Datasets:

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MoCa_ViDoRe

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Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
query-id: int64
corpus-id: int64
score: int64
-- schema metadata --
huggingface: '{"info": {"features": {"query-id": {"dtype": "int64", "_typ' + 113
to
{'_id': Value('int64'), 'image_layer_01': List(Value('float16'), length=2048), 'image_layer_02': List(Value('float16'), length=2048), 'image_layer_03': List(Value('float16'), length=2048), 'image_layer_04': List(Value('float16'), length=2048), 'image_layer_05': List(Value('float16'), length=2048), 'image_layer_06': List(Value('float16'), length=2048), 'image_layer_07': List(Value('float16'), length=2048), 'image_layer_08': List(Value('float16'), length=2048), 'image_layer_09': List(Value('float16'), length=2048), 'image_layer_10': List(Value('float16'), length=2048), 'image_layer_11': List(Value('float16'), length=2048), 'image_layer_12': List(Value('float16'), length=2048), 'image_layer_13': List(Value('float16'), length=2048), 'image_layer_14': List(Value('float16'), length=2048), 'image_layer_15': List(Value('float16'), length=2048), 'image_layer_16': List(Value('float16'), length=2048), 'image_layer_17': List(Value('float16'), length=2048), 'image_layer_18': List(Value('float16'), length=2048), 'image_layer_19': List(Value('float16'), length=2048), 'image_layer_20': List(Value('float16'), length=2048), 'image_layer_21': List(Value('float16'), length=2048), 'image_layer_22': List(Value('float16'), length=2048), 'image_layer_23': List(Value('float16'), length=2048), 'image_layer_24': List(Value('float16'), length=2048), 'image_layer_25': List(Value('float16'), length=2048), 'image_layer_26': List(Value('float16'), length=2048), 'image_layer_27': List(Value('float16'), length=2048), 'image_layer_28': List(Value('float16'), length=2048), 'image_layer_29': List(Value('float16'), length=2048), 'image_layer_30': List(Value('float16'), length=2048), 'image_layer_31': List(Value('float16'), length=2048), 'image_layer_32': List(Value('float16'), length=2048), 'image_layer_33': List(Value('float16'), length=2048), 'image_layer_34': List(Value('float16'), length=2048), 'image_layer_35': List(Value('float16'), length=2048), 'image_layer_36': List(Value('float16'), length=2048)}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/arrow/arrow.py", line 75, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/arrow/arrow.py", line 54, 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
              query-id: int64
              corpus-id: int64
              score: int64
              -- schema metadata --
              huggingface: '{"info": {"features": {"query-id": {"dtype": "int64", "_typ' + 113
              to
              {'_id': Value('int64'), 'image_layer_01': List(Value('float16'), length=2048), 'image_layer_02': List(Value('float16'), length=2048), 'image_layer_03': List(Value('float16'), length=2048), 'image_layer_04': List(Value('float16'), length=2048), 'image_layer_05': List(Value('float16'), length=2048), 'image_layer_06': List(Value('float16'), length=2048), 'image_layer_07': List(Value('float16'), length=2048), 'image_layer_08': List(Value('float16'), length=2048), 'image_layer_09': List(Value('float16'), length=2048), 'image_layer_10': List(Value('float16'), length=2048), 'image_layer_11': List(Value('float16'), length=2048), 'image_layer_12': List(Value('float16'), length=2048), 'image_layer_13': List(Value('float16'), length=2048), 'image_layer_14': List(Value('float16'), length=2048), 'image_layer_15': List(Value('float16'), length=2048), 'image_layer_16': List(Value('float16'), length=2048), 'image_layer_17': List(Value('float16'), length=2048), 'image_layer_18': List(Value('float16'), length=2048), 'image_layer_19': List(Value('float16'), length=2048), 'image_layer_20': List(Value('float16'), length=2048), 'image_layer_21': List(Value('float16'), length=2048), 'image_layer_22': List(Value('float16'), length=2048), 'image_layer_23': List(Value('float16'), length=2048), 'image_layer_24': List(Value('float16'), length=2048), 'image_layer_25': List(Value('float16'), length=2048), 'image_layer_26': List(Value('float16'), length=2048), 'image_layer_27': List(Value('float16'), length=2048), 'image_layer_28': List(Value('float16'), length=2048), 'image_layer_29': List(Value('float16'), length=2048), 'image_layer_30': List(Value('float16'), length=2048), 'image_layer_31': List(Value('float16'), length=2048), 'image_layer_32': List(Value('float16'), length=2048), 'image_layer_33': List(Value('float16'), length=2048), 'image_layer_34': List(Value('float16'), length=2048), 'image_layer_35': List(Value('float16'), length=2048), 'image_layer_36': List(Value('float16'), length=2048)}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset