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The dataset generation failed because of a cast error
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 missing columns ({'explanation'})
This happened while the csv dataset builder was generating data using
hf://datasets/DevOps-Eval/devopseval-exam/val/integration.csv (at revision ed3591b44cd6d8f2139693a18ff2f4de7a71d2ac)
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
id: int64
question: string
A: string
B: string
C: string
D: string
answer: string
type: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1104
to
{'id': Value(dtype='int64', id=None), 'question': Value(dtype='string', id=None), 'A': Value(dtype='string', id=None), 'B': Value(dtype='string', id=None), 'C': Value(dtype='string', id=None), 'D': Value(dtype='string', id=None), 'answer': Value(dtype='string', id=None), 'explanation': Value(dtype='string', id=None), 'type': 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 1 missing columns ({'explanation'})
This happened while the csv dataset builder was generating data using
hf://datasets/DevOps-Eval/devopseval-exam/val/integration.csv (at revision ed3591b44cd6d8f2139693a18ff2f4de7a71d2ac)
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)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id int64 | question string | A string | B string | C string | D string | answer string | explanation string | type string |
|---|---|---|---|---|---|---|---|---|
0 | 在DevOps实践中,以下哪个是持续集成(Continuous Integration)的关键特征? | 自动化构建和测试 | 持续部署和发布 | 敏捷开发和迭代 | 容器化和微服务架构 | A | 自动化构建和测试是持续集成的关键特征,而持续部署和发布(选项B)属于持续交付和部署的范畴,敏捷开发和迭代(选项C)是一种开发方法论,而容器化和微服务架构(选项D)是一种技术实践,这些选项都属于与持续集成不同的类别或关注点。 | Integration知识 |
0 | 在DevOps实践中,以下哪个是持续集成(Continuous Integration)的关键特征? | 自动化构建和测试 | 持续部署和发布 | 敏捷开发和迭代 | 容器化和微服务架构 | A | null | Integration知识 |
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