Value('int64'), 'valid_duration': List(Value('int64'))}, 'skill_annotation': List({'skill_idx': Value('int64'), 'skill_id': List(Value('int64')), 'skill_description': List(Value('string')), 'object_id': List(List(Value('string'))), 'manipulating_object_id': List(Value('string')), 'memory_prefix': List(Value('string')), 'spatial_prefix': List(Value('null')), 'frame_duration': List(Value('int64')), 'mp_ef': List(Value('null')), 'skill_type': List(Value('string'))}), 'primitive_annotation': List({'primitive_idx': Value('int64'), 'primitive_id': List(Value('int64')), 'primitive_description': List(Value('string')), 'object_id': List(List(Value('string'))), 'manipulating_object_id': List(Value('string')), 'memory_prefix': List(Value('string')), 'spatial_prefix': List(Value('null')), 'frame_duration': List(Value('int64')), 'skill_idxes': List(Value('int64'))})}
              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 1450, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 993, in stream_convert_to_parquet
                  builder._prepare_split(
                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 16 new columns ({'total_episodes', 'fps', 'total_frames', 'data_path', 'chunks_size', 'metainfo_path', 'total_videos', 'total_tasks', 'video_files_size_in_mb', 'annotation_path', 'features', 'video_path', 'splits', 'data_files_size_in_mb', 'codebase_version', 'robot_type'}) and 5 missing columns ({'data_folder', 'skill_annotation', 'task_name', 'meta_data', 'primitive_annotation'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/lerobot/behavior1k-task0000/meta/info.json (at revision 1caa106f6f08e572c0660e0fb1f49e9d503be067)
              
              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)