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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
base_seed: int64
created_at: timestamp[s]
dataset_path_in_repo: string
generation_seconds: double
mode: string
output_repo: string
path_in_repo: string
run_id: string
shard_count: int64
shard_index: int64
shard_name: string
shard_seed: int64
summary: struct<acceptance_rate: double, accepted_samples: int64, accepted_samples_per_second: double, accept (... 1351 chars omitted)
  child 0, acceptance_rate: double
  child 1, accepted_samples: int64
  child 2, accepted_samples_per_second: double
  child 3, accepted_system_counts: struct<2: int64, 3: int64, 4: int64, 5: int64, 6: int64>
      child 0, 2: int64
      child 1, 3: int64
      child 2, 4: int64
      child 3, 5: int64
      child 4, 6: int64
  child 4, attempts: int64
  child 5, attempts_per_second: double
  child 6, elapsed_seconds: double
  child 7, failures: struct<crop_risk: int64, multi_page: int64, render_worker_crashed: int64, target_system_2_got_1: int (... 654 chars omitted)
      child 0, crop_risk: int64
      child 1, multi_page: int64
      child 2, render_worker_crashed: int64
      child 3, target_system_2_got_1: int64
      child 4, target_system_2_got_3: int64
      child 5, target_system_2_got_4: int64
      child 6, target_system_3_got_1: int64
      child 7, target_system_3_got_2: int64
      child 8, target_system_3_got_4: int64
      child 9, target_system_3_got_5: int64
      child 10, target_system_4_got_2: int64
      child 11, target_system_4_got_3: int64
      child 12, target_system_4_got_5: i
...
64
      child 20, target_system_6_got_4: int64
      child 21, target_system_6_got_5: int64
      child 22, target_system_6_got_7: int64
      child 23, target_system_6_got_8: int64
      child 24, target_system_6_got_9: int64
      child 25, token_length: int64
  child 8, generator_version: string
  child 9, notation_feature_counts: struct<articulation_marks: int64, beam_marks: int64, chord_fields: int64, field_tokens: int64, note_ (... 71 chars omitted)
      child 0, articulation_marks: int64
      child 1, beam_marks: int64
      child 2, chord_fields: int64
      child 3, field_tokens: int64
      child 4, note_tokens: int64
      child 5, rest_tokens: int64
      child 6, slur_marks: int64
      child 7, tie_marks: int64
  child 10, notation_feature_rates_per_note: struct<articulation_marks: double, beam_marks: double, slur_marks: double, tie_marks: double>
      child 0, articulation_marks: double
      child 1, beam_marks: double
      child 2, slur_marks: double
      child 3, tie_marks: double
  child 11, sample_id_prefix: string
  child 12, token_length: struct<max: int64, mean: double, min: int64>
      child 0, max: int64
      child 1, mean: double
      child 2, min: int64
target_samples: int64
total_samples: int64
_split: null
_format_type: null
_data_files: list<item: struct<filename: string>>
  child 0, item: struct<filename: string>
      child 0, filename: string
_format_kwargs: struct<>
_fingerprint: string
_format_columns: null
_output_all_columns: bool
to
{'_data_files': List({'filename': Value('string')}), '_fingerprint': Value('string'), '_format_columns': Value('null'), '_format_kwargs': {}, '_format_type': Value('null'), '_output_all_columns': Value('bool'), '_split': Value('null')}
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
              base_seed: int64
              created_at: timestamp[s]
              dataset_path_in_repo: string
              generation_seconds: double
              mode: string
              output_repo: string
              path_in_repo: string
              run_id: string
              shard_count: int64
              shard_index: int64
              shard_name: string
              shard_seed: int64
              summary: struct<acceptance_rate: double, accepted_samples: int64, accepted_samples_per_second: double, accept (... 1351 chars omitted)
                child 0, acceptance_rate: double
                child 1, accepted_samples: int64
                child 2, accepted_samples_per_second: double
                child 3, accepted_system_counts: struct<2: int64, 3: int64, 4: int64, 5: int64, 6: int64>
                    child 0, 2: int64
                    child 1, 3: int64
                    child 2, 4: int64
                    child 3, 5: int64
                    child 4, 6: int64
                child 4, attempts: int64
                child 5, attempts_per_second: double
                child 6, elapsed_seconds: double
                child 7, failures: struct<crop_risk: int64, multi_page: int64, render_worker_crashed: int64, target_system_2_got_1: int (... 654 chars omitted)
                    child 0, crop_risk: int64
                    child 1, multi_page: int64
                    child 2, render_worker_crashed: int64
                    child 3, target_system_2_got_1: int64
                    child 4, target_system_2_got_3: int64
                    child 5, target_system_2_got_4: int64
                    child 6, target_system_3_got_1: int64
                    child 7, target_system_3_got_2: int64
                    child 8, target_system_3_got_4: int64
                    child 9, target_system_3_got_5: int64
                    child 10, target_system_4_got_2: int64
                    child 11, target_system_4_got_3: int64
                    child 12, target_system_4_got_5: i
              ...
              64
                    child 20, target_system_6_got_4: int64
                    child 21, target_system_6_got_5: int64
                    child 22, target_system_6_got_7: int64
                    child 23, target_system_6_got_8: int64
                    child 24, target_system_6_got_9: int64
                    child 25, token_length: int64
                child 8, generator_version: string
                child 9, notation_feature_counts: struct<articulation_marks: int64, beam_marks: int64, chord_fields: int64, field_tokens: int64, note_ (... 71 chars omitted)
                    child 0, articulation_marks: int64
                    child 1, beam_marks: int64
                    child 2, chord_fields: int64
                    child 3, field_tokens: int64
                    child 4, note_tokens: int64
                    child 5, rest_tokens: int64
                    child 6, slur_marks: int64
                    child 7, tie_marks: int64
                child 10, notation_feature_rates_per_note: struct<articulation_marks: double, beam_marks: double, slur_marks: double, tie_marks: double>
                    child 0, articulation_marks: double
                    child 1, beam_marks: double
                    child 2, slur_marks: double
                    child 3, tie_marks: double
                child 11, sample_id_prefix: string
                child 12, token_length: struct<max: int64, mean: double, min: int64>
                    child 0, max: int64
                    child 1, mean: double
                    child 2, min: int64
              target_samples: int64
              total_samples: int64
              _split: null
              _format_type: null
              _data_files: list<item: struct<filename: string>>
                child 0, item: struct<filename: string>
                    child 0, filename: string
              _format_kwargs: struct<>
              _fingerprint: string
              _format_columns: null
              _output_all_columns: bool
              to
              {'_data_files': List({'filename': Value('string')}), '_fingerprint': Value('string'), '_format_columns': Value('null'), '_format_kwargs': {}, '_format_type': Value('null'), '_output_all_columns': Value('bool'), '_split': Value('null')}
              because column names don't match

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