Datasets:

---

sangramrout

/

CoPilot4d

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
seconds: int64
metrics: list<item: struct<k_to_report: list<item: int64>, name: string, aggregators: list<item: struct<name: (... 29 chars omitted)
  child 0, item: struct<k_to_report: list<item: int64>, name: string, aggregators: list<item: struct<name: string>>,  (... 17 chars omitted)
      child 0, k_to_report: list<item: int64>
          child 0, item: int64
      child 1, name: string
      child 2, aggregators: list<item: struct<name: string>>
          child 0, item: struct<name: string>
              child 0, name: string
      child 3, tolerance: int64
class_range: struct<car: int64, truck: int64, bus: int64, trailer: int64, construction_vehicle: int64, pedestrian (... 80 chars omitted)
  child 0, car: int64
  child 1, truck: int64
  child 2, bus: int64
  child 3, trailer: int64
  child 4, construction_vehicle: int64
  child 5, pedestrian: int64
  child 6, motorcycle: int64
  child 7, bicycle: int64
  child 8, traffic_cone: int64
  child 9, barrier: int64
mean_ap_weight: int64
dist_th_tp: double
min_precision: double
min_recall: double
max_boxes_per_sample: int64
dist_ths: list<item: double>
  child 0, item: double
dist_fcn: string
to
{'class_range': {'car': Value('int64'), 'truck': Value('int64'), 'bus': Value('int64'), 'trailer': Value('int64'), 'construction_vehicle': Value('int64'), 'pedestrian': Value('int64'), 'motorcycle': Value('int64'), 'bicycle': Value('int64'), 'traffic_cone': Value('int64'), 'barrier': Value('int64')}, 'dist_fcn': Value('string'), 'dist_ths': List(Value('float64')), 'dist_th_tp': Value('float64'), 'min_recall': Value('float64'), 'min_precision': Value('float64'), 'max_boxes_per_sample': Value('int64'), 'mean_ap_weight': 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 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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
              seconds: int64
              metrics: list<item: struct<k_to_report: list<item: int64>, name: string, aggregators: list<item: struct<name: (... 29 chars omitted)
                child 0, item: struct<k_to_report: list<item: int64>, name: string, aggregators: list<item: struct<name: string>>,  (... 17 chars omitted)
                    child 0, k_to_report: list<item: int64>
                        child 0, item: int64
                    child 1, name: string
                    child 2, aggregators: list<item: struct<name: string>>
                        child 0, item: struct<name: string>
                            child 0, name: string
                    child 3, tolerance: int64
              class_range: struct<car: int64, truck: int64, bus: int64, trailer: int64, construction_vehicle: int64, pedestrian (... 80 chars omitted)
                child 0, car: int64
                child 1, truck: int64
                child 2, bus: int64
                child 3, trailer: int64
                child 4, construction_vehicle: int64
                child 5, pedestrian: int64
                child 6, motorcycle: int64
                child 7, bicycle: int64
                child 8, traffic_cone: int64
                child 9, barrier: int64
              mean_ap_weight: int64
              dist_th_tp: double
              min_precision: double
              min_recall: double
              max_boxes_per_sample: int64
              dist_ths: list<item: double>
                child 0, item: double
              dist_fcn: string
              to
              {'class_range': {'car': Value('int64'), 'truck': Value('int64'), 'bus': Value('int64'), 'trailer': Value('int64'), 'construction_vehicle': Value('int64'), 'pedestrian': Value('int64'), 'motorcycle': Value('int64'), 'bicycle': Value('int64'), 'traffic_cone': Value('int64'), 'barrier': Value('int64')}, 'dist_fcn': Value('string'), 'dist_ths': List(Value('float64')), 'dist_th_tp': Value('float64'), 'min_recall': Value('float64'), 'min_precision': Value('float64'), 'max_boxes_per_sample': Value('int64'), 'mean_ap_weight': Value('int64')}
              because column names don't match