Datasets:
Update: dataset zip file structure; loading script WIP
Browse files- .gitignore +1 -0
- config.json +1686 -0
- datasets.zip +2 -2
- datasets_joined.zip +3 -0
- dev.py +8 -0
- utcd.py +143 -0
.gitignore
CHANGED
@@ -1,3 +1,4 @@
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1 |
.idea/
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2 |
.vscode/
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.DS_Store
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1 |
.idea/
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2 |
.vscode/
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3 |
.DS_Store
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4 |
+
dev.py
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config.json
ADDED
@@ -0,0 +1,1686 @@
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+
"Payday loan",
|
1666 |
+
"Payday loan, title loan, or personal loan",
|
1667 |
+
"Prepaid card",
|
1668 |
+
"Student loan",
|
1669 |
+
"Vehicle loan or lease",
|
1670 |
+
"Virtual currency"
|
1671 |
+
],
|
1672 |
+
"n_label": 18,
|
1673 |
+
"n_text": 156602,
|
1674 |
+
"n_pair": 156635,
|
1675 |
+
"multi_label": true,
|
1676 |
+
"n_multi_label": 30
|
1677 |
+
}
|
1678 |
+
},
|
1679 |
+
"re-txt_avg_tokens": 202.49348028760807,
|
1680 |
+
"bert-txt_avg_tokens": 293.5908736797742,
|
1681 |
+
"gpt2-txt_avg_tokens": 254.61107137839875,
|
1682 |
+
"re-lb_avg_tokens": 5.312324831614901,
|
1683 |
+
"bert-lb_avg_tokens": 8.884297889999042,
|
1684 |
+
"gpt2-lb_avg_tokens": 6.611644906949277
|
1685 |
+
}
|
1686 |
+
}
|
datasets.zip
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:20d9d447b2c283880abe2a28fbf1f3617cdceda0f3788a1f545ae8df884e7847
|
3 |
+
size 1744258165
|
datasets_joined.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2cee07002b203df72a56ac5b09a56ac625b741ba053b136ecdbceca1036c7193
|
3 |
+
size 1744154943
|
dev.py
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
from stefutil import *
|
2 |
+
|
3 |
+
|
4 |
+
if __name__ == '__main__':
|
5 |
+
from datasets import load_dataset
|
6 |
+
|
7 |
+
dnm = 'claritylab/utcd'
|
8 |
+
mic(load_dataset(dnm))
|
utcd.py
CHANGED
@@ -0,0 +1,143 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
"""Universal Text Classification Dataset (UTCD)"""
|
2 |
+
|
3 |
+
|
4 |
+
import os
|
5 |
+
import json
|
6 |
+
from os.path import join as os_join
|
7 |
+
from typing import List
|
8 |
+
|
9 |
+
import datasets
|
10 |
+
|
11 |
+
from stefutil import *
|
12 |
+
|
13 |
+
|
14 |
+
_DESCRIPTION = """
|
15 |
+
UTCD is a compilation of 18 classification datasets spanning 3 categories of Sentiment,
|
16 |
+
Intent/Dialogue and Topic classification. UTCD focuses on the task of zero-shot text classification where the
|
17 |
+
candidate labels are descriptive of the text being classified. UTCD consists of ~ 6M/800K train/test examples.
|
18 |
+
"""
|
19 |
+
|
20 |
+
# TODO: citation
|
21 |
+
|
22 |
+
_URL = "https://github.com/ChrisIsKing/zero-shot-text-classification/tree/master"
|
23 |
+
_URL_ZIP = "https://huggingface.co/datasets/claritylab/UTCD/raw/main/datasets.zip"
|
24 |
+
|
25 |
+
_VERSION = datasets.Version('0.0.1')
|
26 |
+
|
27 |
+
|
28 |
+
class UtcdConfig(datasets.BuilderConfig):
|
29 |
+
"""BuilderConfig for SuperGLUE."""
|
30 |
+
|
31 |
+
def __init__(self, domain: str, normalize_aspect: bool = False, **kwargs):
|
32 |
+
"""BuilderConfig for UTCD.
|
33 |
+
Args:
|
34 |
+
domain: `string`, dataset domain, one of [`in`, `out`].
|
35 |
+
normalize_aspect: `bool`, if True, an aspect-normalized version of the dataset is returned.
|
36 |
+
**kwargs: keyword arguments forwarded to super.
|
37 |
+
"""
|
38 |
+
# Version history:
|
39 |
+
# 0.0.1: Initial version.
|
40 |
+
super(UtcdConfig, self).__init__(version=_VERSION, **kwargs)
|
41 |
+
ca.check_mismatch('Dataset Domain', domain, ['in', 'out'])
|
42 |
+
self.domain = domain
|
43 |
+
self.normalize_aspect = normalize_aspect
|
44 |
+
|
45 |
+
def to_dir_name(self):
|
46 |
+
"""
|
47 |
+
:return: directory name for the dataset files for this config stored on hub
|
48 |
+
"""
|
49 |
+
domain_str = 'in-domain' if self.domain == 'in' else 'out-of-domain'
|
50 |
+
prefix = 'aspect-normalized-' if self.normalize_aspect else ''
|
51 |
+
return f'{prefix}{domain_str}'
|
52 |
+
|
53 |
+
|
54 |
+
config = StefConfig('config.json')
|
55 |
+
# mic(config('go_emotion'))
|
56 |
+
|
57 |
+
|
58 |
+
class Utcd(datasets.GeneratorBasedBuilder):
|
59 |
+
"""UTCD: Universal Text Classification Dataset. Version 0.0."""
|
60 |
+
|
61 |
+
# _config = dict(
|
62 |
+
# go_emotion=dict(aspect='sentiment', domain='in', name='GoEmotions'),
|
63 |
+
# sentiment_tweets_2020=dict(aspect='sentiment', domain='in', name='TweetEval'),
|
64 |
+
# emotion=dict(aspect='sentiment', domain='in', name='Emotion'),
|
65 |
+
# sgd=dict(aspect='intent', domain='in', name='Schema-Guided Dialogue'),
|
66 |
+
# clinc_150=dict(aspect='intent', domain='in', name='Clinc-150'),
|
67 |
+
# slurp=dict(aspect='intent', domain='in', name='SLURP'),
|
68 |
+
# ag_news=dict(aspect='topic', domain='in', name='AG News'),
|
69 |
+
# dbpedia=dict(aspect='topic', domain='in', name='DBpedia'),
|
70 |
+
# yahoo=dict(aspect='topic', domain='in', name='Yahoo Answer Topics'),
|
71 |
+
#
|
72 |
+
# amazon_polarity=dict(aspect='sentiment', domain='out', name='Amazon Review Polarity'),
|
73 |
+
# finance_sentiment=dict( aspect='sentiment', domain='out', name='Financial Phrase Bank'),
|
74 |
+
# yelp=dict(aspect='sentiment', domain='out', name='Yelp Review'),
|
75 |
+
# banking77=dict(aspect='intent', domain='out', name='Banking77'),
|
76 |
+
# snips=dict(aspect='intent', domain='out', name='SNIPS'),
|
77 |
+
# nlu_evaluation=dict(aspect='intent', domain='out', name='NLU Evaluation'),
|
78 |
+
# multi_eurlex=dict(aspect='topic', domain='out', name='MultiEURLEX'),
|
79 |
+
# patent=dict(aspect='topic', domain='out', name='Big Patent'),
|
80 |
+
# consumer_finance=dict(aspect='topic', domain='out', name='Consumer Finance Complaints')
|
81 |
+
# )
|
82 |
+
|
83 |
+
VERSION = _VERSION
|
84 |
+
|
85 |
+
BUILDER_CONFIGS = [
|
86 |
+
UtcdConfig(
|
87 |
+
name='in-domain',
|
88 |
+
description='All in-domain datasets.',
|
89 |
+
domain='in',
|
90 |
+
normalize_aspect=False
|
91 |
+
),
|
92 |
+
UtcdConfig(
|
93 |
+
name='aspect-normalized-in-domain',
|
94 |
+
description='Aspect-normalized version of all in-domain datasets.',
|
95 |
+
domain='in',
|
96 |
+
normalize_aspect=True
|
97 |
+
),
|
98 |
+
UtcdConfig(
|
99 |
+
name='out-of-domain',
|
100 |
+
description='All out-of-domain datasets.',
|
101 |
+
domain='out',
|
102 |
+
normalize_aspect=False
|
103 |
+
),
|
104 |
+
UtcdConfig(
|
105 |
+
name='aspect-normalized-out-of-domain',
|
106 |
+
description='Aspect-normalized version of all out-of-domain datasets.',
|
107 |
+
domain='out',
|
108 |
+
normalize_aspect=True
|
109 |
+
)
|
110 |
+
]
|
111 |
+
|
112 |
+
def _get_dataset_names(self):
|
113 |
+
return [dnm for dnm, d_dset in config().items() if d_dset['domain'] == self.config.domain]
|
114 |
+
|
115 |
+
def _info(self):
|
116 |
+
dnms = self._get_dataset_names()
|
117 |
+
labels = [config(f'{dnm}.splits.{split}.labels') for dnm in dnms for split in ['train', 'test']]
|
118 |
+
mic(dnms, labels)
|
119 |
+
return datasets.DatasetInfo(
|
120 |
+
description=_DESCRIPTION,
|
121 |
+
features=datasets.Features(
|
122 |
+
text=datasets.Value(dtype='string'), labels=labels, dataset_name=datasets.ClassLabel(names=dnms)
|
123 |
+
),
|
124 |
+
homepage=_URL
|
125 |
+
# TODO: citation
|
126 |
+
)
|
127 |
+
|
128 |
+
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
|
129 |
+
# for aspect-normalized versions of the dataset, we include a validation set
|
130 |
+
splits = ['train', 'eval', 'test'] if self.config.normalize_aspect else ['train', 'test']
|
131 |
+
dnms = self._get_dataset_names()
|
132 |
+
dir_nm = self.config.to_dir_name()
|
133 |
+
split2paths = {s: [os_join(dir_nm, dnm, s) for dnm in dnms] for s in splits}
|
134 |
+
mic(split2paths)
|
135 |
+
|
136 |
+
downloaded_files = dl_manager.download_and_extract('datasets.zip')
|
137 |
+
mic(downloaded_files)
|
138 |
+
raise NotImplementedError
|
139 |
+
|
140 |
+
return [
|
141 |
+
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
|
142 |
+
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
|
143 |
+
]
|