Datasets:

---

Kiy-K

/

repro-mem-t-scaled-inference

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
benchmark: string
checkpoint: string
hardware: string
job_id: string
num_examples: int64
rerun_mean_f1: double
released_predictions_same_subset_mean_f1: double
mean_approx_inference_tokens: double
mean_retrieval_steps: double
question_loop_wall_seconds: double
official_max_retrieval_steps: int64
official_context_length: int64
notes: string
retrieval_steps: int64
approx_inference_tokens: int64
released_prediction: string
gold: string
rerun_f1: double
question_id: string
wall_seconds: double
rerun_prediction: string
index: int64
released_f1: double
to
{'index': Value('int64'), 'question_id': Value('string'), 'gold': Value('string'), 'released_prediction': Value('string'), 'rerun_prediction': Value('string'), 'released_f1': Value('float64'), 'rerun_f1': Value('float64'), 'retrieval_steps': Value('int64'), 'approx_inference_tokens': Value('int64'), 'wall_seconds': Value('float64')}
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 478, 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
              benchmark: string
              checkpoint: string
              hardware: string
              job_id: string
              num_examples: int64
              rerun_mean_f1: double
              released_predictions_same_subset_mean_f1: double
              mean_approx_inference_tokens: double
              mean_retrieval_steps: double
              question_loop_wall_seconds: double
              official_max_retrieval_steps: int64
              official_context_length: int64
              notes: string
              retrieval_steps: int64
              approx_inference_tokens: int64
              released_prediction: string
              gold: string
              rerun_f1: double
              question_id: string
              wall_seconds: double
              rerun_prediction: string
              index: int64
              released_f1: double
              to
              {'index': Value('int64'), 'question_id': Value('string'), 'gold': Value('string'), 'released_prediction': Value('string'), 'rerun_prediction': Value('string'), 'released_f1': Value('float64'), 'rerun_f1': Value('float64'), 'retrieval_steps': Value('int64'), 'approx_inference_tokens': Value('int64'), 'wall_seconds': Value('float64')}
              because column names don't match