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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
n_layer: int64
d: int64
n_head: int64
N: int64
n_params: int64
steps: int64
S: int64
train_bpt: double
test_bpt: double
oracle_test_bpt: double
memU_total: double
memU_per_sample: double
memU_bits_per_param: double
dataset_bits: double
mia_f1: double
mia_auc: double
member_loss_mean: double
nonmember_loss_mean: double
wall_s: double
seed: int64
bits_per_param: double
V: int64
log2V: double
frac_memorized: double
mem_bits_per_seq: double
lr: double
mem_bits_total: double
batch: int64
precision: string
to
{'n_layer': Value('int64'), 'd': Value('int64'), 'n_head': Value('int64'), 'V': Value('int64'), 'S': Value('int64'), 'seed': Value('int64'), 'lr': Value('float64'), 'batch': Value('int64'), 'precision': Value('string'), 'N': Value('int64'), 'n_params': Value('int64'), 'steps': Value('int64'), 'train_bpt': Value('float64'), 'log2V': Value('float64'), 'mem_bits_total': Value('float64'), 'mem_bits_per_seq': Value('float64'), 'bits_per_param': Value('float64'), 'frac_memorized': Value('float64'), 'dataset_bits': Value('float64'), 'member_loss_mean': Value('float64'), 'nonmember_loss_mean': Value('float64'), 'mia_f1': Value('float64'), 'mia_auc': Value('float64'), 'wall_s': 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
n_layer: int64
d: int64
n_head: int64
N: int64
n_params: int64
steps: int64
S: int64
train_bpt: double
test_bpt: double
oracle_test_bpt: double
memU_total: double
memU_per_sample: double
memU_bits_per_param: double
dataset_bits: double
mia_f1: double
mia_auc: double
member_loss_mean: double
nonmember_loss_mean: double
wall_s: double
seed: int64
bits_per_param: double
V: int64
log2V: double
frac_memorized: double
mem_bits_per_seq: double
lr: double
mem_bits_total: double
batch: int64
precision: string
to
{'n_layer': Value('int64'), 'd': Value('int64'), 'n_head': Value('int64'), 'V': Value('int64'), 'S': Value('int64'), 'seed': Value('int64'), 'lr': Value('float64'), 'batch': Value('int64'), 'precision': Value('string'), 'N': Value('int64'), 'n_params': Value('int64'), 'steps': Value('int64'), 'train_bpt': Value('float64'), 'log2V': Value('float64'), 'mem_bits_total': Value('float64'), 'mem_bits_per_seq': Value('float64'), 'bits_per_param': Value('float64'), 'frac_memorized': Value('float64'), 'dataset_bits': Value('float64'), 'member_loss_mean': Value('float64'), 'nonmember_loss_mean': Value('float64'), 'mia_f1': Value('float64'), 'mia_auc': Value('float64'), 'wall_s': Value('float64')}
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