Datasets:

---

Lilynched999

/

dataset-artifacts

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
batch_count: int64
batches: list<item: struct<batch_id: int64, byte_size: int64, relative_filename: string, sample_count: int64, (... 17 chars omitted)
  child 0, item: struct<batch_id: int64, byte_size: int64, relative_filename: string, sample_count: int64, sha256: st (... 5 chars omitted)
      child 0, batch_id: int64
      child 1, byte_size: int64
      child 2, relative_filename: string
      child 3, sample_count: int64
      child 4, sha256: string
dataset_build_id: string
sample_count: int64
shard_id: int64
shards: list<item: struct<batch_count: int64, relative_shard_manifest_path: string, sample_count: int64, sha (... 45 chars omitted)
  child 0, item: struct<batch_count: int64, relative_shard_manifest_path: string, sample_count: int64, shard_id: int6 (... 33 chars omitted)
      child 0, batch_count: int64
      child 1, relative_shard_manifest_path: string
      child 2, sample_count: int64
      child 3, shard_id: int64
      child 4, shard_manifest_sha256: string
partition_algorithm: string
schema_version: int64
name: string
dataset_id: string
batch_size: int64
batch_count_per_shard: int64
num_classes: int64
profile: string
partition_seed: int64
shard_count: int64
task_type: string
preprocessing: struct<channel_order: string, mean: list<item: double>, scale: string, std: list<item: double>>
  child 0, channel_order: string
  child 1, mean: list<item: double>
      child 0, item: double
  child 2, scale: string
  child 3, std: list<item: double>
      child 0, item: double
dtype: string
input_shape: list<item: int64>
  child 0, item: int64
to
{'batch_count_per_shard': Value('int64'), 'batch_size': Value('int64'), 'dataset_build_id': Value('string'), 'dataset_id': Value('string'), 'dtype': Value('string'), 'input_shape': List(Value('int64')), 'name': Value('string'), 'num_classes': Value('int64'), 'partition_algorithm': Value('string'), 'partition_seed': Value('int64'), 'preprocessing': {'channel_order': Value('string'), 'mean': List(Value('float64')), 'scale': Value('string'), 'std': List(Value('float64'))}, 'profile': Value('string'), 'sample_count': Value('int64'), 'schema_version': Value('int64'), 'shard_count': Value('int64'), 'shards': List({'batch_count': Value('int64'), 'relative_shard_manifest_path': Value('string'), 'sample_count': Value('int64'), 'shard_id': Value('int64'), 'shard_manifest_sha256': Value('string')}), 'task_type': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              batch_count: int64
              batches: list<item: struct<batch_id: int64, byte_size: int64, relative_filename: string, sample_count: int64, (... 17 chars omitted)
                child 0, item: struct<batch_id: int64, byte_size: int64, relative_filename: string, sample_count: int64, sha256: st (... 5 chars omitted)
                    child 0, batch_id: int64
                    child 1, byte_size: int64
                    child 2, relative_filename: string
                    child 3, sample_count: int64
                    child 4, sha256: string
              dataset_build_id: string
              sample_count: int64
              shard_id: int64
              shards: list<item: struct<batch_count: int64, relative_shard_manifest_path: string, sample_count: int64, sha (... 45 chars omitted)
                child 0, item: struct<batch_count: int64, relative_shard_manifest_path: string, sample_count: int64, shard_id: int6 (... 33 chars omitted)
                    child 0, batch_count: int64
                    child 1, relative_shard_manifest_path: string
                    child 2, sample_count: int64
                    child 3, shard_id: int64
                    child 4, shard_manifest_sha256: string
              partition_algorithm: string
              schema_version: int64
              name: string
              dataset_id: string
              batch_size: int64
              batch_count_per_shard: int64
              num_classes: int64
              profile: string
              partition_seed: int64
              shard_count: int64
              task_type: string
              preprocessing: struct<channel_order: string, mean: list<item: double>, scale: string, std: list<item: double>>
                child 0, channel_order: string
                child 1, mean: list<item: double>
                    child 0, item: double
                child 2, scale: string
                child 3, std: list<item: double>
                    child 0, item: double
              dtype: string
              input_shape: list<item: int64>
                child 0, item: int64
              to
              {'batch_count_per_shard': Value('int64'), 'batch_size': Value('int64'), 'dataset_build_id': Value('string'), 'dataset_id': Value('string'), 'dtype': Value('string'), 'input_shape': List(Value('int64')), 'name': Value('string'), 'num_classes': Value('int64'), 'partition_algorithm': Value('string'), 'partition_seed': Value('int64'), 'preprocessing': {'channel_order': Value('string'), 'mean': List(Value('float64')), 'scale': Value('string'), 'std': List(Value('float64'))}, 'profile': Value('string'), 'sample_count': Value('int64'), 'schema_version': Value('int64'), 'shard_count': Value('int64'), 'shards': List({'batch_count': Value('int64'), 'relative_shard_manifest_path': Value('string'), 'sample_count': Value('int64'), 'shard_id': Value('int64'), 'shard_manifest_sha256': Value('string')}), 'task_type': Value('string')}
              because column names don't match