Datasets:

---

malomalom

/

spacehpc-representation-capacity-full24-models-v1

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
evaluation_batches: double
optimizer_step: int64
train_mse_since_previous_eval: double
val_cosine_1step: double
val_mse_1step: double
val_mse_action_shuffled: double
val_persistence_mse: double
val_rollout_h1_mse: double
val_rollout_h2_mse: double
val_rollout_h3_mse: double
tune_episode_count: int64
tune_ids_sha256: string
smoke: bool
fit_ids_sha256: string
best_checkpoint: string
task: string
history_path: string
optimizer_steps: int64
protocol_id: string
parent_protocol_sha256: string
kind: string
eval_every: int64
scientific_result_payload: bool
batch_size: int64
layer: int64
seed: int64
parameter_count: int64
data_id: string
history_records: int64
capacity: string
implementation_id: string
fit_episode_count: int64
to
{'batch_size': Value('int64'), 'best_checkpoint': Value('string'), 'capacity': Value('string'), 'data_id': Value('string'), 'eval_every': Value('int64'), 'fit_episode_count': Value('int64'), 'fit_ids_sha256': Value('string'), 'history_path': Value('string'), 'history_records': Value('int64'), 'implementation_id': Value('string'), 'kind': Value('string'), 'layer': Value('int64'), 'optimizer_steps': Value('int64'), 'parameter_count': Value('int64'), 'parent_protocol_sha256': Value('string'), 'protocol_id': Value('string'), 'scientific_result_payload': Value('bool'), 'seed': Value('int64'), 'smoke': Value('bool'), 'task': Value('string'), 'tune_episode_count': Value('int64'), 'tune_ids_sha256': 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 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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
              evaluation_batches: double
              optimizer_step: int64
              train_mse_since_previous_eval: double
              val_cosine_1step: double
              val_mse_1step: double
              val_mse_action_shuffled: double
              val_persistence_mse: double
              val_rollout_h1_mse: double
              val_rollout_h2_mse: double
              val_rollout_h3_mse: double
              tune_episode_count: int64
              tune_ids_sha256: string
              smoke: bool
              fit_ids_sha256: string
              best_checkpoint: string
              task: string
              history_path: string
              optimizer_steps: int64
              protocol_id: string
              parent_protocol_sha256: string
              kind: string
              eval_every: int64
              scientific_result_payload: bool
              batch_size: int64
              layer: int64
              seed: int64
              parameter_count: int64
              data_id: string
              history_records: int64
              capacity: string
              implementation_id: string
              fit_episode_count: int64
              to
              {'batch_size': Value('int64'), 'best_checkpoint': Value('string'), 'capacity': Value('string'), 'data_id': Value('string'), 'eval_every': Value('int64'), 'fit_episode_count': Value('int64'), 'fit_ids_sha256': Value('string'), 'history_path': Value('string'), 'history_records': Value('int64'), 'implementation_id': Value('string'), 'kind': Value('string'), 'layer': Value('int64'), 'optimizer_steps': Value('int64'), 'parameter_count': Value('int64'), 'parent_protocol_sha256': Value('string'), 'protocol_id': Value('string'), 'scientific_result_payload': Value('bool'), 'seed': Value('int64'), 'smoke': Value('bool'), 'task': Value('string'), 'tune_episode_count': Value('int64'), 'tune_ids_sha256': Value('string')}
              because column names don't match