Giguru Scheuer
commited on
Commit
•
0647863
1
Parent(s):
8205a6a
Updated
Browse files- canard_quretec.py +25 -10
canard_quretec.py
CHANGED
@@ -21,7 +21,6 @@ import os
|
|
21 |
import datasets
|
22 |
|
23 |
|
24 |
-
# TODO: Add BibTeX citation
|
25 |
# Find for instance the citation on arxiv or on the dataset repo/website
|
26 |
_CITATION = """\
|
27 |
@inproceedings{Elgohary:Peskov:Boyd-Graber-2019,
|
@@ -49,8 +48,23 @@ _LICENSE = "CC BY-SA 4.0"
|
|
49 |
|
50 |
# The HuggingFace dataset library don't host the datasets but only point to the original files
|
51 |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
|
|
|
52 |
_URLs = {
|
53 |
-
'
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
54 |
}
|
55 |
|
56 |
|
@@ -74,7 +88,8 @@ class CanardQuretec(datasets.GeneratorBasedBuilder):
|
|
74 |
# data = datasets.load_dataset('my_dataset', 'second_domain')
|
75 |
BUILDER_CONFIGS = [
|
76 |
datasets.BuilderConfig(name="gold_supervision", version=VERSION, description="Was used for training quretec with gold supervision"),
|
77 |
-
|
|
|
78 |
]
|
79 |
|
80 |
# It's not mandatory to have a default configuration. Just use one if it make sense.
|
@@ -122,26 +137,26 @@ class CanardQuretec(datasets.GeneratorBasedBuilder):
|
|
122 |
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
|
123 |
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
|
124 |
my_urls = _URLs[self.config.name]
|
125 |
-
|
126 |
return [
|
127 |
datasets.SplitGenerator(
|
128 |
name=datasets.Split.TRAIN,
|
129 |
gen_kwargs={ # These kwargs will be passed to _generate_examples
|
130 |
-
"filepath":
|
131 |
"split": "train",
|
132 |
},
|
133 |
),
|
134 |
datasets.SplitGenerator(
|
135 |
name=datasets.Split.TEST,
|
136 |
gen_kwargs={ # These kwargs will be passed to _generate_examples
|
137 |
-
"filepath":
|
138 |
"split": "test"
|
139 |
},
|
140 |
),
|
141 |
datasets.SplitGenerator(
|
142 |
name=datasets.Split.VALIDATION,
|
143 |
gen_kwargs={ # These kwargs will be passed to _generate_examples
|
144 |
-
"filepath":
|
145 |
"split": "dev",
|
146 |
},
|
147 |
),
|
@@ -155,7 +170,7 @@ class CanardQuretec(datasets.GeneratorBasedBuilder):
|
|
155 |
# The `key` is here for legacy reason (tfds) and is not important in itself.
|
156 |
|
157 |
with open(filepath) as f:
|
158 |
-
|
159 |
-
for id_,
|
160 |
# if self.config.name == "first_domain":
|
161 |
-
yield id_,
|
|
|
21 |
import datasets
|
22 |
|
23 |
|
|
|
24 |
# Find for instance the citation on arxiv or on the dataset repo/website
|
25 |
_CITATION = """\
|
26 |
@inproceedings{Elgohary:Peskov:Boyd-Graber-2019,
|
|
|
48 |
|
49 |
# The HuggingFace dataset library don't host the datasets but only point to the original files
|
50 |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
|
51 |
+
_URL = "https://drive.google.com/drive/folders/1e3s-V6VQqOKHrmn_kBStNsV0gGHPeJVf/"
|
52 |
_URLs = {
|
53 |
+
'gold_supervision': {
|
54 |
+
'train': _URL+"train_gold_supervision.json",
|
55 |
+
'dev': _URL+"dev_gold_supervision.json",
|
56 |
+
'test': _URL+"test_gold_supervision.json"
|
57 |
+
},
|
58 |
+
'original_all': {
|
59 |
+
'train': _URL+"train_original_all.json",
|
60 |
+
'dev': _URL+"dev_original_all.json",
|
61 |
+
'test': _URL+"test_original_all.json"
|
62 |
+
},
|
63 |
+
'distant_supervision': {
|
64 |
+
'train': _URL+"train_distant_supervision.json",
|
65 |
+
'dev': _URL+"dev_distant_supervision.json",
|
66 |
+
'test': _URL+"test_distant_supervision.json"
|
67 |
+
}
|
68 |
}
|
69 |
|
70 |
|
|
|
88 |
# data = datasets.load_dataset('my_dataset', 'second_domain')
|
89 |
BUILDER_CONFIGS = [
|
90 |
datasets.BuilderConfig(name="gold_supervision", version=VERSION, description="Was used for training quretec with gold supervision"),
|
91 |
+
datasets.BuilderConfig(name="original_all", version=VERSION, description="Was used for creating dataset statistics"),
|
92 |
+
datasets.BuilderConfig(name="distant_supervision", version=VERSION, description="Was used for training quretec with distant supervision"),
|
93 |
]
|
94 |
|
95 |
# It's not mandatory to have a default configuration. Just use one if it make sense.
|
|
|
137 |
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
|
138 |
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
|
139 |
my_urls = _URLs[self.config.name]
|
140 |
+
downloaded_files = dl_manager.download_and_extract(my_urls)
|
141 |
return [
|
142 |
datasets.SplitGenerator(
|
143 |
name=datasets.Split.TRAIN,
|
144 |
gen_kwargs={ # These kwargs will be passed to _generate_examples
|
145 |
+
"filepath": downloaded_files['train'],
|
146 |
"split": "train",
|
147 |
},
|
148 |
),
|
149 |
datasets.SplitGenerator(
|
150 |
name=datasets.Split.TEST,
|
151 |
gen_kwargs={ # These kwargs will be passed to _generate_examples
|
152 |
+
"filepath": downloaded_files['test'],
|
153 |
"split": "test"
|
154 |
},
|
155 |
),
|
156 |
datasets.SplitGenerator(
|
157 |
name=datasets.Split.VALIDATION,
|
158 |
gen_kwargs={ # These kwargs will be passed to _generate_examples
|
159 |
+
"filepath": downloaded_files['dev'],
|
160 |
"split": "dev",
|
161 |
},
|
162 |
),
|
|
|
170 |
# The `key` is here for legacy reason (tfds) and is not important in itself.
|
171 |
|
172 |
with open(filepath) as f:
|
173 |
+
data_array = json.load(f)
|
174 |
+
for id_, item_dict in data_array:
|
175 |
# if self.config.name == "first_domain":
|
176 |
+
yield id_, item_dict
|