Datasets:

---

explcre

/

agenticvbench-understanding-materials

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
races: list<item: struct<track: string, t: int64, items_collected: int64, spinouts: int64, skid_time: doubl (... 3 chars omitted)
  child 0, item: struct<track: string, t: int64, items_collected: int64, spinouts: int64, skid_time: double>
      child 0, track: string
      child 1, t: int64
      child 2, items_collected: int64
      child 3, spinouts: int64
      child 4, skid_time: double
reward: double
details: struct<reason: string, hero: string, n_races: int64, n_predicted_races: int64, n_time_matched: int64 (... 312 chars omitted)
  child 0, reason: string
  child 1, hero: string
  child 2, n_races: int64
  child 3, n_predicted_races: int64
  child 4, n_time_matched: int64
  child 5, time_tol_s: double
  child 6, dims: struct<items_collected: struct<tau: double, accuracy: double, score: double, n_pairs: int64, gt_vari (... 108 chars omitted)
      child 0, items_collected: struct<tau: double, accuracy: double, score: double, n_pairs: int64, gt_varies: bool>
          child 0, tau: double
          child 1, accuracy: double
          child 2, score: double
          child 3, n_pairs: int64
          child 4, gt_varies: bool
      child 1, skid_time: struct<tau: double, accuracy: double, score: double, n_pairs: int64, gt_varies: bool>
          child 0, tau: double
          child 1, accuracy: double
          child 2, score: double
          child 3, n_pairs: int64
          child 4, gt_varies: bool
  child 7, weights: struct<items_collected: double, skid_time: double>
      child 0, items_collected: double
      child 1, skid_time: double
  child 8, note: string
to
{'reward': Value('float64'), 'details': {'reason': Value('string'), 'hero': Value('string'), 'n_races': Value('int64'), 'n_predicted_races': Value('int64'), 'n_time_matched': Value('int64'), 'time_tol_s': Value('float64'), 'dims': {'items_collected': {'tau': Value('float64'), 'accuracy': Value('float64'), 'score': Value('float64'), 'n_pairs': Value('int64'), 'gt_varies': Value('bool')}, 'skid_time': {'tau': Value('float64'), 'accuracy': Value('float64'), 'score': Value('float64'), 'n_pairs': Value('int64'), 'gt_varies': Value('bool')}}, 'weights': {'items_collected': Value('float64'), 'skid_time': Value('float64')}, 'note': Value('string')}}
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
              races: list<item: struct<track: string, t: int64, items_collected: int64, spinouts: int64, skid_time: doubl (... 3 chars omitted)
                child 0, item: struct<track: string, t: int64, items_collected: int64, spinouts: int64, skid_time: double>
                    child 0, track: string
                    child 1, t: int64
                    child 2, items_collected: int64
                    child 3, spinouts: int64
                    child 4, skid_time: double
              reward: double
              details: struct<reason: string, hero: string, n_races: int64, n_predicted_races: int64, n_time_matched: int64 (... 312 chars omitted)
                child 0, reason: string
                child 1, hero: string
                child 2, n_races: int64
                child 3, n_predicted_races: int64
                child 4, n_time_matched: int64
                child 5, time_tol_s: double
                child 6, dims: struct<items_collected: struct<tau: double, accuracy: double, score: double, n_pairs: int64, gt_vari (... 108 chars omitted)
                    child 0, items_collected: struct<tau: double, accuracy: double, score: double, n_pairs: int64, gt_varies: bool>
                        child 0, tau: double
                        child 1, accuracy: double
                        child 2, score: double
                        child 3, n_pairs: int64
                        child 4, gt_varies: bool
                    child 1, skid_time: struct<tau: double, accuracy: double, score: double, n_pairs: int64, gt_varies: bool>
                        child 0, tau: double
                        child 1, accuracy: double
                        child 2, score: double
                        child 3, n_pairs: int64
                        child 4, gt_varies: bool
                child 7, weights: struct<items_collected: double, skid_time: double>
                    child 0, items_collected: double
                    child 1, skid_time: double
                child 8, note: string
              to
              {'reward': Value('float64'), 'details': {'reason': Value('string'), 'hero': Value('string'), 'n_races': Value('int64'), 'n_predicted_races': Value('int64'), 'n_time_matched': Value('int64'), 'time_tol_s': Value('float64'), 'dims': {'items_collected': {'tau': Value('float64'), 'accuracy': Value('float64'), 'score': Value('float64'), 'n_pairs': Value('int64'), 'gt_varies': Value('bool')}, 'skid_time': {'tau': Value('float64'), 'accuracy': Value('float64'), 'score': Value('float64'), 'n_pairs': Value('int64'), 'gt_varies': Value('bool')}}, 'weights': {'items_collected': Value('float64'), 'skid_time': Value('float64')}, 'note': Value('string')}}
              because column names don't match