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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
arm: string
mode: string
feedback: string
stage2_checkpoint: string
stage3_checkpoint: string
temperature: string
n_traj: int64
n_steps: int64
step_ns: int64
ode_steps: int64
seed: int64
renorm_pred: bool
rescale_rg: bool
window: int64
stage2_flow: bool
stage2_ode_steps: int64
stage2_ode_method: string
stage2_flow_renorm: string
domains: list<item: string>
child 0, item: string
files: list<item: string>
child 0, item: string
ca_ca_nm: struct<1balA00: double, 1em7A00: double, 1gjsA00: double>
child 0, 1balA00: double
child 1, 1em7A00: double
child 2, 1gjsA00: double
1em7A00: struct<length: int64, n_reference_frames: int64, n_pair_features: int64, reference_floor: struct<mae (... 227 chars omitted)
child 0, length: int64
child 1, n_reference_frames: int64
child 2, n_pair_features: int64
child 3, reference_floor: struct<mae: double, rmse: double, coverage: double, ca_ca_nm: double>
child 0, mae: double
child 1, rmse: double
child 2, coverage: double
child 3, ca_ca_nm: double
child 4, reference_ca_ca_nm: double
child 5, jepa_rollout: struct<mae: double, rmse: double, coverage: double, ca_ca_nm: double, rg_nm: double, rg_frac: double (... 23 chars omitted)
child 0, mae: double
child 1, rmse: double
child 2, coverage: double
child 3, ca_ca_nm: double
child 4, rg_nm: double
child 5, rg_frac: double
child 6, geometry_valid: bool
1balA00: struct<length: int64, n_reference_frames: int64, n_pair_feat
...
frac_std: double
child 12, n_non_physical: int64
child 1, reference_floor: struct<n_domains: int64, n_failed: int64, mae_mean: double, mae_std: double, rmse_mean: double, rmse (... 165 chars omitted)
child 0, n_domains: int64
child 1, n_failed: int64
child 2, mae_mean: double
child 3, mae_std: double
child 4, rmse_mean: double
child 5, rmse_std: double
child 6, coverage_mean: double
child 7, coverage_std: double
child 8, ca_ca_nm_mean: double
child 9, ca_ca_nm_std: double
child 10, rg_frac_mean: null
child 11, rg_frac_std: null
child 12, n_non_physical: int64
1gjsA00: struct<length: int64, n_reference_frames: int64, n_pair_features: int64, reference_floor: struct<mae (... 227 chars omitted)
child 0, length: int64
child 1, n_reference_frames: int64
child 2, n_pair_features: int64
child 3, reference_floor: struct<mae: double, rmse: double, coverage: double, ca_ca_nm: double>
child 0, mae: double
child 1, rmse: double
child 2, coverage: double
child 3, ca_ca_nm: double
child 4, reference_ca_ca_nm: double
child 5, jepa_rollout: struct<mae: double, rmse: double, coverage: double, ca_ca_nm: double, rg_nm: double, rg_frac: double (... 23 chars omitted)
child 0, mae: double
child 1, rmse: double
child 2, coverage: double
child 3, ca_ca_nm: double
child 4, rg_nm: double
child 5, rg_frac: double
child 6, geometry_valid: bool
to
{'1balA00': {'length': Value('int64'), 'n_reference_frames': Value('int64'), 'n_pair_features': Value('int64'), 'reference_floor': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64')}, 'reference_ca_ca_nm': Value('float64'), 'jepa_rollout': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64'), 'rg_nm': Value('float64'), 'rg_frac': Value('float64'), 'geometry_valid': Value('bool')}}, '1em7A00': {'length': Value('int64'), 'n_reference_frames': Value('int64'), 'n_pair_features': Value('int64'), 'reference_floor': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64')}, 'reference_ca_ca_nm': Value('float64'), 'jepa_rollout': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64'), 'rg_nm': Value('float64'), 'rg_frac': Value('float64'), 'geometry_valid': Value('bool')}}, '1gjsA00': {'length': Value('int64'), 'n_reference_frames': Value('int64'), 'n_pair_features': Value('int64'), 'reference_floor': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64')}, 'reference_ca_ca_nm': Value('float64'), 'jepa_rollout': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64'), 'rg_nm': Value('float64'), 'rg_frac': Value('float64'), 'geometry_valid': Value('bool')}}, '_summary': {'jepa_rollout': {'n_domains': Value('int64'), 'n_failed': Value('int64'), 'mae_mean': Value('float64'), 'mae_std': Value('float64'), 'rmse_mean': Value('float64'), 'rmse_std': Value('float64'), 'coverage_mean': Value('float64'), 'coverage_std': Value('float64'), 'ca_ca_nm_mean': Value('float64'), 'ca_ca_nm_std': Value('float64'), 'rg_frac_mean': Value('float64'), 'rg_frac_std': Value('float64'), 'n_non_physical': Value('int64')}, 'reference_floor': {'n_domains': Value('int64'), 'n_failed': Value('int64'), 'mae_mean': Value('float64'), 'mae_std': Value('float64'), 'rmse_mean': Value('float64'), 'rmse_std': Value('float64'), 'coverage_mean': Value('float64'), 'coverage_std': Value('float64'), 'ca_ca_nm_mean': Value('float64'), 'ca_ca_nm_std': Value('float64'), 'rg_frac_mean': Value('null'), 'rg_frac_std': Value('null'), 'n_non_physical': Value('int64')}}}
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
arm: string
mode: string
feedback: string
stage2_checkpoint: string
stage3_checkpoint: string
temperature: string
n_traj: int64
n_steps: int64
step_ns: int64
ode_steps: int64
seed: int64
renorm_pred: bool
rescale_rg: bool
window: int64
stage2_flow: bool
stage2_ode_steps: int64
stage2_ode_method: string
stage2_flow_renorm: string
domains: list<item: string>
child 0, item: string
files: list<item: string>
child 0, item: string
ca_ca_nm: struct<1balA00: double, 1em7A00: double, 1gjsA00: double>
child 0, 1balA00: double
child 1, 1em7A00: double
child 2, 1gjsA00: double
1em7A00: struct<length: int64, n_reference_frames: int64, n_pair_features: int64, reference_floor: struct<mae (... 227 chars omitted)
child 0, length: int64
child 1, n_reference_frames: int64
child 2, n_pair_features: int64
child 3, reference_floor: struct<mae: double, rmse: double, coverage: double, ca_ca_nm: double>
child 0, mae: double
child 1, rmse: double
child 2, coverage: double
child 3, ca_ca_nm: double
child 4, reference_ca_ca_nm: double
child 5, jepa_rollout: struct<mae: double, rmse: double, coverage: double, ca_ca_nm: double, rg_nm: double, rg_frac: double (... 23 chars omitted)
child 0, mae: double
child 1, rmse: double
child 2, coverage: double
child 3, ca_ca_nm: double
child 4, rg_nm: double
child 5, rg_frac: double
child 6, geometry_valid: bool
1balA00: struct<length: int64, n_reference_frames: int64, n_pair_feat
...
frac_std: double
child 12, n_non_physical: int64
child 1, reference_floor: struct<n_domains: int64, n_failed: int64, mae_mean: double, mae_std: double, rmse_mean: double, rmse (... 165 chars omitted)
child 0, n_domains: int64
child 1, n_failed: int64
child 2, mae_mean: double
child 3, mae_std: double
child 4, rmse_mean: double
child 5, rmse_std: double
child 6, coverage_mean: double
child 7, coverage_std: double
child 8, ca_ca_nm_mean: double
child 9, ca_ca_nm_std: double
child 10, rg_frac_mean: null
child 11, rg_frac_std: null
child 12, n_non_physical: int64
1gjsA00: struct<length: int64, n_reference_frames: int64, n_pair_features: int64, reference_floor: struct<mae (... 227 chars omitted)
child 0, length: int64
child 1, n_reference_frames: int64
child 2, n_pair_features: int64
child 3, reference_floor: struct<mae: double, rmse: double, coverage: double, ca_ca_nm: double>
child 0, mae: double
child 1, rmse: double
child 2, coverage: double
child 3, ca_ca_nm: double
child 4, reference_ca_ca_nm: double
child 5, jepa_rollout: struct<mae: double, rmse: double, coverage: double, ca_ca_nm: double, rg_nm: double, rg_frac: double (... 23 chars omitted)
child 0, mae: double
child 1, rmse: double
child 2, coverage: double
child 3, ca_ca_nm: double
child 4, rg_nm: double
child 5, rg_frac: double
child 6, geometry_valid: bool
to
{'1balA00': {'length': Value('int64'), 'n_reference_frames': Value('int64'), 'n_pair_features': Value('int64'), 'reference_floor': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64')}, 'reference_ca_ca_nm': Value('float64'), 'jepa_rollout': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64'), 'rg_nm': Value('float64'), 'rg_frac': Value('float64'), 'geometry_valid': Value('bool')}}, '1em7A00': {'length': Value('int64'), 'n_reference_frames': Value('int64'), 'n_pair_features': Value('int64'), 'reference_floor': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64')}, 'reference_ca_ca_nm': Value('float64'), 'jepa_rollout': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64'), 'rg_nm': Value('float64'), 'rg_frac': Value('float64'), 'geometry_valid': Value('bool')}}, '1gjsA00': {'length': Value('int64'), 'n_reference_frames': Value('int64'), 'n_pair_features': Value('int64'), 'reference_floor': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64')}, 'reference_ca_ca_nm': Value('float64'), 'jepa_rollout': {'mae': Value('float64'), 'rmse': Value('float64'), 'coverage': Value('float64'), 'ca_ca_nm': Value('float64'), 'rg_nm': Value('float64'), 'rg_frac': Value('float64'), 'geometry_valid': Value('bool')}}, '_summary': {'jepa_rollout': {'n_domains': Value('int64'), 'n_failed': Value('int64'), 'mae_mean': Value('float64'), 'mae_std': Value('float64'), 'rmse_mean': Value('float64'), 'rmse_std': Value('float64'), 'coverage_mean': Value('float64'), 'coverage_std': Value('float64'), 'ca_ca_nm_mean': Value('float64'), 'ca_ca_nm_std': Value('float64'), 'rg_frac_mean': Value('float64'), 'rg_frac_std': Value('float64'), 'n_non_physical': Value('int64')}, 'reference_floor': {'n_domains': Value('int64'), 'n_failed': Value('int64'), 'mae_mean': Value('float64'), 'mae_std': Value('float64'), 'rmse_mean': Value('float64'), 'rmse_std': Value('float64'), 'coverage_mean': Value('float64'), 'coverage_std': Value('float64'), 'ca_ca_nm_mean': Value('float64'), 'ca_ca_nm_std': Value('float64'), 'rg_frac_mean': Value('null'), 'rg_frac_std': Value('null'), 'n_non_physical': Value('int64')}}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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