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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
smoke: bool
parsed: int64
total: int64
parsed_frac: double
metrics: struct<median_final_ratio: double, n_runs: double>
child 0, median_final_ratio: double
child 1, n_runs: double
sec_per_item: double
config: struct<n: int64, stub: bool, smoke: bool, dump_raw: int64, model: null, dtype: string, out: string, (... 208 chars omitted)
child 0, n: int64
child 1, stub: bool
child 2, smoke: bool
child 3, dump_raw: int64
child 4, model: null
child 5, dtype: string
child 6, out: string
child 7, seed: int64
child 8, upload_repo: string
child 9, steps: int64
child 10, subset: int64
child 11, sharp_every: int64
child 12, pi_iters: int64
child 13, hidden: int64
child 14, dmodel: int64
child 15, block: int64
child 16, tasks: string
child 17, opts: string
child 18, lr_cifar: string
child 19, lr_shake: string
median_final_ratio: double
n_runs: int64
results: struct<cifar:vanilla: struct<task: string, opt: string, lr: double, norm: string, normalized: bool, (... 2940 chars omitted)
child 0, cifar:vanilla: struct<task: string, opt: string, lr: double, norm: string, normalized: bool, steps_ran: int64, fina (... 261 chars omitted)
child 0, task: string
child 1, opt: string
child 2, lr: double
child 3, norm: string
child 4, normalized: bool
child 5, steps_ran: int64
child 6, final_ratio: double
child 7, final_loss: double
child 8, max_ratio: double
child 9, init_ratio: double
child 10,
...
child 0, item: struct<step: int64, loss: double, S: double, dual_g: double, metric: double, thresh: double, ratio: (... 7 chars omitted)
child 0, step: int64
child 1, loss: double
child 2, S: double
child 3, dual_g: double
child 4, metric: double
child 5, thresh: double
child 6, ratio: double
child 7, shakespeare:muon: struct<task: string, opt: string, lr: double, norm: string, normalized: bool, steps_ran: int64, fina (... 261 chars omitted)
child 0, task: string
child 1, opt: string
child 2, lr: double
child 3, norm: string
child 4, normalized: bool
child 5, steps_ran: int64
child 6, final_ratio: double
child 7, final_loss: double
child 8, max_ratio: double
child 9, init_ratio: double
child 10, progressive_sharpening: bool
child 11, stable_band_0p8_1p5: double
child 12, hist: list<item: struct<step: int64, loss: double, S: double, dual_g: double, metric: double, thresh: doub (... 19 chars omitted)
child 0, item: struct<step: int64, loss: double, S: double, dual_g: double, metric: double, thresh: double, ratio: (... 7 chars omitted)
child 0, step: int64
child 1, loss: double
child 2, S: double
child 3, dual_g: double
child 4, metric: double
child 5, thresh: double
child 6, ratio: double
to
{'config': {'n': Value('int64'), 'stub': Value('bool'), 'smoke': Value('bool'), 'dump_raw': Value('int64'), 'model': Value('null'), 'dtype': Value('string'), 'out': Value('string'), 'seed': Value('int64'), 'upload_repo': Value('string'), 'steps': Value('int64'), 'subset': Value('int64'), 'sharp_every': Value('int64'), 'pi_iters': Value('int64'), 'hidden': Value('int64'), 'dmodel': Value('int64'), 'block': Value('int64'), 'tasks': Value('string'), 'opts': Value('string'), 'lr_cifar': Value('string'), 'lr_shake': Value('string')}, 'parsed': Value('int64'), 'n_runs': Value('int64'), 'median_final_ratio': Value('float64'), 'results': {'cifar:vanilla': {'task': Value('string'), 'opt': Value('string'), 'lr': Value('float64'), 'norm': Value('string'), 'normalized': Value('bool'), 'steps_ran': Value('int64'), 'final_ratio': Value('float64'), 'final_loss': Value('float64'), 'max_ratio': Value('float64'), 'init_ratio': Value('float64'), 'progressive_sharpening': Value('bool'), 'stable_band_0p8_1p5': Value('float64'), 'hist': List({'step': Value('int64'), 'loss': Value('float64'), 'S': Value('float64'), 'dual_g': Value('float64'), 'metric': Value('float64'), 'thresh': Value('float64'), 'ratio': Value('float64')})}, 'cifar:linf': {'task': Value('string'), 'opt': Value('string'), 'lr': Value('float64'), 'norm': Value('string'), 'normalized': Value('bool'), 'steps_ran': Value('int64'), 'final_ratio': Value('float64'), 'final_loss': Value('float64'), 'max_ratio': Value('float64'), 'init_rat
...
t64'), 'init_ratio': Value('float64'), 'progressive_sharpening': Value('bool'), 'stable_band_0p8_1p5': Value('float64'), 'hist': List({'step': Value('int64'), 'loss': Value('float64'), 'S': Value('float64'), 'dual_g': Value('float64'), 'metric': Value('float64'), 'thresh': Value('float64'), 'ratio': Value('float64')})}, 'shakespeare:signgd': {'task': Value('string'), 'opt': Value('string'), 'lr': Value('float64'), 'norm': Value('string'), 'normalized': Value('bool'), 'steps_ran': Value('int64'), 'final_ratio': Value('float64'), 'final_loss': Value('float64'), 'max_ratio': Value('float64'), 'init_ratio': Value('float64'), 'progressive_sharpening': Value('bool'), 'stable_band_0p8_1p5': Value('float64'), 'hist': List({'step': Value('int64'), 'loss': Value('float64'), 'S': Value('float64'), 'dual_g': Value('float64'), 'metric': Value('float64'), 'thresh': Value('float64'), 'ratio': Value('float64')})}, 'shakespeare:muon': {'task': Value('string'), 'opt': Value('string'), 'lr': Value('float64'), 'norm': Value('string'), 'normalized': Value('bool'), 'steps_ran': Value('int64'), 'final_ratio': Value('float64'), 'final_loss': Value('float64'), 'max_ratio': Value('float64'), 'init_ratio': Value('float64'), 'progressive_sharpening': Value('bool'), 'stable_band_0p8_1p5': Value('float64'), 'hist': List({'step': Value('int64'), 'loss': Value('float64'), 'S': Value('float64'), 'dual_g': Value('float64'), 'metric': Value('float64'), 'thresh': Value('float64'), 'ratio': 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
smoke: bool
parsed: int64
total: int64
parsed_frac: double
metrics: struct<median_final_ratio: double, n_runs: double>
child 0, median_final_ratio: double
child 1, n_runs: double
sec_per_item: double
config: struct<n: int64, stub: bool, smoke: bool, dump_raw: int64, model: null, dtype: string, out: string, (... 208 chars omitted)
child 0, n: int64
child 1, stub: bool
child 2, smoke: bool
child 3, dump_raw: int64
child 4, model: null
child 5, dtype: string
child 6, out: string
child 7, seed: int64
child 8, upload_repo: string
child 9, steps: int64
child 10, subset: int64
child 11, sharp_every: int64
child 12, pi_iters: int64
child 13, hidden: int64
child 14, dmodel: int64
child 15, block: int64
child 16, tasks: string
child 17, opts: string
child 18, lr_cifar: string
child 19, lr_shake: string
median_final_ratio: double
n_runs: int64
results: struct<cifar:vanilla: struct<task: string, opt: string, lr: double, norm: string, normalized: bool, (... 2940 chars omitted)
child 0, cifar:vanilla: struct<task: string, opt: string, lr: double, norm: string, normalized: bool, steps_ran: int64, fina (... 261 chars omitted)
child 0, task: string
child 1, opt: string
child 2, lr: double
child 3, norm: string
child 4, normalized: bool
child 5, steps_ran: int64
child 6, final_ratio: double
child 7, final_loss: double
child 8, max_ratio: double
child 9, init_ratio: double
child 10,
...
child 0, item: struct<step: int64, loss: double, S: double, dual_g: double, metric: double, thresh: double, ratio: (... 7 chars omitted)
child 0, step: int64
child 1, loss: double
child 2, S: double
child 3, dual_g: double
child 4, metric: double
child 5, thresh: double
child 6, ratio: double
child 7, shakespeare:muon: struct<task: string, opt: string, lr: double, norm: string, normalized: bool, steps_ran: int64, fina (... 261 chars omitted)
child 0, task: string
child 1, opt: string
child 2, lr: double
child 3, norm: string
child 4, normalized: bool
child 5, steps_ran: int64
child 6, final_ratio: double
child 7, final_loss: double
child 8, max_ratio: double
child 9, init_ratio: double
child 10, progressive_sharpening: bool
child 11, stable_band_0p8_1p5: double
child 12, hist: list<item: struct<step: int64, loss: double, S: double, dual_g: double, metric: double, thresh: doub (... 19 chars omitted)
child 0, item: struct<step: int64, loss: double, S: double, dual_g: double, metric: double, thresh: double, ratio: (... 7 chars omitted)
child 0, step: int64
child 1, loss: double
child 2, S: double
child 3, dual_g: double
child 4, metric: double
child 5, thresh: double
child 6, ratio: double
to
{'config': {'n': Value('int64'), 'stub': Value('bool'), 'smoke': Value('bool'), 'dump_raw': Value('int64'), 'model': Value('null'), 'dtype': Value('string'), 'out': Value('string'), 'seed': Value('int64'), 'upload_repo': Value('string'), 'steps': Value('int64'), 'subset': Value('int64'), 'sharp_every': Value('int64'), 'pi_iters': Value('int64'), 'hidden': Value('int64'), 'dmodel': Value('int64'), 'block': Value('int64'), 'tasks': Value('string'), 'opts': Value('string'), 'lr_cifar': Value('string'), 'lr_shake': Value('string')}, 'parsed': Value('int64'), 'n_runs': Value('int64'), 'median_final_ratio': Value('float64'), 'results': {'cifar:vanilla': {'task': Value('string'), 'opt': Value('string'), 'lr': Value('float64'), 'norm': Value('string'), 'normalized': Value('bool'), 'steps_ran': Value('int64'), 'final_ratio': Value('float64'), 'final_loss': Value('float64'), 'max_ratio': Value('float64'), 'init_ratio': Value('float64'), 'progressive_sharpening': Value('bool'), 'stable_band_0p8_1p5': Value('float64'), 'hist': List({'step': Value('int64'), 'loss': Value('float64'), 'S': Value('float64'), 'dual_g': Value('float64'), 'metric': Value('float64'), 'thresh': Value('float64'), 'ratio': Value('float64')})}, 'cifar:linf': {'task': Value('string'), 'opt': Value('string'), 'lr': Value('float64'), 'norm': Value('string'), 'normalized': Value('bool'), 'steps_ran': Value('int64'), 'final_ratio': Value('float64'), 'final_loss': Value('float64'), 'max_ratio': Value('float64'), 'init_rat
...
t64'), 'init_ratio': Value('float64'), 'progressive_sharpening': Value('bool'), 'stable_band_0p8_1p5': Value('float64'), 'hist': List({'step': Value('int64'), 'loss': Value('float64'), 'S': Value('float64'), 'dual_g': Value('float64'), 'metric': Value('float64'), 'thresh': Value('float64'), 'ratio': Value('float64')})}, 'shakespeare:signgd': {'task': Value('string'), 'opt': Value('string'), 'lr': Value('float64'), 'norm': Value('string'), 'normalized': Value('bool'), 'steps_ran': Value('int64'), 'final_ratio': Value('float64'), 'final_loss': Value('float64'), 'max_ratio': Value('float64'), 'init_ratio': Value('float64'), 'progressive_sharpening': Value('bool'), 'stable_band_0p8_1p5': Value('float64'), 'hist': List({'step': Value('int64'), 'loss': Value('float64'), 'S': Value('float64'), 'dual_g': Value('float64'), 'metric': Value('float64'), 'thresh': Value('float64'), 'ratio': Value('float64')})}, 'shakespeare:muon': {'task': Value('string'), 'opt': Value('string'), 'lr': Value('float64'), 'norm': Value('string'), 'normalized': Value('bool'), 'steps_ran': Value('int64'), 'final_ratio': Value('float64'), 'final_loss': Value('float64'), 'max_ratio': Value('float64'), 'init_ratio': Value('float64'), 'progressive_sharpening': Value('bool'), 'stable_band_0p8_1p5': Value('float64'), 'hist': List({'step': Value('int64'), 'loss': Value('float64'), 'S': Value('float64'), 'dual_g': Value('float64'), 'metric': Value('float64'), 'thresh': Value('float64'), 'ratio': 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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