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	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# 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
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	"""DuoRC: A Paraphrased
	Reading Comprehension Question Answering Dataset"""


	import json

	import datasets


	_CITATION = """\
	@inproceedings{DuoRC,
	author = { Amrita Saha and Rahul Aralikatte and Mitesh M. Khapra and Karthik Sankaranarayanan},\
	title = {{DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension}},
	booktitle = {Meeting of the Association for Computational Linguistics (ACL)},
	year = {2018}
	}
	"""


	_DESCRIPTION = """\
	DuoRC contains 186,089 unique question-answer pairs created from a collection of 7680 pairs of movie plots where each pair in the collection reflects two versions of the same movie.
	"""

	_HOMEPAGE = "https://duorc.github.io/"

	_LICENSE = "https://raw.githubusercontent.com/duorc/duorc/master/LICENSE"

	_URL = "https://raw.githubusercontent.com/duorc/duorc/master/dataset/"
	_URLs = {
	"SelfRC": {
	"train": _URL + "SelfRC_train.json",
	# "dev": _URL + "SelfRC_dev.json",
	"test": _URL + "SelfRC_test.json",
	},
	"ParaphraseRC": {
	"train": _URL + "ParaphraseRC_train.json",
	# "dev": _URL + "ParaphraseRC_dev.json",
	"test": _URL + "ParaphraseRC_test.json",
	},
	}


	class DuorcConfig(datasets.BuilderConfig):
	"""BuilderConfig for DuoRC SelfRC."""

	def __init__(self, **kwargs):
	"""BuilderConfig for DuoRC SelfRC.
	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(DuorcConfig, self).__init__(**kwargs)


	class Duorc(datasets.GeneratorBasedBuilder):
	"""DuoRC Dataset"""

	VERSION = datasets.Version("1.0.0")
	BUILDER_CONFIGS = [
	DuorcConfig(name="SelfRC", version=VERSION, description="SelfRC dataset"),
	DuorcConfig(name="ParaphraseRC", version=VERSION, description="ParaphraseRC dataset"),
	]

	def _info(self):
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=datasets.Features(
	{
	"plot_id": datasets.Value("string"),
	"plot": datasets.Value("string"),
	"title": datasets.Value("string"),
	"question_id": datasets.Value("string"),
	"question": datasets.Value("string"),
	"answers": datasets.features.Sequence(datasets.Value("string")),
	"no_answer": datasets.Value("bool"),
	}
	),
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	my_urls = _URLs[self.config.name]
	downloaded_files = dl_manager.download_and_extract(my_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["test"],
	},
	),
	]

	def _generate_examples(self, filepath):
	"""This function returns the examples in the raw (text) form."""
	with open(filepath, encoding="utf-8") as f:
	duorc = json.load(f)
	for example in duorc:
	plot_id = example["id"]
	plot = example["plot"].strip()
	title = example["title"].strip()
	for qas in example["qa"]:
	question_id = qas["id"]
	question = qas["question"].strip()
	answers = [answer.strip() for answer in qas["answers"]]
	no_answer = qas["no_answer"]

	yield question_id, {
	"title": title,
	"plot": plot,
	"question": question,
	"plot_id": plot_id,
	"question_id": question_id,
	"answers": answers,
	"no_answer": no_answer,
	}