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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.
"""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]]
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