Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
question-generation
License:
File size: 4,702 Bytes
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""" python -c "from datasets import load_dataset;load_dataset('.')" """
import json
from itertools import chain
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """[SQuAD Shifts](https://modestyachts.github.io/squadshifts-website/index.html) dataset for question generation (QG) task."""
_URL = 'https://huggingface.co/datasets/asahi417/qg_squadshift/raw/main/data/processed'
_FILES = {
str(datasets.Split.TEST): {
'new_wiki': [f'{_URL}/new_wiki.test{i:02d}.jsonl' for i in range(3)],
'nyt': [f'{_URL}/nyt.test{i:02d}.jsonl' for i in range(4)],
'reddit': [f'{_URL}/reddit.test{i:02d}.jsonl' for i in range(4)],
'amazon': [f'{_URL}/amazon.test{i:02d}.jsonl' for i in range(4)]
},
str(datasets.Split.TRAIN): {
'new_wiki': [f'{_URL}/new_wiki.train{i:02d}.jsonl' for i in range(2)],
'nyt': [f'{_URL}/nyt.train{i:02d}.jsonl' for i in range(3)],
'reddit': [f'{_URL}/reddit.train{i:02d}.jsonl' for i in range(3)],
'amazon': [f'{_URL}/amazon.train{i:02d}.jsonl' for i in range(3)]
},
str(datasets.Split.VALIDATION): {
'new_wiki': [f'{_URL}/new_wiki.validation{i:02d}.jsonl' for i in range(1)],
'nyt': [f'{_URL}/nyt.validation{i:02d}.jsonl' for i in range(2)],
'reddit': [f'{_URL}/reddit.validation{i:02d}.jsonl' for i in range(2)],
'amazon': [f'{_URL}/amazon.validation{i:02d}.jsonl' for i in range(2)]
},
}
# _FILES = {
# str(datasets.Split.TEST): {
# 'new_wiki': [f'{_URL}/new_wiki.test.jsonl'],
# 'nyt': [f'{_URL}/nyt.test.jsonl'],
# 'reddit': [f'{_URL}/reddit.test.jsonl'],
# 'amazon': [f'{_URL}/amazon.test.jsonl']
# },
# str(datasets.Split.TRAIN): {
# 'new_wiki': [f'{_URL}/new_wiki.train.jsonl'],
# 'nyt': [f'{_URL}/nyt.train.jsonl'],
# 'reddit': [f'{_URL}/reddit.train.jsonl'],
# 'amazon': [f'{_URL}/amazon.train.jsonl']
# },
# str(datasets.Split.VALIDATION): {
# 'new_wiki': [f'{_URL}/new_wiki.validation.jsonl'],
# 'nyt': [f'{_URL}/nyt.validation.jsonl'],
# 'reddit': [f'{_URL}/reddit.validation.jsonl'],
# 'amazon': [f'{_URL}/amazon.validation.jsonl']
# },
# }
_DOMAIN = list(_FILES[list(_FILES.keys())[0]].keys())
class QGSQuADShiftsConfig(datasets.BuilderConfig):
"""BuilderConfig for SquadQG"""
def __init__(self, **kwargs):
"""BuilderConfig for SquadQG.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(QGSQuADShiftsConfig, self).__init__(**kwargs)
class QGSQuADShifts(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [QGSQuADShiftsConfig(name="default", description="All domain.")]
BUILDER_CONFIGS += [QGSQuADShiftsConfig(name=i, description=f"Domain {i}") for i in sorted(_DOMAIN)]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"answer": datasets.Value("string"),
"question": datasets.Value("string"),
"sentence": datasets.Value("string"),
"paragraph": datasets.Value("string"),
"sentence_answer": datasets.Value("string"),
"paragraph_answer": datasets.Value("string"),
"paragraph_sentence": datasets.Value("string"),
"paragraph_id": datasets.Value("string")
}
),
supervised_keys=None,
homepage="https://github.com/asahi417/lm-question-generation"
)
def _split_generators(self, dl_manager):
if self.config.name == 'default':
downloaded_file = dl_manager.download_and_extract({k: list(chain(*list(v.values()))) for k, v in _FILES.items()})
else:
downloaded_file = dl_manager.download_and_extract({k: v[self.config.name] for k, v in _FILES.items()})
return [datasets.SplitGenerator(name=k, gen_kwargs={"filepaths": downloaded_file[k]}) for k in _FILES.keys()]
def _generate_examples(self, filepaths):
_key = 0
for filepath in filepaths:
logger.info("generating examples from = %s", filepath)
with open(filepath, encoding="utf-8") as f:
_list = f.read().split('\n')
if _list[-1] == '':
_list = _list[:-1]
for i in _list:
data = json.loads(i)
yield _key, data
_key += 1
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