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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
cfg: struct<run_id: string, process: struct<eps_p: double, eps_d: double, q_p: double, q_d: double, p: do (... 389 chars omitted)
child 0, run_id: string
child 1, process: struct<eps_p: double, eps_d: double, q_p: double, q_d: double, p: double, P: int64, D: int64>
child 0, eps_p: double
child 1, eps_d: double
child 2, q_p: double
child 3, q_d: double
child 4, p: double
child 5, P: int64
child 6, D: int64
child 2, seed: int64
child 3, out_gamma: double
child 4, seq_len: int64
child 5, n_train: int64
child 6, n_eval: int64
child 7, pre_steps: int64
child 8, ft_steps: int64
child 9, lr_base: double
child 10, d_model: int64
child 11, n_heads: int64
child 12, n_layers: int64
child 13, mlp: bool
child 14, obs_n: int64
child 15, gen_len: int64
child 16, window: int64
child 17, prompt_len: int64
child 18, obs_points_pre: int64
child 19, obs_points_ft: int64
child 20, ft_persona: int64
child 21, ft_domain: int64
child 22, ft_rebalance_norms: bool
refs: struct<vocab: int64, n_states: int64, myopic_entropy_pre: double, bigram_entropy_pre: double, myopic (... 210 chars omitted)
child 0, vocab: int64
child 1, n_states: int64
child 2, myopic_entropy_pre: double
child 3, bigram_entropy_pre: double
child 4, myopic_entropy_ft: double
child 5, bigram_entropy_ft: double
child 6, marker_rate_ft: double
child 7, detector_threshold: list<item: double>
child 0, item: double
child 8, mark
...
ble
pre_loss_train: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
ft_loss_train: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
lr: double
wall_s: double
n_pairs: int64
pairs: list<item: struct<gamma: double, seed: int64, refactored: double, control: double, difference: doubl (... 296 chars omitted)
child 0, item: struct<gamma: double, seed: int64, refactored: double, control: double, difference: double, refactor (... 284 chars omitted)
child 0, gamma: double
child 1, seed: int64
child 2, refactored: double
child 3, control: double
child 4, difference: double
child 5, refactored_finite_frac: double
child 6, refactored_loss_peak_ratio: double
child 7, control_finite_frac: double
child 8, control_loss_peak_ratio: double
child 9, max_logit_change: double
child 10, alpha: null
child 11, gamma_after: double
child 12, usable: bool
child 13, ft_loss_trace_refactored: list<item: double>
child 0, item: double
child 14, ft_loss_trace_control: list<item: double>
child 0, item: double
tag: string
paired_difference: struct<mean: double, sem: double, n: int64, all_same_sign: bool, gammas: list<item: double>>
child 0, mean: double
child 1, sem: double
child 2, n: int64
child 3, all_same_sign: bool
child 4, gammas: list<item: double>
child 0, item: double
n_usable: int64
to
{'tag': Value('string'), 'n_pairs': Value('int64'), 'n_usable': Value('int64'), 'pairs': List({'gamma': Value('float64'), 'seed': Value('int64'), 'refactored': Value('float64'), 'control': Value('float64'), 'difference': Value('float64'), 'refactored_finite_frac': Value('float64'), 'refactored_loss_peak_ratio': Value('float64'), 'control_finite_frac': Value('float64'), 'control_loss_peak_ratio': Value('float64'), 'max_logit_change': Value('float64'), 'alpha': Value('null'), 'gamma_after': Value('float64'), 'usable': Value('bool'), 'ft_loss_trace_refactored': List(Value('float64')), 'ft_loss_trace_control': List(Value('float64'))}), 'paired_difference': {'mean': Value('float64'), 'sem': Value('float64'), 'n': Value('int64'), 'all_same_sign': Value('bool'), 'gammas': List(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
cfg: struct<run_id: string, process: struct<eps_p: double, eps_d: double, q_p: double, q_d: double, p: do (... 389 chars omitted)
child 0, run_id: string
child 1, process: struct<eps_p: double, eps_d: double, q_p: double, q_d: double, p: double, P: int64, D: int64>
child 0, eps_p: double
child 1, eps_d: double
child 2, q_p: double
child 3, q_d: double
child 4, p: double
child 5, P: int64
child 6, D: int64
child 2, seed: int64
child 3, out_gamma: double
child 4, seq_len: int64
child 5, n_train: int64
child 6, n_eval: int64
child 7, pre_steps: int64
child 8, ft_steps: int64
child 9, lr_base: double
child 10, d_model: int64
child 11, n_heads: int64
child 12, n_layers: int64
child 13, mlp: bool
child 14, obs_n: int64
child 15, gen_len: int64
child 16, window: int64
child 17, prompt_len: int64
child 18, obs_points_pre: int64
child 19, obs_points_ft: int64
child 20, ft_persona: int64
child 21, ft_domain: int64
child 22, ft_rebalance_norms: bool
refs: struct<vocab: int64, n_states: int64, myopic_entropy_pre: double, bigram_entropy_pre: double, myopic (... 210 chars omitted)
child 0, vocab: int64
child 1, n_states: int64
child 2, myopic_entropy_pre: double
child 3, bigram_entropy_pre: double
child 4, myopic_entropy_ft: double
child 5, bigram_entropy_ft: double
child 6, marker_rate_ft: double
child 7, detector_threshold: list<item: double>
child 0, item: double
child 8, mark
...
ble
pre_loss_train: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
ft_loss_train: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
lr: double
wall_s: double
n_pairs: int64
pairs: list<item: struct<gamma: double, seed: int64, refactored: double, control: double, difference: doubl (... 296 chars omitted)
child 0, item: struct<gamma: double, seed: int64, refactored: double, control: double, difference: double, refactor (... 284 chars omitted)
child 0, gamma: double
child 1, seed: int64
child 2, refactored: double
child 3, control: double
child 4, difference: double
child 5, refactored_finite_frac: double
child 6, refactored_loss_peak_ratio: double
child 7, control_finite_frac: double
child 8, control_loss_peak_ratio: double
child 9, max_logit_change: double
child 10, alpha: null
child 11, gamma_after: double
child 12, usable: bool
child 13, ft_loss_trace_refactored: list<item: double>
child 0, item: double
child 14, ft_loss_trace_control: list<item: double>
child 0, item: double
tag: string
paired_difference: struct<mean: double, sem: double, n: int64, all_same_sign: bool, gammas: list<item: double>>
child 0, mean: double
child 1, sem: double
child 2, n: int64
child 3, all_same_sign: bool
child 4, gammas: list<item: double>
child 0, item: double
n_usable: int64
to
{'tag': Value('string'), 'n_pairs': Value('int64'), 'n_usable': Value('int64'), 'pairs': List({'gamma': Value('float64'), 'seed': Value('int64'), 'refactored': Value('float64'), 'control': Value('float64'), 'difference': Value('float64'), 'refactored_finite_frac': Value('float64'), 'refactored_loss_peak_ratio': Value('float64'), 'control_finite_frac': Value('float64'), 'control_loss_peak_ratio': Value('float64'), 'max_logit_change': Value('float64'), 'alpha': Value('null'), 'gamma_after': Value('float64'), 'usable': Value('bool'), 'ft_loss_trace_refactored': List(Value('float64')), 'ft_loss_trace_control': List(Value('float64'))}), 'paired_difference': {'mean': Value('float64'), 'sem': Value('float64'), 'n': Value('int64'), 'all_same_sign': Value('bool'), 'gammas': List(Value('float64'))}}
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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