nezhazheng/autotrain-xx-50653120896
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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"
}
] | bfb95b86a4714996 | [
"feat_db_id",
"feat_query_toks",
"feat_query_toks_no_value",
"feat_question_toks",
"source",
"target"
] | {} | null | false | null |
This dataset has been automatically processed by AutoTrain for project xx.
The BCP-47 code for the dataset's language is unk.
A sample from this dataset looks as follows:
[
{
"feat_db_id": "department_management",
"target": "SELECT count(*) FROM head WHERE age > 56",
"source": "How many heads of the departments are older than 56 ?",
"feat_query_toks": [
"SELECT",
"count",
"(",
"*",
")",
"FROM",
"head",
"WHERE",
"age",
">",
"56"
],
"feat_query_toks_no_value": [
"select",
"count",
"(",
"*",
")",
"from",
"head",
"where",
"age",
">",
"value"
],
"feat_question_toks": [
"How",
"many",
"heads",
"of",
"the",
"departments",
"are",
"older",
"than",
"56",
"?"
]
},
{
"feat_db_id": "department_management",
"target": "SELECT name , born_state , age FROM head ORDER BY age",
"source": "List the name, born state and age of the heads of departments ordered by age.",
"feat_query_toks": [
"SELECT",
"name",
",",
"born_state",
",",
"age",
"FROM",
"head",
"ORDER",
"BY",
"age"
],
"feat_query_toks_no_value": [
"select",
"name",
",",
"born_state",
",",
"age",
"from",
"head",
"order",
"by",
"age"
],
"feat_question_toks": [
"List",
"the",
"name",
",",
"born",
"state",
"and",
"age",
"of",
"the",
"heads",
"of",
"departments",
"ordered",
"by",
"age",
"."
]
}
]
The dataset has the following fields (also called "features"):
{
"feat_db_id": "Value(dtype='string', id=None)",
"target": "Value(dtype='string', id=None)",
"source": "Value(dtype='string', id=None)",
"feat_query_toks": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"feat_query_toks_no_value": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"feat_question_toks": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)"
}
This dataset is split into a train and validation split. The split sizes are as follow:
Split name | Num samples |
---|---|
train | 1001 |
valid | 1001 |