Datasets:

---

ethanCSL

/

pick_n_place_50_two_camera

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 ({'total_chunks', 'video_path', 'robot_type', 'chunks_size', 'total_episodes', 'data_path', 'total_tasks', 'fps', 'total_frames', 'total_videos', 'codebase_version', 'features', 'splits'}) and 3 missing columns ({'length', 'episode_index', 'tasks'}).

This happened while the json dataset builder was generating data using

hf://datasets/ethanCSL/pick_n_place_50_two_camera/meta/info.json (at revision cb4bf73f8a3badc85e86d8b802daf524c42a2344)

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
              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<observation.images.image_front_eye: struct<dtype: string, shape: list<item: int64>, names: li (... 1373 chars omitted)
                child 0, observation.images.image_front_eye: 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.image_rear_eye: 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: 
              ...
              t<item: string>>
                        child 0, motors: list<item: string>
                            child 0, item: string
                child 4, action: struct<dtype: string, shape: list<item: int64>, names: struct<motors: list<item: string>>>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: struct<motors: list<item: string>>
                        child 0, motors: list<item: string>
                            child 0, item: string
                child 5, 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 6, 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 7, 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 8, 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, 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')}
              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 1455, 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 1054, 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 ({'total_chunks', 'video_path', 'robot_type', 'chunks_size', 'total_episodes', 'data_path', 'total_tasks', 'fps', 'total_frames', 'total_videos', 'codebase_version', 'features', 'splits'}) and 3 missing columns ({'length', 'episode_index', 'tasks'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/ethanCSL/pick_n_place_50_two_camera/meta/info.json (at revision cb4bf73f8a3badc85e86d8b802daf524c42a2344)
              
              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)