Datasets:

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ConvLab

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woz

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ConvLab 22

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 3 new columns ({'intents', 'dialogue_acts', 'state'}) and 5 missing columns ({'dialogue_id', 'turns', 'data_split', 'original_id', 'dataset'}).

This happened while the json dataset builder was generating data using

zip://data/ontology.json::/tmp/hf-datasets-cache/medium/datasets/53206195565606-config-parquet-and-info-ConvLab-woz-c9e64abc/downloads/cbd0e34776082c2a308366ecee72d12f5332c9b4295af309910c213e7add3dfc

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 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              domains: struct<restaurant: struct<description: string, slots: struct<food: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, area: struct<description: string, is_categorical: bool, possible_values: list<item: string>>, postcode: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, phone: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, address: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, price range: struct<description: string, is_categorical: bool, possible_values: list<item: string>>, name: struct<description: string, is_categorical: bool, possible_values: list<item: null>>>>>
                child 0, restaurant: struct<description: string, slots: struct<food: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, area: struct<description: string, is_categorical: bool, possible_values: list<item: string>>, postcode: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, phone: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, address: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, price range: struct<description: string, is_categorical: bool, possible_values: list<item: string>>, name: struct<description: string, is_categorical: bool, possible_values: list<item: null>>>>
                    child 0, description: string
               
              ...
              is_categorical: bool
                            child 2, possible_values: list<item: string>
                                child 0, item: string
                        child 6, name: struct<description: string, is_categorical: bool, possible_values: list<item: null>>
                            child 0, description: string
                            child 1, is_categorical: bool
                            child 2, possible_values: list<item: null>
                                child 0, item: null
              intents: struct<inform: struct<description: string>, request: struct<description: string>>
                child 0, inform: struct<description: string>
                    child 0, description: string
                child 1, request: struct<description: string>
                    child 0, description: string
              state: struct<restaurant: struct<food: string, area: string, postcode: string, phone: string, address: string, price range: string, name: string>>
                child 0, restaurant: struct<food: string, area: string, postcode: string, phone: string, address: string, price range: string, name: string>
                    child 0, food: string
                    child 1, area: string
                    child 2, postcode: string
                    child 3, phone: string
                    child 4, address: string
                    child 5, price range: string
                    child 6, name: string
              dialogue_acts: struct<categorical: list<item: string>, non-categorical: list<item: string>, binary: list<item: string>>
                child 0, categorical: list<item: string>
                    child 0, item: string
                child 1, non-categorical: list<item: string>
                    child 0, item: string
                child 2, binary: list<item: string>
                    child 0, item: string
              to
              {'domains': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'dialogue_id': Value(dtype='string', id=None), 'turns': [{'dialogue_acts': {'binary': [{'domain': Value(dtype='string', id=None), 'intent': Value(dtype='string', id=None), 'slot': Value(dtype='string', id=None)}], 'categorical': [{'domain': Value(dtype='string', id=None), 'intent': Value(dtype='string', id=None), 'slot': Value(dtype='string', id=None), 'value': Value(dtype='string', id=None)}], 'non-categorical': [{'domain': Value(dtype='string', id=None), 'end': Value(dtype='int64', id=None), 'intent': Value(dtype='string', id=None), 'slot': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'value': Value(dtype='string', id=None)}]}, 'speaker': Value(dtype='string', id=None), 'state': {'restaurant': {'address': Value(dtype='string', id=None), 'area': Value(dtype='string', id=None), 'food': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None), 'phone': Value(dtype='string', id=None), 'postcode': Value(dtype='string', id=None), 'price range': Value(dtype='string', id=None)}}, 'utt_idx': Value(dtype='int64', id=None), 'utterance': Value(dtype='string', id=None)}], 'data_split': Value(dtype='string', id=None), 'original_id': Value(dtype='int64', id=None), 'dataset': 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 1321, 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 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2013, 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 3 new columns ({'intents', 'dialogue_acts', 'state'}) and 5 missing columns ({'dialogue_id', 'turns', 'data_split', 'original_id', 'dataset'}).
              
              This happened while the json dataset builder was generating data using
              
              zip://data/ontology.json::/tmp/hf-datasets-cache/medium/datasets/53206195565606-config-parquet-and-info-ConvLab-woz-c9e64abc/downloads/cbd0e34776082c2a308366ecee72d12f5332c9b4295af309910c213e7add3dfc
              
              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)