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import datasets
_CITATION = """\
"""
_DESCRIPTION = """\
This is a test dataset.
"""
_URLS = {
"train": "https://huggingface.co/datasets/changxin/test_pq/blob/main/another_text.txt", # absolute
"dev": "some_text.txt", # relative
"TEST1":"chuishui.txt"
}
class Test(datasets.GeneratorBasedBuilder):
"""SQUAD: The Stanford Question Answering Dataset. Version 1.1."""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"text": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="https://huggingface.co/datasets/changxin/test_pq",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download_and_extract(_URLS)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["TEST1"]}),
]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (text) form."""
for _id, line in enumerate(open(filepath, encoding="utf-8")):
yield _id, {"text": line.rstrip()}
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