Datasets:

---

Agatha7k

/

vp_benchmark

like 0

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'object_annotations'}) and 2 missing columns ({'object_anno_2', 'object_anno_1'}).

This happened while the json dataset builder was generating data using

hf://datasets/Agatha7k/vp_benchmark/object_caption_data_val_split_thing_300_vis.json (at revision 6b39331723a13f833221ea1159274791efc6aa00)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 623, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              object_annotations: list<item: struct<caption: string, id: int64>>
                child 0, item: struct<caption: string, id: int64>
                    child 0, caption: string
                    child 1, id: int64
              image_name: string
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 345
              to
              {'image_name': Value(dtype='string', id=None), 'object_anno_1': {'object_num': Value(dtype='string', id=None), 'qa1_attribute': Value(dtype='string', id=None), 'qa1_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa1_true_answer': Value(dtype='string', id=None), 'qa2_attribute': Value(dtype='string', id=None), 'qa2_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa2_true_answer': Value(dtype='string', id=None), 'qa3_attribute': Value(dtype='string', id=None), 'qa3_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa3_true_answer': Value(dtype='string', id=None), 'qa4_attribute': Value(dtype='string', id=None), 'qa4_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa4_true_answer': Value(dtype='string', id=None), 'qa5_attribute': Value(dtype='string', id=None), 'qa5_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa5_true_answer': Value(dtype='string', id=None)}, 'object_anno_2': {'object_num': Value(dtype='string', id=None), 'qa1_attribute': Value(dtype='string', id=None), 'qa1_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa1_true_answer': Value(dtype='string', id=None), 'qa2_attribute': Value(dtype='string', id=None), 'qa2_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa2_true_answer': Value(dtype='string', id=None), 'qa3_attribute': Value(dtype='string', id=None), 'qa3_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa3_true_answer': Value(dtype='string', id=None), 'qa4_attribute': Value(dtype='string', id=None), 'qa4_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa4_true_answer': Value(dtype='string', id=None), 'qa5_attribute': Value(dtype='string', id=None), 'qa5_false_answer': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'qa5_true_answer': Value(dtype='string', id=None)}}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1438, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1050, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1873, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'object_annotations'}) and 2 missing columns ({'object_anno_2', 'object_anno_1'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/Agatha7k/vp_benchmark/object_caption_data_val_split_thing_300_vis.json (at revision 6b39331723a13f833221ea1159274791efc6aa00)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)