Datasets:

---

agharsallah

/

gfpptokv9c-repro

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
smoke: bool
parsed: int64
total: int64
parsed_frac: double
metrics: struct<ece_uncalibrated_lenet5: double, ece_ecl_lenet5: double>
  child 0, ece_uncalibrated_lenet5: double
  child 1, ece_ecl_lenet5: double
sec_per_item: double
device: string
config: struct<n: int64, stub: bool, smoke: bool, dump_raw: int64, model: null, dtype: string, out: string,  (... 204 chars omitted)
  child 0, n: int64
  child 1, stub: bool
  child 2, smoke: bool
  child 3, dump_raw: int64
  child 4, model: null
  child 5, dtype: string
  child 6, out: string
  child 7, seed: int64
  child 8, upload_repo: string
  child 9, models: string
  child 10, epochs: int64
  child 11, ecl_epochs: int64
  child 12, batch_size: int64
  child 13, lr: double
  child 14, lambda_ecl: double
  child 15, num_bins: int64
  child 16, skip_pseudocal: bool
  child 17, n_train: int64
  child 18, n_test: int64
models: struct<lenet5: struct<name: string, ece_uncalibrated: double, ece_ecl: double, ece_pseudocal: null,  (... 344 chars omitted)
  child 0, lenet5: struct<name: string, ece_uncalibrated: double, ece_ecl: double, ece_pseudocal: null, improvement_abs (... 34 chars omitted)
      child 0, name: string
      child 1, ece_uncalibrated: double
      child 2, ece_ecl: double
      child 3, ece_pseudocal: null
      child 4, improvement_abs: double
      child 5, improvement_pct: double
  child 1, resnet20: struct<name: string, ece_uncalibrated: double, ece_ecl: double, ece_pseudocal: null, improvement_abs (... 34 chars omitted)
      child 0, name: string
      child 1, ece_uncalibrated: double
      child 2, ece_ecl: double
      child 3, ece_pseudocal: null
      child 4, improvement_abs: double
      child 5, improvement_pct: double
  child 2, densenet40: struct<name: string, ece_uncalibrated: double, ece_ecl: double, ece_pseudocal: null, improvement_abs (... 34 chars omitted)
      child 0, name: string
      child 1, ece_uncalibrated: double
      child 2, ece_ecl: double
      child 3, ece_pseudocal: null
      child 4, improvement_abs: double
      child 5, improvement_pct: double
to
{'config': {'n': Value('int64'), 'stub': Value('bool'), 'smoke': Value('bool'), 'dump_raw': Value('int64'), 'model': Value('null'), 'dtype': Value('string'), 'out': Value('string'), 'seed': Value('int64'), 'upload_repo': Value('string'), 'models': Value('string'), 'epochs': Value('int64'), 'ecl_epochs': Value('int64'), 'batch_size': Value('int64'), 'lr': Value('float64'), 'lambda_ecl': Value('float64'), 'num_bins': Value('int64'), 'skip_pseudocal': Value('bool'), 'n_train': Value('int64'), 'n_test': Value('int64')}, 'device': Value('string'), 'models': {'lenet5': {'name': Value('string'), 'ece_uncalibrated': Value('float64'), 'ece_ecl': Value('float64'), 'ece_pseudocal': Value('null'), 'improvement_abs': Value('float64'), 'improvement_pct': Value('float64')}, 'resnet20': {'name': Value('string'), 'ece_uncalibrated': Value('float64'), 'ece_ecl': Value('float64'), 'ece_pseudocal': Value('null'), 'improvement_abs': Value('float64'), 'improvement_pct': Value('float64')}, 'densenet40': {'name': Value('string'), 'ece_uncalibrated': Value('float64'), 'ece_ecl': Value('float64'), 'ece_pseudocal': Value('null'), 'improvement_abs': Value('float64'), 'improvement_pct': 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<ece_uncalibrated_lenet5: double, ece_ecl_lenet5: double>
                child 0, ece_uncalibrated_lenet5: double
                child 1, ece_ecl_lenet5: double
              sec_per_item: double
              device: string
              config: struct<n: int64, stub: bool, smoke: bool, dump_raw: int64, model: null, dtype: string, out: string,  (... 204 chars omitted)
                child 0, n: int64
                child 1, stub: bool
                child 2, smoke: bool
                child 3, dump_raw: int64
                child 4, model: null
                child 5, dtype: string
                child 6, out: string
                child 7, seed: int64
                child 8, upload_repo: string
                child 9, models: string
                child 10, epochs: int64
                child 11, ecl_epochs: int64
                child 12, batch_size: int64
                child 13, lr: double
                child 14, lambda_ecl: double
                child 15, num_bins: int64
                child 16, skip_pseudocal: bool
                child 17, n_train: int64
                child 18, n_test: int64
              models: struct<lenet5: struct<name: string, ece_uncalibrated: double, ece_ecl: double, ece_pseudocal: null,  (... 344 chars omitted)
                child 0, lenet5: struct<name: string, ece_uncalibrated: double, ece_ecl: double, ece_pseudocal: null, improvement_abs (... 34 chars omitted)
                    child 0, name: string
                    child 1, ece_uncalibrated: double
                    child 2, ece_ecl: double
                    child 3, ece_pseudocal: null
                    child 4, improvement_abs: double
                    child 5, improvement_pct: double
                child 1, resnet20: struct<name: string, ece_uncalibrated: double, ece_ecl: double, ece_pseudocal: null, improvement_abs (... 34 chars omitted)
                    child 0, name: string
                    child 1, ece_uncalibrated: double
                    child 2, ece_ecl: double
                    child 3, ece_pseudocal: null
                    child 4, improvement_abs: double
                    child 5, improvement_pct: double
                child 2, densenet40: struct<name: string, ece_uncalibrated: double, ece_ecl: double, ece_pseudocal: null, improvement_abs (... 34 chars omitted)
                    child 0, name: string
                    child 1, ece_uncalibrated: double
                    child 2, ece_ecl: double
                    child 3, ece_pseudocal: null
                    child 4, improvement_abs: double
                    child 5, improvement_pct: double
              to
              {'config': {'n': Value('int64'), 'stub': Value('bool'), 'smoke': Value('bool'), 'dump_raw': Value('int64'), 'model': Value('null'), 'dtype': Value('string'), 'out': Value('string'), 'seed': Value('int64'), 'upload_repo': Value('string'), 'models': Value('string'), 'epochs': Value('int64'), 'ecl_epochs': Value('int64'), 'batch_size': Value('int64'), 'lr': Value('float64'), 'lambda_ecl': Value('float64'), 'num_bins': Value('int64'), 'skip_pseudocal': Value('bool'), 'n_train': Value('int64'), 'n_test': Value('int64')}, 'device': Value('string'), 'models': {'lenet5': {'name': Value('string'), 'ece_uncalibrated': Value('float64'), 'ece_ecl': Value('float64'), 'ece_pseudocal': Value('null'), 'improvement_abs': Value('float64'), 'improvement_pct': Value('float64')}, 'resnet20': {'name': Value('string'), 'ece_uncalibrated': Value('float64'), 'ece_ecl': Value('float64'), 'ece_pseudocal': Value('null'), 'improvement_abs': Value('float64'), 'improvement_pct': Value('float64')}, 'densenet40': {'name': Value('string'), 'ece_uncalibrated': Value('float64'), 'ece_ecl': Value('float64'), 'ece_pseudocal': Value('null'), 'improvement_abs': Value('float64'), 'improvement_pct': Value('float64')}}}
              because column names don't match