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: string
status: string
created_at_unix: double
config: struct<total_groups: int64, groups_per_shard: int64, start_group: int64, seed: int64, frames: int64, (... 338 chars omitted)
child 0, total_groups: int64
child 1, groups_per_shard: int64
child 2, start_group: int64
child 3, seed: int64
child 4, frames: int64
child 5, width: int64
child 6, height: int64
child 7, samples: int64
child 8, difficulty_profile: string
child 9, variants_per_group: int64
child 10, records_per_group: int64
child 11, source_fingerprint: struct<Blender_video/scripts/generate_repair_shard.py: string, Blender_video/scripts/finalize_repair (... 90 chars omitted)
child 0, Blender_video/scripts/generate_repair_shard.py: string
child 1, Blender_video/scripts/finalize_repair_shard.py: string
child 2, Blender_video/run_cloud_shard.sh: string
child 3, configs/default.yaml: string
shards: struct<shard_0000: struct<status: string, start_group: int64, group_count: int64, started_at_unix: d (... 2171 chars omitted)
child 0, shard_0000: struct<status: string, start_group: int64, group_count: int64, started_at_unix: double, elapsed_sec: (... 81 chars omitted)
child 0, status: string
child 1, start_group: int64
child 2, group_count: int64
child 3, started_at_unix: double
child 4, elapsed_sec: double
child 5, manifest_sha256: string
child 6, record_count: int64
child 7, completed_at_unix: double
child 1,
...
ring
child 4, results: list<item: struct<sample_id: string, injected_category: string, decision: string, observed_categorie (... 65 chars omitted)
child 0, item: struct<sample_id: string, injected_category: string, decision: string, observed_categories: list<ite (... 53 chars omitted)
child 0, sample_id: string
child 1, injected_category: string
child 2, decision: string
child 3, observed_categories: list<item: string>
child 0, item: string
child 4, valid: bool
child 5, reasons: list<item: string>
child 0, item: string
audit: struct<valid: bool, sample_count: int64, group_count: int64, action_counts: struct<reject: int64, lo (... 198 chars omitted)
child 0, valid: bool
child 1, sample_count: int64
child 2, group_count: int64
child 3, action_counts: struct<reject: int64, local_editing: int64, global_regeneration: int64, prompt_repair: int64>
child 0, reject: int64
child 1, local_editing: int64
child 2, global_regeneration: int64
child 3, prompt_repair: int64
child 4, split_counts: struct<unassigned: int64>
child 0, unassigned: int64
child 5, successful_count: int64
child 6, group_leakage: struct<>
child 7, missing_artifacts: list<item: null>
child 0, item: null
manifest: string
critic_decisions: struct<violation: int64, physical: int64, unknown: int64>
child 0, violation: int64
child 1, physical: int64
child 2, unknown: int64
to
{'audit': {'valid': Value('bool'), 'sample_count': Value('int64'), 'group_count': Value('int64'), 'action_counts': {'reject': Value('int64'), 'local_editing': Value('int64'), 'global_regeneration': Value('int64'), 'prompt_repair': Value('int64')}, 'split_counts': {'unassigned': Value('int64')}, 'successful_count': Value('int64'), 'group_leakage': {}, 'missing_artifacts': List(Value('null'))}, 'semantic_gate': {'valid': Value('bool'), 'checked': Value('int64'), 'failure_count': Value('int64'), 'failures': List({'sample_id': Value('string'), 'injected_category': Value('string'), 'decision': Value('string'), 'observed_categories': List(Value('string')), 'valid': Value('bool'), 'reasons': List(Value('string'))}), 'results': List({'sample_id': Value('string'), 'injected_category': Value('string'), 'decision': Value('string'), 'observed_categories': List(Value('string')), 'valid': Value('bool'), 'reasons': List(Value('string'))})}, 'critic_decisions': {'violation': Value('int64'), 'physical': Value('int64'), 'unknown': Value('int64')}, 'manifest': Value('string')}
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: string
status: string
created_at_unix: double
config: struct<total_groups: int64, groups_per_shard: int64, start_group: int64, seed: int64, frames: int64, (... 338 chars omitted)
child 0, total_groups: int64
child 1, groups_per_shard: int64
child 2, start_group: int64
child 3, seed: int64
child 4, frames: int64
child 5, width: int64
child 6, height: int64
child 7, samples: int64
child 8, difficulty_profile: string
child 9, variants_per_group: int64
child 10, records_per_group: int64
child 11, source_fingerprint: struct<Blender_video/scripts/generate_repair_shard.py: string, Blender_video/scripts/finalize_repair (... 90 chars omitted)
child 0, Blender_video/scripts/generate_repair_shard.py: string
child 1, Blender_video/scripts/finalize_repair_shard.py: string
child 2, Blender_video/run_cloud_shard.sh: string
child 3, configs/default.yaml: string
shards: struct<shard_0000: struct<status: string, start_group: int64, group_count: int64, started_at_unix: d (... 2171 chars omitted)
child 0, shard_0000: struct<status: string, start_group: int64, group_count: int64, started_at_unix: double, elapsed_sec: (... 81 chars omitted)
child 0, status: string
child 1, start_group: int64
child 2, group_count: int64
child 3, started_at_unix: double
child 4, elapsed_sec: double
child 5, manifest_sha256: string
child 6, record_count: int64
child 7, completed_at_unix: double
child 1,
...
ring
child 4, results: list<item: struct<sample_id: string, injected_category: string, decision: string, observed_categorie (... 65 chars omitted)
child 0, item: struct<sample_id: string, injected_category: string, decision: string, observed_categories: list<ite (... 53 chars omitted)
child 0, sample_id: string
child 1, injected_category: string
child 2, decision: string
child 3, observed_categories: list<item: string>
child 0, item: string
child 4, valid: bool
child 5, reasons: list<item: string>
child 0, item: string
audit: struct<valid: bool, sample_count: int64, group_count: int64, action_counts: struct<reject: int64, lo (... 198 chars omitted)
child 0, valid: bool
child 1, sample_count: int64
child 2, group_count: int64
child 3, action_counts: struct<reject: int64, local_editing: int64, global_regeneration: int64, prompt_repair: int64>
child 0, reject: int64
child 1, local_editing: int64
child 2, global_regeneration: int64
child 3, prompt_repair: int64
child 4, split_counts: struct<unassigned: int64>
child 0, unassigned: int64
child 5, successful_count: int64
child 6, group_leakage: struct<>
child 7, missing_artifacts: list<item: null>
child 0, item: null
manifest: string
critic_decisions: struct<violation: int64, physical: int64, unknown: int64>
child 0, violation: int64
child 1, physical: int64
child 2, unknown: int64
to
{'audit': {'valid': Value('bool'), 'sample_count': Value('int64'), 'group_count': Value('int64'), 'action_counts': {'reject': Value('int64'), 'local_editing': Value('int64'), 'global_regeneration': Value('int64'), 'prompt_repair': Value('int64')}, 'split_counts': {'unassigned': Value('int64')}, 'successful_count': Value('int64'), 'group_leakage': {}, 'missing_artifacts': List(Value('null'))}, 'semantic_gate': {'valid': Value('bool'), 'checked': Value('int64'), 'failure_count': Value('int64'), 'failures': List({'sample_id': Value('string'), 'injected_category': Value('string'), 'decision': Value('string'), 'observed_categories': List(Value('string')), 'valid': Value('bool'), 'reasons': List(Value('string'))}), 'results': List({'sample_id': Value('string'), 'injected_category': Value('string'), 'decision': Value('string'), 'observed_categories': List(Value('string')), 'valid': Value('bool'), 'reasons': List(Value('string'))})}, 'critic_decisions': {'violation': Value('int64'), 'physical': Value('int64'), 'unknown': Value('int64')}, 'manifest': Value('string')}
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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