Datasets:

HaninZ

/

supreme-court-speech

like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
index: int32
id: string
audio: struct<bytes: binary, path: string>
  child 0, bytes: binary
  child 1, path: string
speaker_id: string
normalized_text: string
sentiment: string
start_second: double
end_second: double
local_path: string
-- schema metadata --
huggingface: '{"info": {"features": {"index": {"dtype": "int32", "_type":' + 436
to
{'client_id': Value(dtype='string', id=None), 'audio': Audio(sampling_rate=None, mono=True, decode=True, id=None), 'sentence': Value(dtype='string', id=None), 'age': Value(dtype='string', id=None), 'gender': Value(dtype='string', id=None), 'accent': Value(dtype='string', id=None)}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1854, in _prepare_split_single
                  for _, table in generator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/arrow/arrow.py", line 76, in _generate_tables
                  yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/arrow/arrow.py", line 59, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              index: int32
              id: string
              audio: struct<bytes: binary, path: string>
                child 0, bytes: binary
                child 1, path: string
              speaker_id: string
              normalized_text: string
              sentiment: string
              start_second: double
              end_second: double
              local_path: string
              -- schema metadata --
              huggingface: '{"info": {"features": {"index": {"dtype": "int32", "_type":' + 436
              to
              {'client_id': Value(dtype='string', id=None), 'audio': Audio(sampling_rate=None, mono=True, decode=True, id=None), 'sentence': Value(dtype='string', id=None), 'age': Value(dtype='string', id=None), 'gender': Value(dtype='string', id=None), 'accent': Value(dtype='string', id=None)}
              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 1417, 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 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 1741, 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 1897, 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