Datasets:
deal_or_no_dialog

	# 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.
	"""Deal or no deal negotiator"""


	import datasets


	_CITATION = """\
	@article{lewis2017deal,
	title={Deal or no deal? end-to-end learning for negotiation dialogues},
	author={Lewis, Mike and Yarats, Denis and Dauphin, Yann N and Parikh, Devi and Batra, Dhruv},
	journal={arXiv preprint arXiv:1706.05125},
	year={2017}
	}
	"""

	_DESCRIPTION = """\
	A large dataset of human-human negotiations on a multi-issue bargaining task, where agents who cannot observe each other’s reward functions must reach anagreement (o a deal) via natural language dialogue.
	"""

	_HOMEPAGE = "https://github.com/facebookresearch/end-to-end-negotiator"

	_LICENSE = "The project is licenced under CC-by-NC"

	_URLs = {
	"train": "https://raw.githubusercontent.com/facebookresearch/end-to-end-negotiator/master/src/data/negotiate/train.txt",
	"test": "https://raw.githubusercontent.com/facebookresearch/end-to-end-negotiator/master/src/data/negotiate/test.txt",
	"val": "https://raw.githubusercontent.com/facebookresearch/end-to-end-negotiator/master/src/data/negotiate/val.txt",
	"selfplay": "https://raw.githubusercontent.com/facebookresearch/end-to-end-negotiator/master/src/data/negotiate/selfplay.txt",
	}


	class DealOrNoDialog(datasets.GeneratorBasedBuilder):
	"""Deal or no deal negotiator"""

	VERSION = datasets.Version("1.1.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="dialogues",
	description="Consists of 5808 dialogues, based on 2236 unique scenarios.",
	version=VERSION,
	),
	datasets.BuilderConfig(
	name="self_play", description="Count and values with no dialogues. Used for self playing.", version=VERSION
	),
	]

	DEFAULT_CONFIG_NAME = "dialogues"

	def _info(self):
	if self.config.name == "dialogues":
	features = datasets.Features(
	{
	"input": datasets.Sequence({"count": datasets.Value("int32"), "value": datasets.Value("int32")}),
	"dialogue": datasets.Value("string"),
	"output": datasets.Value("string"),
	"partner_input": datasets.Sequence(
	{"count": datasets.Value("int32"), "value": datasets.Value("int32")}
	),
	}
	)
	else: # self_play
	features = datasets.Features(
	{
	"input": datasets.Sequence({"count": datasets.Value("int32"), "value": datasets.Value("int32")}),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	if self.config.name == "dialogues":
	path_train = dl_manager.download_and_extract(_URLs["train"])
	path_test = dl_manager.download_and_extract(_URLs["test"])
	path_val = dl_manager.download_and_extract(_URLs["val"])

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": path_train,
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"filepath": path_test, "split": "test"},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": path_val,
	"split": "val",
	},
	),
	]

	else:
	path = dl_manager.download_and_extract(_URLs["selfplay"])
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": path,
	"split": "train",
	},
	),
	]

	def _generate_examples(self, filepath, split="train"):
	"""Yields examples."""
	if self.config.name == "dialogues":
	with open(filepath, encoding="utf-8") as f:
	for idx, line in enumerate(f):
	tokens = line.split()

	yield idx, {
	"input": {
	"count": get_count_value(get_tag(tokens, "input"))[0],
	"value": get_count_value(get_tag(tokens, "input"))[1],
	},
	"dialogue": get_tag(tokens, "dialogue"),
	"output": get_tag(tokens, "output"),
	"partner_input": {
	"count": get_count_value(get_tag(tokens, "partner_input"))[0],
	"value": get_count_value(get_tag(tokens, "partner_input"))[1],
	},
	}

	else:
	with open(filepath, encoding="utf-8") as f:
	for idx, line in enumerate(f):
	yield idx, {"input": {"count": get_count_value(line)[0], "value": get_count_value(line)[1]}}


	def get_tag(tokens, tag):
	return " ".join(tokens[tokens.index("<" + tag + ">") + 1 : tokens.index("</" + tag + ">")])


	def get_count_value(sequence):
	seq_list = [int(el) for el in sequence.split()]
	assert len(seq_list) == 6
	return [seq_list[idx] for idx in [0, 2, 4]], [seq_list[idx] for idx in [1, 3, 5]]