Dataset Viewer
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
schema_version: int64
logbook_revision: string
publication_sha256: string
trackio_version: string
reviewed_at: string
reviewer: string
viewports: list<item: string>
child 0, item: string
pages_reviewed: list<item: string>
child 0, item: string
checks: list<item: string>
child 0, item: string
notes: string
noise: double
device: string
n_train: int64
label: string
baseline: struct<model: string, parameters: int64, train_seconds: double, final_minibatch_train_error: double, (... 26 chars omitted)
child 0, model: string
child 1, parameters: int64
child 2, train_seconds: double
child 3, final_minibatch_train_error: double
child 4, test_relative_l2: double
derivative: struct<model: string, parameters: int64, train_seconds: double, final_minibatch_train_error: double, (... 98 chars omitted)
child 0, model: string
child 1, parameters: int64
child 2, train_seconds: double
child 3, final_minibatch_train_error: double
child 4, test_relative_l2: double
child 5, learned_orders: list<item: double>
child 0, item: double
child 6, learned_scales: list<item: double>
child 0, item: double
seed: int64
n_test: int64
relative_improvement_percent: double
resolution: int64
epochs: int64
to
{'label': Value('string'), 'device': Value('string'), 'seed': Value('int64'), 'epochs': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'resolution': Value('int64'), 'noise': Value('float64'), 'baseline': {'model': Value('string'), 'parameters': Value('int64'), 'train_seconds': Value('float64'), 'final_minibatch_train_error': Value('float64'), 'test_relative_l2': Value('float64')}, 'derivative': {'model': Value('string'), 'parameters': Value('int64'), 'train_seconds': Value('float64'), 'final_minibatch_train_error': Value('float64'), 'test_relative_l2': Value('float64'), 'learned_orders': List(Value('float64')), 'learned_scales': List(Value('float64'))}, 'relative_improvement_percent': 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
schema_version: int64
logbook_revision: string
publication_sha256: string
trackio_version: string
reviewed_at: string
reviewer: string
viewports: list<item: string>
child 0, item: string
pages_reviewed: list<item: string>
child 0, item: string
checks: list<item: string>
child 0, item: string
notes: string
noise: double
device: string
n_train: int64
label: string
baseline: struct<model: string, parameters: int64, train_seconds: double, final_minibatch_train_error: double, (... 26 chars omitted)
child 0, model: string
child 1, parameters: int64
child 2, train_seconds: double
child 3, final_minibatch_train_error: double
child 4, test_relative_l2: double
derivative: struct<model: string, parameters: int64, train_seconds: double, final_minibatch_train_error: double, (... 98 chars omitted)
child 0, model: string
child 1, parameters: int64
child 2, train_seconds: double
child 3, final_minibatch_train_error: double
child 4, test_relative_l2: double
child 5, learned_orders: list<item: double>
child 0, item: double
child 6, learned_scales: list<item: double>
child 0, item: double
seed: int64
n_test: int64
relative_improvement_percent: double
resolution: int64
epochs: int64
to
{'label': Value('string'), 'device': Value('string'), 'seed': Value('int64'), 'epochs': Value('int64'), 'n_train': Value('int64'), 'n_test': Value('int64'), 'resolution': Value('int64'), 'noise': Value('float64'), 'baseline': {'model': Value('string'), 'parameters': Value('int64'), 'train_seconds': Value('float64'), 'final_minibatch_train_error': Value('float64'), 'test_relative_l2': Value('float64')}, 'derivative': {'model': Value('string'), 'parameters': Value('int64'), 'train_seconds': Value('float64'), 'final_minibatch_train_error': Value('float64'), 'test_relative_l2': Value('float64'), 'learned_orders': List(Value('float64')), 'learned_scales': List(Value('float64'))}, 'relative_improvement_percent': 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.
Fractional Is Better: reproduction artifacts
This repository preserves the executable evidence for an independent
reproduction of OpenReview paper V4FDM692AZ.
The bundle includes the clean implementation, tests, experiment entry points,
exact paired-run result, protocol audit, dependency lockfile, and provenance.
It does not redistribute the 645 MB Burgers archive; the extracted canonical
data file used in the run had SHA-256
d1a0456776255a4bd841dbc18951d3f468266d945d96e24ae531a12f18bb5a1a.
The full-scale cell used 1,000 training examples, 200 test examples, resolution 1,024, 1% input noise, 500 epochs, and seed 42. DEL-FNO reduced test relative L2 error by 12.6138% versus the paired FNO baseline.
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