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import json
from dataclasses import dataclass
from string import Template
import datasets
_CITATION = "" # TODO: @theyorubayesian
_DESCRIPTION = \
"""
A collection of passages culled from news websites for Cross-Lingual Information Retrieval for African Languages.
"""
_HOMEPAGE = "https://github.com/ciral/ciral-corpus"
_LICENSE = "Apache License 2.0"
_VERSION = "1.0.0"
_LANGUAGES = [
"hausa",
"somali",
"swahili",
"yoruba",
"combined"
]
_DATASET_URL = Template("./${mode}passages-v1.0/${language}_passages.jsonl")
@dataclass
class CiralConfig(datasets.BuilderConfig):
translated: bool = False
file_stub_dict = {
None: "",
True: "translated-",
False: ""
}
def get_file_url(self, language: str) -> str:
return _DATASET_URL.substitute(
mode=self.file_stub_dict.get(self.translated),
language=language
)
class CiralPassages(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
CiralConfig(
version=datasets.Version(_VERSION),
name=language,
description=f"CIRAL passages for language: {language}"
) for language in _LANGUAGES
]
DEFAULT_CONFIG_NAME = "combined"
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
citation=_CITATION,
features=datasets.Features({
"docid": datasets.Value("string"),
"title": datasets.Value("string"),
"text": datasets.Value("string"),
"url": datasets.Value("string")
}),
homepage=_HOMEPAGE,
license=_LICENSE
)
def _split_generators(self, dl_manager: datasets.DownloadManager):
language = self.config.name
if language == "combined":
language_file = dl_manager.download_and_extract({
_language: self.config.get_file_url(language=_language)
for _language in _LANGUAGES[:-1]
})
splits = [
datasets.SplitGenerator(
name=_language, gen_kwargs={"filepath": language_file[_language]}
) for _language in _LANGUAGES[:-1]
]
else:
language_file = dl_manager.download_and_extract(
self.config.get_file_url(language=language))
splits = [
datasets.SplitGenerator(
name="train",
gen_kwargs={"filepath": language_file}
)
]
return splits
def _generate_examples(self, filepath: str):
with open(filepath, encoding="utf-8") as f:
for line in f:
data = json.loads(line)
yield data["docid"], data
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