File size: 4,043 Bytes
e852793 b951a6a e852793 261f57a e852793 4e8ce24 e852793 b951a6a e852793 fa4a72e e852793 fa4a72e e852793 fa4a72e e852793 fa4a72e e852793 986bcac 88e5b61 986bcac 88e5b61 986bcac 88e5b61 b951a6a 986bcac e852793 986bcac e852793 |
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 |
import json
import bz2
import datasets
from datasets import DownloadManager, DatasetInfo
class WSDMTConfig(datasets.BuilderConfig):
def __init__(self, *args, corpus, lang1, lang2, **kwargs):
super().__init__(
*args,
name=f"{corpus}@{lang1}-{lang2}",
**kwargs,
)
self.lang1 = lang1
self.lang2 = lang2
self.corpus = corpus
def path_for(self, split, lang):
return f"data/{self.corpus}/{split}/{lang}.jsonl.bz2"
class WSDMTDataset(datasets.GeneratorBasedBuilder):
BUILDER_CONFIG_CLASS = WSDMTConfig
config: WSDMTConfig
def _generate_examples(self, path_lang1, path_lang2):
with bz2.open(path_lang1) as f1, bz2.open(path_lang2) as f2:
for n, (line1, line2) in enumerate(zip(f1, f2)):
sentence1_data = json.loads(line1)
sentence2_data = json.loads(line2)
texts1, senses1, is_senses1, is_polysemous1 = zip(*sentence1_data['data'])
texts2, senses2, is_senses2, is_polysemous2 = zip(*sentence2_data['data'])
sid1, sid2 = sentence1_data['sid'], sentence2_data['sid']
assert sid1 == sid2, (
f"Different sentence id found for {self.config.lang1} and {self.config.lang2}: "
f"{sid1} != {sid2} at line {n}"
)
data_dict = {
'sid': sid1,
self.config.lang1: dict(tokens=texts1, sense=senses1,
identified_as_sense=is_senses1,
is_polysemous=is_polysemous1),
self.config.lang2: dict(tokens=texts2, sense=senses2,
identified_as_sense=is_senses2,
is_polysemous=is_polysemous2),
}
yield n, data_dict
def _info(self) -> DatasetInfo:
return datasets.DatasetInfo(
description="empty description",
features=datasets.Features(
{
"sid": datasets.Value("string"),
self.config.lang1: {
"tokens": datasets.Sequence(datasets.Value("string")),
"sense": datasets.Sequence(datasets.Value("string")),
"identified_as_sense": datasets.Sequence(datasets.Value("bool")),
"is_polysemous": datasets.Sequence(datasets.Value("bool")),
},
self.config.lang2: {
"tokens": datasets.Sequence(datasets.Value("string")),
"sense": datasets.Sequence(datasets.Value("string")),
"identified_as_sense": datasets.Sequence(datasets.Value("bool")),
"is_polysemous": datasets.Sequence(datasets.Value("bool")),
}
},
),
supervised_keys=None,
homepage="no-homepage",
citation="no-citation",
)
def _split_generators(self, dl_manager: DownloadManager):
splits_file = dl_manager.download(f'data/{self.config.corpus}/splits.txt')
with open(splits_file) as f:
split_names = [line.rstrip() for line in f]
urls = {
split: {
self.config.lang1: self.config.path_for(split, self.config.lang1),
self.config.lang2: self.config.path_for(split, self.config.lang2),
}
for split in split_names
}
downloaded = dl_manager.download(urls)
return [
datasets.SplitGenerator(name=split,
gen_kwargs=dict(
path_lang1=paths[self.config.lang1],
path_lang2=paths[self.config.lang2],
))
for split, paths in downloaded.items()
]
|