Datasets:

---

luuow

/

meridian-stellar-cache

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
metric_primary: string
horizons_evaluated: list<item: int64>
  child 0, item: int64
any_horizon_strict_pass: bool
by_horizon: list<item: struct<horizon_hours: int64, n_train_pairs: int64, n_test_pairs: int64, specialists_train (... 918 chars omitted)
  child 0, item: struct<horizon_hours: int64, n_train_pairs: int64, n_test_pairs: int64, specialists_trained: list<it (... 906 chars omitted)
      child 0, horizon_hours: int64
      child 1, n_train_pairs: int64
      child 2, n_test_pairs: int64
      child 3, specialists_trained: list<item: int64>
          child 0, item: int64
      child 4, policies: struct<fixed: struct<mae_drift_dex: double, mae_E_W_m2: double>, persistence: struct<mae_drift_dex:  (... 90 chars omitted)
          child 0, fixed: struct<mae_drift_dex: double, mae_E_W_m2: double>
              child 0, mae_drift_dex: double
              child 1, mae_E_W_m2: double
          child 1, persistence: struct<mae_drift_dex: double, mae_E_W_m2: double>
              child 0, mae_drift_dex: double
              child 1, mae_E_W_m2: double
          child 2, archetype: struct<mae_drift_dex: double, mae_E_W_m2: double>
              child 0, mae_drift_dex: double
              child 1, mae_E_W_m2: double
      child 5, archetype_vs_persistence_pct: double
      child 6, archetype_vs_fixed_pct: double
      child 7, gate_2_strict_pass: bool
      child 8, gate_2_legacy_pass: bool
      child 9, y_train_drift_std: double
      child 10, y_test_drift_std: double
      c
...
coef: list<item: double>
                  child 0, item: double
              child 2, intercept: double
              child 3, n_train: int64
          child 3, 3: struct<type: string, coef: list<item: double>, intercept: double, n_train: int64>
              child 0, type: string
              child 1, coef: list<item: double>
                  child 0, item: double
              child 2, intercept: double
              child 3, n_train: int64
          child 4, 5: struct<type: string, coef: list<item: double>, intercept: double, n_train: int64>
              child 0, type: string
              child 1, coef: list<item: double>
                  child 0, item: double
              child 2, intercept: double
              child 3, n_train: int64
train_perihelia: list<item: string>
  child 0, item: string
test_perihelia: list<item: string>
  child 0, item: string
instrument_order_to_archetype: list<item: struct<target: string, order: int64, archetype: int64>>
  child 0, item: struct<target: string, order: int64, archetype: int64>
      child 0, target: string
      child 1, order: int64
      child 2, archetype: int64
chosen_horizon_hours: int64
assignment_distribution: struct<0: int64, 2: int64, 3: int64, 5: int64>
  child 0, 0: int64
  child 1, 2: int64
  child 2, 3: int64
  child 3, 5: int64
unique_targets: list<item: string>
  child 0, item: string
distinct_archetypes_used: int64
sensible_diversity_pass: bool
median_distance_z: double
n_rows: int64
max_distance_z: double
to
{'n_rows': Value('int64'), 'unique_targets': List(Value('string')), 'assignment_distribution': {'0': Value('int64'), '2': Value('int64'), '3': Value('int64'), '5': Value('int64')}, 'max_distance_z': Value('float64'), 'median_distance_z': Value('float64'), 'instrument_order_to_archetype': List({'target': Value('string'), 'order': Value('int64'), 'archetype': Value('int64')}), 'chosen_horizon_hours': Value('int64'), 'distinct_archetypes_used': Value('int64'), 'sensible_diversity_pass': Value('bool')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              metric_primary: string
              horizons_evaluated: list<item: int64>
                child 0, item: int64
              any_horizon_strict_pass: bool
              by_horizon: list<item: struct<horizon_hours: int64, n_train_pairs: int64, n_test_pairs: int64, specialists_train (... 918 chars omitted)
                child 0, item: struct<horizon_hours: int64, n_train_pairs: int64, n_test_pairs: int64, specialists_trained: list<it (... 906 chars omitted)
                    child 0, horizon_hours: int64
                    child 1, n_train_pairs: int64
                    child 2, n_test_pairs: int64
                    child 3, specialists_trained: list<item: int64>
                        child 0, item: int64
                    child 4, policies: struct<fixed: struct<mae_drift_dex: double, mae_E_W_m2: double>, persistence: struct<mae_drift_dex:  (... 90 chars omitted)
                        child 0, fixed: struct<mae_drift_dex: double, mae_E_W_m2: double>
                            child 0, mae_drift_dex: double
                            child 1, mae_E_W_m2: double
                        child 1, persistence: struct<mae_drift_dex: double, mae_E_W_m2: double>
                            child 0, mae_drift_dex: double
                            child 1, mae_E_W_m2: double
                        child 2, archetype: struct<mae_drift_dex: double, mae_E_W_m2: double>
                            child 0, mae_drift_dex: double
                            child 1, mae_E_W_m2: double
                    child 5, archetype_vs_persistence_pct: double
                    child 6, archetype_vs_fixed_pct: double
                    child 7, gate_2_strict_pass: bool
                    child 8, gate_2_legacy_pass: bool
                    child 9, y_train_drift_std: double
                    child 10, y_test_drift_std: double
                    c
              ...
              coef: list<item: double>
                                child 0, item: double
                            child 2, intercept: double
                            child 3, n_train: int64
                        child 3, 3: struct<type: string, coef: list<item: double>, intercept: double, n_train: int64>
                            child 0, type: string
                            child 1, coef: list<item: double>
                                child 0, item: double
                            child 2, intercept: double
                            child 3, n_train: int64
                        child 4, 5: struct<type: string, coef: list<item: double>, intercept: double, n_train: int64>
                            child 0, type: string
                            child 1, coef: list<item: double>
                                child 0, item: double
                            child 2, intercept: double
                            child 3, n_train: int64
              train_perihelia: list<item: string>
                child 0, item: string
              test_perihelia: list<item: string>
                child 0, item: string
              instrument_order_to_archetype: list<item: struct<target: string, order: int64, archetype: int64>>
                child 0, item: struct<target: string, order: int64, archetype: int64>
                    child 0, target: string
                    child 1, order: int64
                    child 2, archetype: int64
              chosen_horizon_hours: int64
              assignment_distribution: struct<0: int64, 2: int64, 3: int64, 5: int64>
                child 0, 0: int64
                child 1, 2: int64
                child 2, 3: int64
                child 3, 5: int64
              unique_targets: list<item: string>
                child 0, item: string
              distinct_archetypes_used: int64
              sensible_diversity_pass: bool
              median_distance_z: double
              n_rows: int64
              max_distance_z: double
              to
              {'n_rows': Value('int64'), 'unique_targets': List(Value('string')), 'assignment_distribution': {'0': Value('int64'), '2': Value('int64'), '3': Value('int64'), '5': Value('int64')}, 'max_distance_z': Value('float64'), 'median_distance_z': Value('float64'), 'instrument_order_to_archetype': List({'target': Value('string'), 'order': Value('int64'), 'archetype': Value('int64')}), 'chosen_horizon_hours': Value('int64'), 'distinct_archetypes_used': Value('int64'), 'sensible_diversity_pass': Value('bool')}
              because column names don't match