Datasets:
File size: 2,697 Bytes
81e5cba |
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 |
import json
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """\
Ukrainian Multi30k
"""
_CITATION = """\
"""
_URLS = {
"train" : "train.json",
"flickr_2016" : "test_2016_flickr.json",
"flickr_2017" : "test_2017_flickr.json",
"flickr_2018" : "test_2018_flickr.json",
"mscoco_2017" : "test_2017_mscoco.json"
}
class UkrainianMulti30k(datasets.GeneratorBasedBuilder):
"""Ukrainian Multi30k Dataset"""
VERSION = datasets.Version("0.0.1")
DEFAULT_CONFIG_NAME = "multi30k"
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="multi30k", version=VERSION, description=""),
datasets.BuilderConfig(name="flickr_2016", version=VERSION, description=""),
datasets.BuilderConfig(name="flickr_2017", version=VERSION, description=""),
datasets.BuilderConfig(name="flickr_2018", version=VERSION, description=""),
datasets.BuilderConfig(name="mscoco_2017", version=VERSION, description=""),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"en": datasets.Value("string"),
"uk": datasets.Value("string")
}
),
citation=_CITATION,
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download(_URLS)
if self.config.name == "multi30k":
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files["train"]})
]
elif self.config.name == "flickr_2016":
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files["flickr_2016"]})
]
elif self.config.name == "flickr_2017":
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files["flickr_2017"]})
]
elif self.config.name == "flickr_2018":
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files["flickr_2018"]})
]
elif self.config.name == "mscoco_2017":
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files["mscoco_2017"]})
]
def _generate_examples(self, filepaths):
with open(filepaths, encoding="utf-8") as f:
for num, rows_str in enumerate(f):
rows = json.loads(rows_str)
yield num, rows |