Datasets:
quora

	# coding=utf-8
	# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
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	# distributed under the License is distributed on an "AS IS" BASIS,
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	# Lint as: python3
	"""Quora question pairs data"""


	import csv

	import datasets


	_DESCRIPTION = "The Quora dataset is composed of question pairs, and the task is to determine if the questions are paraphrases of each other (have the same meaning)."

	_URL = "http://qim.fs.quoracdn.net/quora_duplicate_questions.tsv"


	class Quora(datasets.GeneratorBasedBuilder):
	"""Quora Question Pairs dataset"""

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"questions": datasets.features.Sequence(
	{
	"id": datasets.Value("int32"),
	"text": datasets.Value("string"),
	}
	),
	"is_duplicate": datasets.Value("bool"),
	}
	),
	homepage="https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs",
	)

	def _split_generators(self, dl_manager):
	data_file = dl_manager.download_and_extract({"data_file": _URL})
	return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=data_file)]

	def _generate_examples(self, data_file):
	with open(data_file, encoding="utf-8") as f:
	data = csv.DictReader(f, delimiter="\t")
	for idx, row in enumerate(data):
	yield idx, {
	"questions": [
	{"id": row["qid1"], "text": row["question1"]},
	{"id": row["qid2"], "text": row["question2"]},
	],
	"is_duplicate": row["is_duplicate"] == "1",
	}