File size: 2,277 Bytes
2a62cc4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
import json
import datasets
from datasets.tasks import QuestionAnsweringExtractive
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@article{2016arXiv160605250R,
author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
Konstantin and {Liang}, Percy},
title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
journal = {arXiv e-prints},
year = 2016,
eid = {arXiv:1606.05250},
pages = {arXiv:1606.05250},
archivePrefix = {arXiv},
eprint = {1606.05250},
}
"""
_DESCRIPTION = """\
Demo...
"""
_URL = "https://github.com/rajivmehtaflex/PythonExp/raw/main/HFDatasets/reddit_data.tar.gz"
class RedditTopicsTargz(datasets.GeneratorBasedBuilder):
"""SQUAD: The Stanford Question Answering Dataset. Version 1.1."""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"sub": datasets.Value("string"),
"title": datasets.Value("string"),
"selftext": datasets.Value("string"),
"upvote_ratio": datasets.Value("float32"),
"id": datasets.Value("string"),
"created_utc": datasets.Value("float32"),
}
),
# No default supervised_keys (as we have to pass both question
# and context as input).
supervised_keys=None,
homepage="https://github.com/rajivmehtapy/",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
path = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": path+'/reddit_data.jsonl'}
),
]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (text) form."""
idx = 0
# open the file and read the lines
with open(filepath, encoding="utf-8") as fp:
for line in fp:
# load json line
obj = json.loads(line)
yield idx, obj
idx += 1 |