Datasets:

---

ywu67

/

record-test-new

like 0

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
_data_files: list<item: struct<filename: string>>
_fingerprint: string
_format_columns: null
_format_kwargs: struct<>
_format_type: null
_output_all_columns: bool
_split: null
vs
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>
data_path: string
video_path: string
features: struct<action: struct<dtype: string, names: list<item: string>, shape: list<item: int64>>, observation.state: struct<dtype: string, names: list<item: string>, shape: list<item: int64>>, observation.images.left: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is_depth_map: bool, video.fps: int64, video.channels: int64, has_audio: bool>>, observation.images.top: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is_depth_map: bool, video.fps: int64, video.channels: int64, has_audio: bool>>, timestamp: struct<dtype: string, shape: list<item: int64>, names: null>, frame_index: struct<dtype: string, shape: list<item: int64>, names: null>, episode_index: struct<dtype: string, shape: list<item: int64>, names: null>, index: struct<dtype: string, shape: list<item: int64>, names: null>, task_index: struct<dtype: string, shape: list<item: int64>, names: null>>
num_episodes: int64
total_seconds: double
clipping_info: struct<original_total_frames: int64, original_duration_seconds: double, clip_duration_seconds: int64, frames_per_episode_clipped: int64, processing_date: string>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3422, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2187, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2391, in iter
                  for key, example in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1904, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 559, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              _data_files: list<item: struct<filename: string>>
              _fingerprint: string
              _format_columns: null
              _format_kwargs: struct<>
              _format_type: null
              _output_all_columns: bool
              _split: null
              vs
              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>
              data_path: string
              video_path: string
              features: struct<action: struct<dtype: string, names: list<item: string>, shape: list<item: int64>>, observation.state: struct<dtype: string, names: list<item: string>, shape: list<item: int64>>, observation.images.left: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is_depth_map: bool, video.fps: int64, video.channels: int64, has_audio: bool>>, observation.images.top: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is_depth_map: bool, video.fps: int64, video.channels: int64, has_audio: bool>>, timestamp: struct<dtype: string, shape: list<item: int64>, names: null>, frame_index: struct<dtype: string, shape: list<item: int64>, names: null>, episode_index: struct<dtype: string, shape: list<item: int64>, names: null>, index: struct<dtype: string, shape: list<item: int64>, names: null>, task_index: struct<dtype: string, shape: list<item: int64>, names: null>>
              num_episodes: int64
              total_seconds: double
              clipping_info: struct<original_total_frames: int64, original_duration_seconds: double, clip_duration_seconds: int64, frames_per_episode_clipped: int64, processing_date: string>