Datasets:
Commit
•
01bd059
1
Parent(s):
c29c92d
Delete loading script
Browse files- cmu_hinglish_dog.py +0 -190
cmu_hinglish_dog.py
DELETED
@@ -1,190 +0,0 @@
|
|
1 |
-
# coding=utf-8
|
2 |
-
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
|
3 |
-
#
|
4 |
-
# Licensed under the Apache License, Version 2.0 (the "License");
|
5 |
-
# you may not use this file except in compliance with the License.
|
6 |
-
# You may obtain a copy of the License at
|
7 |
-
#
|
8 |
-
# http://www.apache.org/licenses/LICENSE-2.0
|
9 |
-
#
|
10 |
-
# Unless required by applicable law or agreed to in writing, software
|
11 |
-
# distributed under the License is distributed on an "AS IS" BASIS,
|
12 |
-
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
13 |
-
# See the License for the specific language governing permissions and
|
14 |
-
# limitations under the License.
|
15 |
-
|
16 |
-
import json
|
17 |
-
import os
|
18 |
-
import re
|
19 |
-
|
20 |
-
import datasets
|
21 |
-
|
22 |
-
|
23 |
-
_CITATION = """\
|
24 |
-
@inproceedings{cmu_dog_emnlp18,
|
25 |
-
title={A Dataset for Document Grounded Conversations},
|
26 |
-
author={Zhou, Kangyan and Prabhumoye, Shrimai and Black, Alan W},
|
27 |
-
year={2018},
|
28 |
-
booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing}
|
29 |
-
}
|
30 |
-
|
31 |
-
@inproceedings{khanuja-etal-2020-gluecos,
|
32 |
-
title = "{GLUEC}o{S}: An Evaluation Benchmark for Code-Switched {NLP}",
|
33 |
-
author = "Khanuja, Simran and
|
34 |
-
Dandapat, Sandipan and
|
35 |
-
Srinivasan, Anirudh and
|
36 |
-
Sitaram, Sunayana and
|
37 |
-
Choudhury, Monojit",
|
38 |
-
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
|
39 |
-
month = jul,
|
40 |
-
year = "2020",
|
41 |
-
address = "Online",
|
42 |
-
publisher = "Association for Computational Linguistics",
|
43 |
-
url = "https://www.aclweb.org/anthology/2020.acl-main.329",
|
44 |
-
pages = "3575--3585"
|
45 |
-
}
|
46 |
-
"""
|
47 |
-
|
48 |
-
_DESCRIPTION = """\
|
49 |
-
This is a collection of text conversations in Hinglish (code mixing between Hindi-English) and their corresponding English only versions. Can be used for Translating between the two.
|
50 |
-
"""
|
51 |
-
|
52 |
-
_HOMEPAGE = "http://festvox.org/cedar/data/notyet/"
|
53 |
-
_URL_HINGLISH = "http://festvox.org/cedar/data/notyet/CMUHinglishDoG.zip"
|
54 |
-
# From: https://github.com/festvox/datasets-CMU_DoG/archive/master/Conversations.zip
|
55 |
-
_URL_ENGLISH = "data-english.zip"
|
56 |
-
|
57 |
-
|
58 |
-
class CMUHinglishDoG(datasets.GeneratorBasedBuilder):
|
59 |
-
"""Load the CMU Hinglish DoG Data for MT"""
|
60 |
-
|
61 |
-
def _info(self):
|
62 |
-
features = datasets.Features(
|
63 |
-
{
|
64 |
-
"date": datasets.Value("string"),
|
65 |
-
"docIdx": datasets.Value("int64"),
|
66 |
-
"translation": datasets.Translation(languages=["en", "hi_en"]),
|
67 |
-
"uid": datasets.Value("string"),
|
68 |
-
"utcTimestamp": datasets.Value("string"),
|
69 |
-
"rating": datasets.Value("int64"),
|
70 |
-
"status": datasets.Value("int64"),
|
71 |
-
"uid1LogInTime": datasets.Value("string"),
|
72 |
-
"uid1LogOutTime": datasets.Value("string"),
|
73 |
-
"uid1response": {
|
74 |
-
"response": datasets.Sequence(datasets.Value("int64")),
|
75 |
-
"type": datasets.Value("string"),
|
76 |
-
},
|
77 |
-
"uid2response": {
|
78 |
-
"response": datasets.Sequence(datasets.Value("int64")),
|
79 |
-
"type": datasets.Value("string"),
|
80 |
-
},
|
81 |
-
"user2_id": datasets.Value("string"),
|
82 |
-
"whoSawDoc": datasets.Sequence(datasets.Value("string")),
|
83 |
-
"wikiDocumentIdx": datasets.Value("int64"),
|
84 |
-
}
|
85 |
-
)
|
86 |
-
return datasets.DatasetInfo(
|
87 |
-
description=_DESCRIPTION,
|
88 |
-
features=features,
|
89 |
-
supervised_keys=None,
|
90 |
-
homepage=_HOMEPAGE,
|
91 |
-
citation=_CITATION,
|
92 |
-
)
|
93 |
-
|
94 |
-
def _split_generators(self, dl_manager):
|
95 |
-
"""The linking part between Hinglish data and English data is inspired from the implementation in GLUECoS.
|
96 |
-
Refer here for the original script https://github.com/microsoft/GLUECoS/blob/7fdc51653e37a32aee17505c47b7d1da364fa77e/Data/Preprocess_Scripts/preprocess_mt_en_hi.py"""
|
97 |
-
|
98 |
-
eng_path = dl_manager.download_and_extract(_URL_ENGLISH)
|
99 |
-
data_dir_en = os.path.join(eng_path, "Conversations")
|
100 |
-
|
101 |
-
hi_en_path = dl_manager.download_and_extract(_URL_HINGLISH)
|
102 |
-
data_dir_hi_en = os.path.join(hi_en_path, "CMUHinglishDoG", "Conversations_Hinglish")
|
103 |
-
|
104 |
-
hi_en_dirs = {
|
105 |
-
"train": os.path.join(data_dir_hi_en, "train"),
|
106 |
-
"valid": os.path.join(data_dir_hi_en, "valid"),
|
107 |
-
"test": os.path.join(data_dir_hi_en, "test"),
|
108 |
-
}
|
109 |
-
|
110 |
-
return [
|
111 |
-
datasets.SplitGenerator(
|
112 |
-
name=datasets.Split.TRAIN,
|
113 |
-
gen_kwargs={
|
114 |
-
"hi_en_dir": hi_en_dirs["train"],
|
115 |
-
"data_dir_en": data_dir_en,
|
116 |
-
},
|
117 |
-
),
|
118 |
-
datasets.SplitGenerator(
|
119 |
-
name=datasets.Split.TEST,
|
120 |
-
gen_kwargs={
|
121 |
-
"hi_en_dir": hi_en_dirs["test"],
|
122 |
-
"data_dir_en": data_dir_en,
|
123 |
-
},
|
124 |
-
),
|
125 |
-
datasets.SplitGenerator(
|
126 |
-
name=datasets.Split.VALIDATION,
|
127 |
-
gen_kwargs={
|
128 |
-
"hi_en_dir": hi_en_dirs["valid"],
|
129 |
-
"data_dir_en": data_dir_en,
|
130 |
-
},
|
131 |
-
),
|
132 |
-
]
|
133 |
-
|
134 |
-
def _generate_examples(self, hi_en_dir, data_dir_en):
|
135 |
-
"""Yields examples."""
|
136 |
-
english_files_train = os.listdir(os.path.join(data_dir_en, "train"))
|
137 |
-
english_files_val = os.listdir(os.path.join(data_dir_en, "valid"))
|
138 |
-
english_files_test = os.listdir(os.path.join(data_dir_en, "test"))
|
139 |
-
|
140 |
-
hinglish_files = os.listdir(hi_en_dir)
|
141 |
-
key = 0
|
142 |
-
for f in hinglish_files:
|
143 |
-
en_file_path = f.split(".json")[0] + ".json"
|
144 |
-
found = True
|
145 |
-
# Looks for the corresponding english file in all 3 splits
|
146 |
-
if en_file_path in english_files_train:
|
147 |
-
en = json.load(open(os.path.join(os.path.join(data_dir_en, "train"), en_file_path)))
|
148 |
-
elif en_file_path in english_files_val:
|
149 |
-
en = json.load(open(os.path.join(os.path.join(data_dir_en, "valid"), en_file_path)))
|
150 |
-
elif en_file_path in english_files_test:
|
151 |
-
en = json.load(open(os.path.join(os.path.join(data_dir_en, "test"), en_file_path)))
|
152 |
-
else:
|
153 |
-
found = False
|
154 |
-
if found:
|
155 |
-
hi_en = json.load(open(os.path.join(hi_en_dir, f)))
|
156 |
-
|
157 |
-
assert len(en["history"]) == len(hi_en["history"])
|
158 |
-
|
159 |
-
for x, y in zip(en["history"], hi_en["history"]):
|
160 |
-
assert x["docIdx"] == y["docIdx"]
|
161 |
-
assert x["uid"] == y["uid"]
|
162 |
-
assert x["utcTimestamp"] == y["utcTimestamp"]
|
163 |
-
|
164 |
-
x["text"] = re.sub("\t|\n", " ", x["text"])
|
165 |
-
y["text"] = re.sub("\t|\n", " ", y["text"])
|
166 |
-
line = {
|
167 |
-
"date": hi_en["date"],
|
168 |
-
"uid": x["uid"],
|
169 |
-
"docIdx": x["docIdx"],
|
170 |
-
"utcTimestamp": x["utcTimestamp"],
|
171 |
-
"translation": {"hi_en": y["text"], "en": x["text"]},
|
172 |
-
"rating": hi_en["rating"],
|
173 |
-
"status": hi_en["status"],
|
174 |
-
"uid1LogOutTime": hi_en.get("uid1LogOutTime"),
|
175 |
-
"uid1LogInTime": hi_en["uid1LogInTime"],
|
176 |
-
"uid1response": {
|
177 |
-
"response": hi_en["uid1response"]["response"] if "uid1response" in hi_en else [],
|
178 |
-
"type": hi_en["uid1response"]["type"] if "uid1response" in hi_en else None,
|
179 |
-
},
|
180 |
-
"uid2response": {
|
181 |
-
"response": hi_en["uid2response"]["response"] if "uid2response" in hi_en else [],
|
182 |
-
"type": hi_en["uid2response"]["type"] if "uid2response" in hi_en else None,
|
183 |
-
},
|
184 |
-
"user2_id": hi_en["user2_id"],
|
185 |
-
"whoSawDoc": hi_en["whoSawDoc"],
|
186 |
-
"wikiDocumentIdx": hi_en["wikiDocumentIdx"],
|
187 |
-
}
|
188 |
-
|
189 |
-
yield key, line
|
190 |
-
key += 1
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|