Datasets:

---

explcre

/

scdistill-cluster-artifacts

like 0

Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<realtrain: struct<best_step: int64, best_val: double, final_val: double, n_evals: int64, validated: bool, val_trace: list<item: double>, val_metric: string, test_trace: null, val_alt_trace: null, val_alt_metric: string, early_stopped: bool, stop_step: int64, ceiling: int64, undertrained: bool, ema_decay: null, ema_val_trace: null, ema_test_trace: null, ema_final_test: null, ema_best_step: null>, distilled_plus_wkdf: struct<best_step: int64, best_val: double, final_val: double, n_evals: int64, validated: bool, val_trace: list<item: double>, val_metric: string, test_trace: null, val_alt_trace: null, val_alt_metric: string, early_stopped: bool, stop_step: int64, ceiling: int64, undertrained: bool, ema_decay: null, ema_val_trace: null, ema_test_trace: null, ema_final_test: null, ema_best_step: null>>
to
{'distilled': {'best_step': Value('int64'), 'best_val': Value('float64'), 'final_val': Value('float64'), 'n_evals': Value('int64'), 'validated': Value('bool'), 'val_trace': List(Value('float64')), 'val_metric': Value('string'), 'test_trace': Value('null'), 'val_alt_trace': Value('null'), 'val_alt_metric': Value('string'), 'early_stopped': Value('bool'), 'stop_step': Value('int64'), 'ceiling': Value('int64'), 'undertrained': Value('bool'), 'ema_decay': Value('null'), 'ema_val_trace': Value('null'), 'ema_test_trace': Value('null'), 'ema_final_test': Value('null'), 'ema_best_step': Value('null')}, 'distilled_wkdf': {'best_step': Value('int64'), 'best_val': Value('float64'), 'final_val': Value('float64'), 'n_evals': Value('int64'), 'validated': Value('bool'), 'val_trace': List(Value('float64')), 'val_metric': Value('string'), 'test_trace': Value('null'), 'val_alt_trace': Value('null'), 'val_alt_metric': Value('string'), 'early_stopped': Value('bool'), 'stop_step': Value('int64'), 'ceiling': Value('int64'), 'undertrained': Value('bool'), 'ema_decay': Value('null'), 'ema_val_trace': Value('null'), 'ema_test_trace': Value('null'), 'ema_final_test': Value('null'), 'ema_best_step': Value('null')}, 'distilled_plus_wkdf_denoise': {'best_step': Value('int64'), 'best_val': Value('float64'), 'final_val': Value('float64'), 'n_evals': Value('int64'), 'validated': Value('bool'), 'val_trace': List(Value('float64')), 'val_metric': Value('string'), 'test_trace': Value('null'), 'val_alt_trace': Value('null'), 'val_alt_metric': Value('string'), 'early_stopped': Value('bool'), 'stop_step': Value('int64'), 'ceiling': Value('int64'), 'undertrained': Value('bool'), 'ema_decay': Value('null'), 'ema_val_trace': Value('null'), 'ema_test_trace': Value('null'), 'ema_final_test': Value('null'), 'ema_best_step': Value('null')}}
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 2303, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2149, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<realtrain: struct<best_step: int64, best_val: double, final_val: double, n_evals: int64, validated: bool, val_trace: list<item: double>, val_metric: string, test_trace: null, val_alt_trace: null, val_alt_metric: string, early_stopped: bool, stop_step: int64, ceiling: int64, undertrained: bool, ema_decay: null, ema_val_trace: null, ema_test_trace: null, ema_final_test: null, ema_best_step: null>, distilled_plus_wkdf: struct<best_step: int64, best_val: double, final_val: double, n_evals: int64, validated: bool, val_trace: list<item: double>, val_metric: string, test_trace: null, val_alt_trace: null, val_alt_metric: string, early_stopped: bool, stop_step: int64, ceiling: int64, undertrained: bool, ema_decay: null, ema_val_trace: null, ema_test_trace: null, ema_final_test: null, ema_best_step: null>>
              to
              {'distilled': {'best_step': Value('int64'), 'best_val': Value('float64'), 'final_val': Value('float64'), 'n_evals': Value('int64'), 'validated': Value('bool'), 'val_trace': List(Value('float64')), 'val_metric': Value('string'), 'test_trace': Value('null'), 'val_alt_trace': Value('null'), 'val_alt_metric': Value('string'), 'early_stopped': Value('bool'), 'stop_step': Value('int64'), 'ceiling': Value('int64'), 'undertrained': Value('bool'), 'ema_decay': Value('null'), 'ema_val_trace': Value('null'), 'ema_test_trace': Value('null'), 'ema_final_test': Value('null'), 'ema_best_step': Value('null')}, 'distilled_wkdf': {'best_step': Value('int64'), 'best_val': Value('float64'), 'final_val': Value('float64'), 'n_evals': Value('int64'), 'validated': Value('bool'), 'val_trace': List(Value('float64')), 'val_metric': Value('string'), 'test_trace': Value('null'), 'val_alt_trace': Value('null'), 'val_alt_metric': Value('string'), 'early_stopped': Value('bool'), 'stop_step': Value('int64'), 'ceiling': Value('int64'), 'undertrained': Value('bool'), 'ema_decay': Value('null'), 'ema_val_trace': Value('null'), 'ema_test_trace': Value('null'), 'ema_final_test': Value('null'), 'ema_best_step': Value('null')}, 'distilled_plus_wkdf_denoise': {'best_step': Value('int64'), 'best_val': Value('float64'), 'final_val': Value('float64'), 'n_evals': Value('int64'), 'validated': Value('bool'), 'val_trace': List(Value('float64')), 'val_metric': Value('string'), 'test_trace': Value('null'), 'val_alt_trace': Value('null'), 'val_alt_metric': Value('string'), 'early_stopped': Value('bool'), 'stop_step': Value('int64'), 'ceiling': Value('int64'), 'undertrained': Value('bool'), 'ema_decay': Value('null'), 'ema_val_trace': Value('null'), 'ema_test_trace': Value('null'), 'ema_final_test': Value('null'), 'ema_best_step': Value('null')}}