Datasets:

---

agharsallah

/

xpdpfcj65t-repro

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
smoke: bool
parsed: int64
total: int64
parsed_frac: double
metrics: struct<max_rel_gap_pre_1000: double, mean_rel_gap_pre_1000: double, final_rel_gap: double, final_rea (... 43 chars omitted)
  child 0, max_rel_gap_pre_1000: double
  child 1, mean_rel_gap_pre_1000: double
  child 2, final_rel_gap: double
  child 3, final_real_loss: double
  child 4, final_meancov_loss: double
sec_per_item: double
device: string
mean_rel_gap_pre_1000: double
curve_real: list<item: list<item: double>>
  child 0, item: list<item: double>
      child 0, item: double
final_meancov_loss: double
curve_mean: list<item: list<item: double>>
  child 0, item: list<item: double>
      child 0, item: double
config: struct<n: int64, batch: int64, T: int64, lr: double, base_ch: int64, n_train: int64, n_test: int64,  (... 12 chars omitted)
  child 0, n: int64
  child 1, batch: int64
  child 2, T: int64
  child 3, lr: double
  child 4, base_ch: int64
  child 5, n_train: int64
  child 6, n_test: int64
  child 7, seed: int64
divergence_step: int64
max_rel_gap_post_2000: double
final_rel_gap: double
final_real_loss: double
curve_meancov: list<item: list<item: double>>
  child 0, item: list<item: double>
      child 0, item: double
gaps: list<item: list<item: double>>
  child 0, item: list<item: double>
      child 0, item: double
max_rel_gap_pre_1000: double
to
{'config': {'n': Value('int64'), 'batch': Value('int64'), 'T': Value('int64'), 'lr': Value('float64'), 'base_ch': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'seed': Value('int64')}, 'device': Value('string'), 'divergence_step': Value('int64'), 'max_rel_gap_pre_1000': Value('float64'), 'mean_rel_gap_pre_1000': Value('float64'), 'max_rel_gap_post_2000': Value('float64'), 'final_rel_gap': Value('float64'), 'final_real_loss': Value('float64'), 'final_meancov_loss': Value('float64'), 'curve_real': List(List(Value('float64'))), 'curve_mean': List(List(Value('float64'))), 'curve_meancov': List(List(Value('float64'))), 'gaps': List(List(Value('float64')))}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              smoke: bool
              parsed: int64
              total: int64
              parsed_frac: double
              metrics: struct<max_rel_gap_pre_1000: double, mean_rel_gap_pre_1000: double, final_rel_gap: double, final_rea (... 43 chars omitted)
                child 0, max_rel_gap_pre_1000: double
                child 1, mean_rel_gap_pre_1000: double
                child 2, final_rel_gap: double
                child 3, final_real_loss: double
                child 4, final_meancov_loss: double
              sec_per_item: double
              device: string
              mean_rel_gap_pre_1000: double
              curve_real: list<item: list<item: double>>
                child 0, item: list<item: double>
                    child 0, item: double
              final_meancov_loss: double
              curve_mean: list<item: list<item: double>>
                child 0, item: list<item: double>
                    child 0, item: double
              config: struct<n: int64, batch: int64, T: int64, lr: double, base_ch: int64, n_train: int64, n_test: int64,  (... 12 chars omitted)
                child 0, n: int64
                child 1, batch: int64
                child 2, T: int64
                child 3, lr: double
                child 4, base_ch: int64
                child 5, n_train: int64
                child 6, n_test: int64
                child 7, seed: int64
              divergence_step: int64
              max_rel_gap_post_2000: double
              final_rel_gap: double
              final_real_loss: double
              curve_meancov: list<item: list<item: double>>
                child 0, item: list<item: double>
                    child 0, item: double
              gaps: list<item: list<item: double>>
                child 0, item: list<item: double>
                    child 0, item: double
              max_rel_gap_pre_1000: double
              to
              {'config': {'n': Value('int64'), 'batch': Value('int64'), 'T': Value('int64'), 'lr': Value('float64'), 'base_ch': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'seed': Value('int64')}, 'device': Value('string'), 'divergence_step': Value('int64'), 'max_rel_gap_pre_1000': Value('float64'), 'mean_rel_gap_pre_1000': Value('float64'), 'max_rel_gap_post_2000': Value('float64'), 'final_rel_gap': Value('float64'), 'final_real_loss': Value('float64'), 'final_meancov_loss': Value('float64'), 'curve_real': List(List(Value('float64'))), 'curve_mean': List(List(Value('float64'))), 'curve_meancov': List(List(Value('float64'))), 'gaps': List(List(Value('float64')))}
              because column names don't match