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relentless / relentless.py
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"""
from datasets import load_dataset
data = load_dataset(".")
"""
import json
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """ Named-entities Relation Ranking. """
_NAME = "relentless"
_VERSION = "0.2.4"
_CITATION = """TBA"""
_HOME_PAGE = "https://huggingface.co/datasets/cardiffnlp/relentless"
_URL = f'https://huggingface.co/datasets/cardiffnlp/{_NAME}/raw/main'
_URLS = {
str(datasets.Split.VALIDATION): [f'{_URL}/data/data_processed.new.validation.jsonl'],
str(datasets.Split.TEST): [f'{_URL}/data/data_processed.new.test.jsonl']
}
class RelentlessConfig(datasets.BuilderConfig):
"""BuilderConfig"""
def __init__(self, **kwargs):
"""BuilderConfig.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(RelentlessConfig, self).__init__(**kwargs)
class Relentless(datasets.GeneratorBasedBuilder):
"""Dataset."""
BUILDER_CONFIGS = [RelentlessConfig(version=datasets.Version(_VERSION), description=_DESCRIPTION)]
def _split_generators(self, dl_manager):
# downloaded_file = dl_manager.download_and_extract(_URLS[self.config.name])
downloaded_file = dl_manager.download_and_extract(_URLS)
return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]})
for i in [datasets.Split.VALIDATION, datasets.Split.TEST]]
def _generate_examples(self, filepaths):
_key = 0
for filepath in filepaths:
logger.info(f"generating examples from = {filepath}")
with open(filepath, encoding="utf-8") as f:
_list = [i for i in f.read().split('\n') if len(i) > 0]
for i in _list:
data = json.loads(i)
yield _key, data
_key += 1
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"pairs": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
"scores_all": datasets.Sequence(datasets.Sequence(datasets.Value('int32'))),
"scores_mean": datasets.Sequence(datasets.Value("float32")),
"relation_type": datasets.Value("string"),
"prototypical_examples": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
"ranks": datasets.Sequence(datasets.Value('int32'))
}
),
supervised_keys=None,
homepage=_HOME_PAGE,
citation=_CITATION,
)