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Error code: DatasetGenerationError Exception: ArrowNotImplementedError Message: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. 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 583, in write_table self._build_writer(inferred_schema=pa_table.schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer self.pa_writer = self._WRITER_CLASS(self.stream, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__ self.writer = _parquet.ParquetWriter( File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__ File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2027, in _prepare_split_single num_examples, num_bytes = writer.finalize() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 602, in finalize self._build_writer(self.schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer self.pa_writer = self._WRITER_CLASS(self.stream, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__ self.writer = _parquet.ParquetWriter( File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__ File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field. 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 1529, 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 1154, 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 2038, 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
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_data_files
list | _fingerprint
string | _format_columns
sequence | _format_kwargs
dict | _format_type
null | _output_all_columns
bool | _split
null |
---|---|---|---|---|---|---|
[
{
"filename": "data-00000-of-00001.arrow"
}
] | 12b9c39b04f1ee82 | [
"answers.answer_start",
"answers.text",
"context",
"feat_id",
"feat_title",
"question"
] | {} | null | false | null |
AutoTrain Dataset for project: demo-train-project
Dataset Description
This dataset has been automatically processed by AutoTrain for project demo-train-project.
Languages
The BCP-47 code for the dataset's language is en.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"context": "Users have the right to, if necessary, rectification of inaccurate personal data concerning that User, via a written request, using the contact details in paragraph 9 below. The User has the right to demand deletion or restriction of processing, and the right to object to processing based on legitimate interest under certain circumstances. The User has the right to revoke any consent to processing that has been given by the User to Controller. Using this right may however, mean that the User can not apply for a specific job or otherwise use the Service. The User has under certain circumstances a right to data portability, which means a right to get the personal data and transfer these to another controller as long as this does not negatively affect the rights and freedoms of others. User has the right to lodge a complaint to the supervisory authority regarding the processing of personal data relating to him or her, if the User considers that the processing of personal data infringes the legal framework of privacy law. 4.",
"question": "Can I edit or change the data that I have provided to you? ",
"answers.text": [
"Users have the right to, if necessary, rectification of inaccurate personal data concerning that User, via a written request, using the contact details"
],
"answers.answer_start": [
0
],
"feat_id": [
"310276"
],
"feat_title": [
""
]
},
{
"context": "The lawful basis is our legitimate interest in being able to administer our business and thereby provide Our Services (Article 6(1)(f) GDPR). Insurance companies. The purpose for these transfers is to handle insurance claims and administer Our insurance policies. The lawful basis is our legitimate interest in handling insurance claims and administrating Our insurance policies on an ongoing basis (Article 6(1)(f) GDPR). Courts and Counter Parties in legal matters. The purpose for these transfers is to defend, exercise and establish legal claims. The lawful basis is Our legitimate interest to defend, exercise and establish legal claims (Article 6(1)(f) GDPR). Regulators: to comply with all applicable laws, regulations and rules, and requests of law enforcement, regulatory and other governmental agencies;\nSolicitors and other professional services firms (including our auditors). Law enforcement agencies, including the Police. The purpose for these transfers is to assist law enforcement agencies and the Police in its investigations, to the extent we are obligated to do so.",
"question": "What is the lawful basis of the processing of my data? ",
"answers.text": [
"The lawful basis is our legitimate interest in being able to administer our business and thereby provide Our Services (Article 6(1)(f) GDPR)."
],
"answers.answer_start": [
0
],
"feat_id": [
"310267"
],
"feat_title": [
""
]
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"context": "Value(dtype='string', id=None)",
"question": "Value(dtype='string', id=None)",
"answers.text": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"answers.answer_start": "Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None)",
"feat_id": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"feat_title": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
Split name | Num samples |
---|---|
train | 456 |
valid | 114 |
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