Datasets:

---

ProCreations

/

minima-results

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
kernel: struct<cpu_extension: bool, cuda_triton: bool, cpu_dynamic_int8: bool>
  child 0, cpu_extension: bool
  child 1, cuda_triton: bool
  child 2, cpu_dynamic_int8: bool
threads: int64
platform: string
processor: string
measurements: list<item: struct<model: string, sequence_length: int64, median_ms: double, tokens_per_second: doubl (... 51 chars omitted)
  child 0, item: struct<model: string, sequence_length: int64, median_ms: double, tokens_per_second: double, load_rss (... 39 chars omitted)
      child 0, model: string
      child 1, sequence_length: int64
      child 2, median_ms: double
      child 3, tokens_per_second: double
      child 4, load_rss_delta_mb: double
      child 5, peak_rss_mb: double
seed: int64
results: list<item: struct<steps: int64, learning_rate: double, matthews: double>>
  child 0, item: struct<steps: int64, learning_rate: double, matthews: double>
      child 0, steps: int64
      child 1, learning_rate: double
      child 2, matthews: double
best: struct<steps: int64, learning_rate: double, matthews: double>
  child 0, steps: int64
  child 1, learning_rate: double
  child 2, matthews: double
model: string
to
{'model': Value('string'), 'seed': Value('int64'), 'results': List({'steps': Value('int64'), 'learning_rate': Value('float64'), 'matthews': Value('float64')}), 'best': {'steps': Value('int64'), 'learning_rate': Value('float64'), 'matthews': 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 483, 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              kernel: struct<cpu_extension: bool, cuda_triton: bool, cpu_dynamic_int8: bool>
                child 0, cpu_extension: bool
                child 1, cuda_triton: bool
                child 2, cpu_dynamic_int8: bool
              threads: int64
              platform: string
              processor: string
              measurements: list<item: struct<model: string, sequence_length: int64, median_ms: double, tokens_per_second: doubl (... 51 chars omitted)
                child 0, item: struct<model: string, sequence_length: int64, median_ms: double, tokens_per_second: double, load_rss (... 39 chars omitted)
                    child 0, model: string
                    child 1, sequence_length: int64
                    child 2, median_ms: double
                    child 3, tokens_per_second: double
                    child 4, load_rss_delta_mb: double
                    child 5, peak_rss_mb: double
              seed: int64
              results: list<item: struct<steps: int64, learning_rate: double, matthews: double>>
                child 0, item: struct<steps: int64, learning_rate: double, matthews: double>
                    child 0, steps: int64
                    child 1, learning_rate: double
                    child 2, matthews: double
              best: struct<steps: int64, learning_rate: double, matthews: double>
                child 0, steps: int64
                child 1, learning_rate: double
                child 2, matthews: double
              model: string
              to
              {'model': Value('string'), 'seed': Value('int64'), 'results': List({'steps': Value('int64'), 'learning_rate': Value('float64'), 'matthews': Value('float64')}), 'best': {'steps': Value('int64'), 'learning_rate': Value('float64'), 'matthews': Value('float64')}}
              because column names don't match