Datasets:

---

ArbazDevHive

/

geosearch-ai-models

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
cls_token: string
mask_token: string
pad_token: string
sep_token: string
unk_token: string
image_processor_type: string
image_std: list<item: double>
  child 0, item: double
image_mean: list<item: double>
  child 0, item: double
size: int64
do_normalize: bool
processor_class: string
do_resize: bool
to
{'do_normalize': Value('bool'), 'do_resize': Value('bool'), 'image_mean': List(Value('float64')), 'image_processor_type': Value('string'), 'image_std': List(Value('float64')), 'processor_class': Value('string'), 'size': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              cls_token: string
              mask_token: string
              pad_token: string
              sep_token: string
              unk_token: string
              image_processor_type: string
              image_std: list<item: double>
                child 0, item: double
              image_mean: list<item: double>
                child 0, item: double
              size: int64
              do_normalize: bool
              processor_class: string
              do_resize: bool
              to
              {'do_normalize': Value('bool'), 'do_resize': Value('bool'), 'image_mean': List(Value('float64')), 'image_processor_type': Value('string'), 'image_std': List(Value('float64')), 'processor_class': Value('string'), 'size': Value('int64')}
              because column names don't match