Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
License:
File size: 6,383 Bytes
43d46be 0d2a0b6 43d46be |
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 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 |
# 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]]
|