Datasets:

---

latticetower

/

gseflow-repro-artifacts

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
dataset: string
config: struct<loader: null, horizon: int64, stride: int64, max_windows: int64, max_trials: null>
  child 0, loader: null
  child 1, horizon: int64
  child 2, stride: int64
  child 3, max_windows: int64
  child 4, max_trials: null
common: struct<epochs: int64, lr: double, hidden_dim: int64, n_layers: int64, n_sample_steps: int64, seed: i (... 22 chars omitted)
  child 0, epochs: int64
  child 1, lr: double
  child 2, hidden_dim: int64
  child 3, n_layers: int64
  child 4, n_sample_steps: int64
  child 5, seed: int64
  child 6, max_eval: int64
n_windows: int64
n_train: int64
n_test: int64
scale: double
deterministic_baseline: struct<train_loss_history: list<item: double>, test_rmse_mean: double, test_rmse_std: double, train_ (... 16 chars omitted)
  child 0, train_loss_history: list<item: double>
      child 0, item: double
  child 1, test_rmse_mean: double
  child 2, test_rmse_std: double
  child 3, train_seconds: double
gse_flow: struct<train_loss_history: list<item: double>, test_rmse_mean: double, test_rmse_std: double, train_ (... 16 chars omitted)
  child 0, train_loss_history: list<item: double>
      child 0, item: double
  child 1, test_rmse_mean: double
  child 2, test_rmse_std: double
  child 3, train_seconds: double
improvement_pct: double
md17: struct<dataset: string, config: struct<loader: null, horizon: int64, stride: int64, max_windows: int (... 513 chars omitted)
  child 0, dataset: string
  child 1, config: struct<loader: null, horizon: int64,
...
 chars omitted)
  child 0, dataset: string
  child 1, config: struct<loader: null, horizon: int64, stride: int64, max_windows: int64, max_trials: null>
      child 0, loader: null
      child 1, horizon: int64
      child 2, stride: int64
      child 3, max_windows: int64
      child 4, max_trials: null
  child 2, common: struct<epochs: int64, lr: double, hidden_dim: int64, n_layers: int64, n_sample_steps: int64, seed: i (... 22 chars omitted)
      child 0, epochs: int64
      child 1, lr: double
      child 2, hidden_dim: int64
      child 3, n_layers: int64
      child 4, n_sample_steps: int64
      child 5, seed: int64
      child 6, max_eval: int64
  child 3, n_windows: int64
  child 4, n_train: int64
  child 5, n_test: int64
  child 6, scale: double
  child 7, deterministic_baseline: struct<train_loss_history: list<item: double>, test_rmse_mean: double, test_rmse_std: double, train_ (... 16 chars omitted)
      child 0, train_loss_history: list<item: double>
          child 0, item: double
      child 1, test_rmse_mean: double
      child 2, test_rmse_std: double
      child 3, train_seconds: double
  child 8, gse_flow: struct<train_loss_history: list<item: double>, test_rmse_mean: double, test_rmse_std: double, train_ (... 16 chars omitted)
      child 0, train_loss_history: list<item: double>
          child 0, item: double
      child 1, test_rmse_mean: double
      child 2, test_rmse_std: double
      child 3, train_seconds: double
  child 9, improvement_pct: double
to
{'md17': {'dataset': Value('string'), 'config': {'loader': Value('null'), 'horizon': Value('int64'), 'stride': Value('int64'), 'max_windows': Value('int64'), 'max_trials': Value('null')}, 'common': {'epochs': Value('int64'), 'lr': Value('float64'), 'hidden_dim': Value('int64'), 'n_layers': Value('int64'), 'n_sample_steps': Value('int64'), 'seed': Value('int64'), 'max_eval': Value('int64')}, 'n_windows': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'scale': Value('float64'), 'deterministic_baseline': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'gse_flow': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'improvement_pct': Value('float64')}, 'md22': {'dataset': Value('string'), 'config': {'loader': Value('null'), 'horizon': Value('int64'), 'stride': Value('int64'), 'max_windows': Value('int64'), 'max_trials': Value('null')}, 'common': {'epochs': Value('int64'), 'lr': Value('float64'), 'hidden_dim': Value('int64'), 'n_layers': Value('int64'), 'n_sample_steps': Value('int64'), 'seed': Value('int64'), 'max_eval': Value('int64')}, 'n_windows': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'scale': Value('float64'), 'deterministic_baseline': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'gse_flow': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'improvement_pct': Value('float64')}, 'cmu': {'dataset': Value('string'), 'config': {'loader': Value('null'), 'horizon': Value('int64'), 'stride': Value('int64'), 'max_windows': Value('int64'), 'max_trials': Value('null')}, 'common': {'epochs': Value('int64'), 'lr': Value('float64'), 'hidden_dim': Value('int64'), 'n_layers': Value('int64'), 'n_sample_steps': Value('int64'), 'seed': Value('int64'), 'max_eval': Value('int64')}, 'n_windows': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'scale': Value('float64'), 'deterministic_baseline': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'gse_flow': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'improvement_pct': Value('float64')}}
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
              dataset: string
              config: struct<loader: null, horizon: int64, stride: int64, max_windows: int64, max_trials: null>
                child 0, loader: null
                child 1, horizon: int64
                child 2, stride: int64
                child 3, max_windows: int64
                child 4, max_trials: null
              common: struct<epochs: int64, lr: double, hidden_dim: int64, n_layers: int64, n_sample_steps: int64, seed: i (... 22 chars omitted)
                child 0, epochs: int64
                child 1, lr: double
                child 2, hidden_dim: int64
                child 3, n_layers: int64
                child 4, n_sample_steps: int64
                child 5, seed: int64
                child 6, max_eval: int64
              n_windows: int64
              n_train: int64
              n_test: int64
              scale: double
              deterministic_baseline: struct<train_loss_history: list<item: double>, test_rmse_mean: double, test_rmse_std: double, train_ (... 16 chars omitted)
                child 0, train_loss_history: list<item: double>
                    child 0, item: double
                child 1, test_rmse_mean: double
                child 2, test_rmse_std: double
                child 3, train_seconds: double
              gse_flow: struct<train_loss_history: list<item: double>, test_rmse_mean: double, test_rmse_std: double, train_ (... 16 chars omitted)
                child 0, train_loss_history: list<item: double>
                    child 0, item: double
                child 1, test_rmse_mean: double
                child 2, test_rmse_std: double
                child 3, train_seconds: double
              improvement_pct: double
              md17: struct<dataset: string, config: struct<loader: null, horizon: int64, stride: int64, max_windows: int (... 513 chars omitted)
                child 0, dataset: string
                child 1, config: struct<loader: null, horizon: int64,
              ...
               chars omitted)
                child 0, dataset: string
                child 1, config: struct<loader: null, horizon: int64, stride: int64, max_windows: int64, max_trials: null>
                    child 0, loader: null
                    child 1, horizon: int64
                    child 2, stride: int64
                    child 3, max_windows: int64
                    child 4, max_trials: null
                child 2, common: struct<epochs: int64, lr: double, hidden_dim: int64, n_layers: int64, n_sample_steps: int64, seed: i (... 22 chars omitted)
                    child 0, epochs: int64
                    child 1, lr: double
                    child 2, hidden_dim: int64
                    child 3, n_layers: int64
                    child 4, n_sample_steps: int64
                    child 5, seed: int64
                    child 6, max_eval: int64
                child 3, n_windows: int64
                child 4, n_train: int64
                child 5, n_test: int64
                child 6, scale: double
                child 7, deterministic_baseline: struct<train_loss_history: list<item: double>, test_rmse_mean: double, test_rmse_std: double, train_ (... 16 chars omitted)
                    child 0, train_loss_history: list<item: double>
                        child 0, item: double
                    child 1, test_rmse_mean: double
                    child 2, test_rmse_std: double
                    child 3, train_seconds: double
                child 8, gse_flow: struct<train_loss_history: list<item: double>, test_rmse_mean: double, test_rmse_std: double, train_ (... 16 chars omitted)
                    child 0, train_loss_history: list<item: double>
                        child 0, item: double
                    child 1, test_rmse_mean: double
                    child 2, test_rmse_std: double
                    child 3, train_seconds: double
                child 9, improvement_pct: double
              to
              {'md17': {'dataset': Value('string'), 'config': {'loader': Value('null'), 'horizon': Value('int64'), 'stride': Value('int64'), 'max_windows': Value('int64'), 'max_trials': Value('null')}, 'common': {'epochs': Value('int64'), 'lr': Value('float64'), 'hidden_dim': Value('int64'), 'n_layers': Value('int64'), 'n_sample_steps': Value('int64'), 'seed': Value('int64'), 'max_eval': Value('int64')}, 'n_windows': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'scale': Value('float64'), 'deterministic_baseline': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'gse_flow': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'improvement_pct': Value('float64')}, 'md22': {'dataset': Value('string'), 'config': {'loader': Value('null'), 'horizon': Value('int64'), 'stride': Value('int64'), 'max_windows': Value('int64'), 'max_trials': Value('null')}, 'common': {'epochs': Value('int64'), 'lr': Value('float64'), 'hidden_dim': Value('int64'), 'n_layers': Value('int64'), 'n_sample_steps': Value('int64'), 'seed': Value('int64'), 'max_eval': Value('int64')}, 'n_windows': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'scale': Value('float64'), 'deterministic_baseline': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'gse_flow': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'improvement_pct': Value('float64')}, 'cmu': {'dataset': Value('string'), 'config': {'loader': Value('null'), 'horizon': Value('int64'), 'stride': Value('int64'), 'max_windows': Value('int64'), 'max_trials': Value('null')}, 'common': {'epochs': Value('int64'), 'lr': Value('float64'), 'hidden_dim': Value('int64'), 'n_layers': Value('int64'), 'n_sample_steps': Value('int64'), 'seed': Value('int64'), 'max_eval': Value('int64')}, 'n_windows': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'scale': Value('float64'), 'deterministic_baseline': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'gse_flow': {'train_loss_history': List(Value('float64')), 'test_rmse_mean': Value('float64'), 'test_rmse_std': Value('float64'), 'train_seconds': Value('float64')}, 'improvement_pct': Value('float64')}}
              because column names don't match