Datasets:

---

icarus112

/

ce-checkpoints

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
model: string
cpu_only: bool
total_planned: int64
episodes_seen: int64
best: struct<agentic_ppl: double, step: int64>
  child 0, agentic_ppl: double
  child 1, step: int64
final: struct<tool_selection_accuracy: double, induction_accuracy: double, agentic_ppl: double, latency_ms_ (... 97 chars omitted)
  child 0, tool_selection_accuracy: double
  child 1, induction_accuracy: double
  child 2, agentic_ppl: double
  child 3, latency_ms_mean: double
  child 4, latency_ms_max: double
  child 5, episodes_seen: int64
  child 6, vocab_size: int64
  child 7, ppm_tables: int64
eval_history: list<item: struct<tool_selection_accuracy: double, induction_accuracy: double, agentic_ppl: double,  (... 179 chars omitted)
  child 0, item: struct<tool_selection_accuracy: double, induction_accuracy: double, agentic_ppl: double, latency_ms_ (... 167 chars omitted)
      child 0, tool_selection_accuracy: double
      child 1, induction_accuracy: double
      child 2, agentic_ppl: double
      child 3, latency_ms_mean: double
      child 4, latency_ms_max: double
      child 5, episodes_seen: int64
      child 6, vocab_size: int64
      child 7, ppm_tables: int64
      child 8, step: int64
      child 9, total: int64
      child 10, phase: string
      child 11, wall_s: double
      child 12, best: bool
output_dir: string
checkpoint: string
log: string
phases: list<item: string>
  child 0, item: string
induction_accuracy: double
vocab_size: int64
ppm_tables: int64
total: int64
phase: string
agentic_ppl: double
latency_ms_max: double
tool_selection_accuracy: double
step: int64
latency_ms_mean: double
wall_s: double
to
{'agentic_ppl': Value('float64'), 'best': Value('bool'), 'episodes_seen': Value('int64'), 'induction_accuracy': Value('float64'), 'latency_ms_max': Value('float64'), 'latency_ms_mean': Value('float64'), 'phase': Value('string'), 'ppm_tables': Value('int64'), 'step': Value('int64'), 'tool_selection_accuracy': Value('float64'), 'total': Value('int64'), 'vocab_size': Value('int64'), 'wall_s': 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
              model: string
              cpu_only: bool
              total_planned: int64
              episodes_seen: int64
              best: struct<agentic_ppl: double, step: int64>
                child 0, agentic_ppl: double
                child 1, step: int64
              final: struct<tool_selection_accuracy: double, induction_accuracy: double, agentic_ppl: double, latency_ms_ (... 97 chars omitted)
                child 0, tool_selection_accuracy: double
                child 1, induction_accuracy: double
                child 2, agentic_ppl: double
                child 3, latency_ms_mean: double
                child 4, latency_ms_max: double
                child 5, episodes_seen: int64
                child 6, vocab_size: int64
                child 7, ppm_tables: int64
              eval_history: list<item: struct<tool_selection_accuracy: double, induction_accuracy: double, agentic_ppl: double,  (... 179 chars omitted)
                child 0, item: struct<tool_selection_accuracy: double, induction_accuracy: double, agentic_ppl: double, latency_ms_ (... 167 chars omitted)
                    child 0, tool_selection_accuracy: double
                    child 1, induction_accuracy: double
                    child 2, agentic_ppl: double
                    child 3, latency_ms_mean: double
                    child 4, latency_ms_max: double
                    child 5, episodes_seen: int64
                    child 6, vocab_size: int64
                    child 7, ppm_tables: int64
                    child 8, step: int64
                    child 9, total: int64
                    child 10, phase: string
                    child 11, wall_s: double
                    child 12, best: bool
              output_dir: string
              checkpoint: string
              log: string
              phases: list<item: string>
                child 0, item: string
              induction_accuracy: double
              vocab_size: int64
              ppm_tables: int64
              total: int64
              phase: string
              agentic_ppl: double
              latency_ms_max: double
              tool_selection_accuracy: double
              step: int64
              latency_ms_mean: double
              wall_s: double
              to
              {'agentic_ppl': Value('float64'), 'best': Value('bool'), 'episodes_seen': Value('int64'), 'induction_accuracy': Value('float64'), 'latency_ms_max': Value('float64'), 'latency_ms_mean': Value('float64'), 'phase': Value('string'), 'ppm_tables': Value('int64'), 'step': Value('int64'), 'tool_selection_accuracy': Value('float64'), 'total': Value('int64'), 'vocab_size': Value('int64'), 'wall_s': Value('float64')}
              because column names don't match