Datasets:

---

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Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
shape: list<item: int64>
data_type: string
chunk_grid: struct<name: string, configuration: struct<chunk_shape: list<item: int64>>>
chunk_key_encoding: struct<name: string, configuration: struct<separator: string>>
fill_value: double
codecs: list<item: struct<name: string, configuration: struct<endian: string, level: int64, checksum: bool>>>
attributes: struct<>
zarr_format: int64
node_type: string
storage_transformers: list<item: null>
vs
shape: list<item: int64>
data_type: struct<name: string, configuration: struct<length_bytes: int64>>
chunk_grid: struct<name: string, configuration: struct<chunk_shape: list<item: int64>>>
chunk_key_encoding: struct<name: string, configuration: struct<separator: string>>
fill_value: string
codecs: list<item: struct<name: string, configuration: struct<level: int64, checksum: bool>>>
attributes: struct<>
zarr_format: int64
node_type: string
storage_transformers: list<item: null>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 531, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              shape: list<item: int64>
              data_type: string
              chunk_grid: struct<name: string, configuration: struct<chunk_shape: list<item: int64>>>
              chunk_key_encoding: struct<name: string, configuration: struct<separator: string>>
              fill_value: double
              codecs: list<item: struct<name: string, configuration: struct<endian: string, level: int64, checksum: bool>>>
              attributes: struct<>
              zarr_format: int64
              node_type: string
              storage_transformers: list<item: null>
              vs
              shape: list<item: int64>
              data_type: struct<name: string, configuration: struct<length_bytes: int64>>
              chunk_grid: struct<name: string, configuration: struct<chunk_shape: list<item: int64>>>
              chunk_key_encoding: struct<name: string, configuration: struct<separator: string>>
              fill_value: string
              codecs: list<item: struct<name: string, configuration: struct<level: int64, checksum: bool>>>
              attributes: struct<>
              zarr_format: int64
              node_type: string
              storage_transformers: list<item: null>