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mlfoundations-cua-dev 9

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
dataset: string
split: string
sampled: int64
processed: int64
skipped: int64
newly_processed: int64
total_cost: double
average_cost_per_image: double
resolution: string
results: list<item: struct<index: int64, cost: double, skipped: bool>>
dry_run: bool
vs
dataset: string
split: string
index: int64
mode: string
instruction: string
dimensions: struct<width: int64, height: int64>
processing_cost: struct<input_tokens: int64, output_tokens: int64, input_cost: double, output_cost: double, total_cost: double>
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 527, 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: 
              dataset: string
              split: string
              sampled: int64
              processed: int64
              skipped: int64
              newly_processed: int64
              total_cost: double
              average_cost_per_image: double
              resolution: string
              results: list<item: struct<index: int64, cost: double, skipped: bool>>
              dry_run: bool
              vs
              dataset: string
              split: string
              index: int64
              mode: string
              instruction: string
              dimensions: struct<width: int64, height: int64>
              processing_cost: struct<input_tokens: int64, output_tokens: int64, input_cost: double, output_cost: double, total_cost: double>