Datasets:

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Consumer AI Edge Hackathon (Meta, Hugging Face, Pytorch, Scaleway & Unaite) 24

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
name: string
n_num_features: int64
n_cat_features: int64
train_size: int64
val_size: int64
test_size: int64
source: string
task_intro: string
task_type: string
openml_id: int64
imbalance_ratio: double
n_classes: int64
num_feature_intro: struct<>
cat_feature_intro: struct<buying_price_vhigh: string, buying_price_high: string, buying_price_med: string, buying_price_low: string, maintenance_price_vhigh: string, maintenance_price_high: string, maintenance_price_med: string, maintenance_price_low: string, doors_2: string, doors_3: string, doors_4: string, doors_5more: string, persons_2: string, persons_4: string, persons_more: string, luggage_boot_size_small: string, luggage_boot_size_med: string, luggage_boot_size_big: string, safety_low: string, safety_med: string, safety_high: string>
vs
task_type: string
num_classes: int64
n_num_features: int64
n_cat_features: int64
train_size: int64
val_size: int64
test_size: int64
source: 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: 
              name: string
              n_num_features: int64
              n_cat_features: int64
              train_size: int64
              val_size: int64
              test_size: int64
              source: string
              task_intro: string
              task_type: string
              openml_id: int64
              imbalance_ratio: double
              n_classes: int64
              num_feature_intro: struct<>
              cat_feature_intro: struct<buying_price_vhigh: string, buying_price_high: string, buying_price_med: string, buying_price_low: string, maintenance_price_vhigh: string, maintenance_price_high: string, maintenance_price_med: string, maintenance_price_low: string, doors_2: string, doors_3: string, doors_4: string, doors_5more: string, persons_2: string, persons_4: string, persons_more: string, luggage_boot_size_small: string, luggage_boot_size_med: string, luggage_boot_size_big: string, safety_low: string, safety_med: string, safety_high: string>
              vs
              task_type: string
              num_classes: int64
              n_num_features: int64
              n_cat_features: int64
              train_size: int64
              val_size: int64
              test_size: int64
              source: string