Datasets:

---

wuff-mann

/

CIDM-v3-SCS-S2A0-Data

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
architecture_name: string
architecture_changed_in_S3A1: bool
modules: list<item: string>
  child 0, item: string
training_contract: struct<optimizer_state_persistent_across_epochs: bool, rollout_curriculum: list<item: int64>, persis (... 111 chars omitted)
  child 0, optimizer_state_persistent_across_epochs: bool
  child 1, rollout_curriculum: list<item: int64>
      child 0, item: int64
  child 2, persistence_relative_skill: bool
  child 3, increment_loss: bool
  child 4, spectral_and_variance_losses: bool
  child 5, wave_domain_losses: bool
grid: string
base_time_step_hours: int64
maximum_training_horizon_steps: int64
history_steps: int64
patch_size: int64
removed_from_v3: list<item: string>
  child 0, item: string
amp: bool
global_normalization: string
rollout_schedule: list<item: int64>
  child 0, item: int64
model_config: struct<name: string, channels: int64, history_steps: int64, latent_dim: int64, hidden_dim: int64, co (... 17 chars omitted)
  child 0, name: string
  child 1, channels: int64
  child 2, history_steps: int64
  child 3, latent_dim: int64
  child 4, hidden_dim: int64
  child 5, core_blocks: int64
checkpoint: string
precision: string
tf32: bool
to
{'architecture_name': Value('string'), 'model_config': {'name': Value('string'), 'channels': Value('int64'), 'history_steps': Value('int64'), 'latent_dim': Value('int64'), 'hidden_dim': Value('int64'), 'core_blocks': Value('int64')}, 'precision': Value('string'), 'amp': Value('bool'), 'tf32': Value('bool'), 'grid': Value('string'), 'history_steps': Value('int64'), 'patch_size': Value('int64'), 'rollout_schedule': List(Value('int64')), 'global_normalization': Value('string'), 'checkpoint': Value('string'), 'removed_from_v3': List(Value('string'))}
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
              architecture_name: string
              architecture_changed_in_S3A1: bool
              modules: list<item: string>
                child 0, item: string
              training_contract: struct<optimizer_state_persistent_across_epochs: bool, rollout_curriculum: list<item: int64>, persis (... 111 chars omitted)
                child 0, optimizer_state_persistent_across_epochs: bool
                child 1, rollout_curriculum: list<item: int64>
                    child 0, item: int64
                child 2, persistence_relative_skill: bool
                child 3, increment_loss: bool
                child 4, spectral_and_variance_losses: bool
                child 5, wave_domain_losses: bool
              grid: string
              base_time_step_hours: int64
              maximum_training_horizon_steps: int64
              history_steps: int64
              patch_size: int64
              removed_from_v3: list<item: string>
                child 0, item: string
              amp: bool
              global_normalization: string
              rollout_schedule: list<item: int64>
                child 0, item: int64
              model_config: struct<name: string, channels: int64, history_steps: int64, latent_dim: int64, hidden_dim: int64, co (... 17 chars omitted)
                child 0, name: string
                child 1, channels: int64
                child 2, history_steps: int64
                child 3, latent_dim: int64
                child 4, hidden_dim: int64
                child 5, core_blocks: int64
              checkpoint: string
              precision: string
              tf32: bool
              to
              {'architecture_name': Value('string'), 'model_config': {'name': Value('string'), 'channels': Value('int64'), 'history_steps': Value('int64'), 'latent_dim': Value('int64'), 'hidden_dim': Value('int64'), 'core_blocks': Value('int64')}, 'precision': Value('string'), 'amp': Value('bool'), 'tf32': Value('bool'), 'grid': Value('string'), 'history_steps': Value('int64'), 'patch_size': Value('int64'), 'rollout_schedule': List(Value('int64')), 'global_normalization': Value('string'), 'checkpoint': Value('string'), 'removed_from_v3': List(Value('string'))}
              because column names don't match