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ConvLab

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

This happened while the json dataset builder was generating data using

zip://data/ontology.json::/tmp/hf-datasets-cache/medium/datasets/73265727319914-config-parquet-and-info-ConvLab-tm2-6af003ce/downloads/48bf4295eec3e2c77555430f4552c0e16b91f5ae5db39c6f7d3b11c83437039b

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<flights: struct<description: string, slots: struct<type: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, destination1: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, destination2: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, origin: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, date.depart_origin: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, date.depart_intermediate: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, date.return: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, time_of_day: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, seating_class: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, seat_location: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, stops: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, price_range: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, num.pax: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, luggage: struct<description: string, is_categorical: bool, possible_values: list<item: null>>, total_fare: struct<description: string, is_cate
              ...
              : string
                    child 15, phone: string
                child 6, sports: struct<name.team: string, record.team: string, record.games_ahead: string, record.games_back: string, place.team: string, result.match: string, score.match: string, date.match: string, day.match: string, time.match: string, name.player: string, position.player: string, record.player: string, name.non_player: string, venue: string, other_description.person: string, other_description.team: string, other_description.match: string>
                    child 0, name.team: string
                    child 1, record.team: string
                    child 2, record.games_ahead: string
                    child 3, record.games_back: string
                    child 4, place.team: string
                    child 5, result.match: string
                    child 6, score.match: string
                    child 7, date.match: string
                    child 8, day.match: string
                    child 9, time.match: string
                    child 10, name.player: string
                    child 11, position.player: string
                    child 12, record.player: string
                    child 13, name.non_player: string
                    child 14, venue: string
                    child 15, other_description.person: string
                    child 16, other_description.team: string
                    child 17, other_description.match: string
              dialogue_acts: struct<categorical: list<item: null>, non-categorical: list<item: string>, binary: list<item: string>>
                child 0, categorical: list<item: null>
                    child 0, item: null
                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), 'original_id': Value(dtype='string', id=None), 'dataset': 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': Sequence(feature=Value(dtype='null', id=None), length=-1, 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': {'flights': {'airline': Value(dtype='string', id=None), 'date': Value(dtype='string', id=None), 'date.depart_intermediate': Value(dtype='string', id=None), 'date.depart_origin': Value(dtype='string', id=None), 'date.return': Value(dtype='string', id=None), 'destination1': Value(dtype='string', id=None), 'destination2': Value(dtype='string', id=None), 'fare': Value(dtype='string', id=None), 'flight_number': Value(dtype='string', id=None), 'from': Value(dtype='string', id=None), 'from.time': Value(dtype='string', id=None), 'luggage': Value(dtype='string', id=None), 'num.pax': Value(dtype='string', id=None), 'origin': Value(dtype='string', id=None), 'other_description': Value(dtype='string', id=None), 'price_range': Value(dtype='string', id=None), 'sea
              ...
              scription': Value(dtype='string', id=None), 'phone': Value(dtype='string', id=None), 'price_range': Value(dtype='string', id=None), 'rating': Value(dtype='string', id=None), 'sub-location': Value(dtype='string', id=None), 'time.reservation': Value(dtype='string', id=None), 'type.food': Value(dtype='string', id=None), 'type.meal': Value(dtype='string', id=None), 'type.seating': Value(dtype='string', id=None)}, 'sports': {'date.match': Value(dtype='string', id=None), 'day.match': Value(dtype='string', id=None), 'name.non_player': Value(dtype='string', id=None), 'name.player': Value(dtype='string', id=None), 'name.team': Value(dtype='string', id=None), 'other_description.match': Value(dtype='string', id=None), 'other_description.person': Value(dtype='string', id=None), 'other_description.team': Value(dtype='string', id=None), 'place.team': Value(dtype='string', id=None), 'position.player': Value(dtype='string', id=None), 'record.games_ahead': Value(dtype='string', id=None), 'record.games_back': Value(dtype='string', id=None), 'record.player': Value(dtype='string', id=None), 'record.team': Value(dtype='string', id=None), 'result.match': Value(dtype='string', id=None), 'score.match': Value(dtype='string', id=None), 'time.match': Value(dtype='string', id=None), 'venue': Value(dtype='string', id=None)}}, 'utt_idx': Value(dtype='int64', id=None), 'utterance': Value(dtype='string', id=None)}], 'dialogue_id': Value(dtype='string', id=None), 'data_split': 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 ({'state', 'dialogue_acts', 'intents'}) and 5 missing columns ({'original_id', 'dataset', 'turns', 'dialogue_id', 'data_split'}).
              
              This happened while the json dataset builder was generating data using
              
              zip://data/ontology.json::/tmp/hf-datasets-cache/medium/datasets/73265727319914-config-parquet-and-info-ConvLab-tm2-6af003ce/downloads/48bf4295eec3e2c77555430f4552c0e16b91f5ae5db39c6f7d3b11c83437039b
              
              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)