File size: 1,851 Bytes
7e9d0fb |
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 |
"""
""" # TODO
try:
import ir_datasets
except ImportError as e:
raise ImportError('ir-datasets package missing; `pip install ir-datasets`')
import datasets
IRDS_ID = 'lotte/science/dev'
IRDS_ENTITY_TYPES = {'docs': {'doc_id': 'string', 'text': 'string'}}
_CITATION = '@article{Santhanam2021ColBERTv2,\n title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",\n author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia", \n journal= "arXiv preprint arXiv:2112.01488",\n year = "2021",\n url = "https://arxiv.org/abs/2112.01488"\n}'
_DESCRIPTION = "" # TODO
class lotte_science_dev(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [datasets.BuilderConfig(name=e) for e in IRDS_ENTITY_TYPES]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features({k: datasets.Value(v) for k, v in IRDS_ENTITY_TYPES[self.config.name].items()}),
homepage=f"https://ir-datasets.com/lotte#lotte/science/dev",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
return [datasets.SplitGenerator(name=self.config.name)]
def _generate_examples(self):
dataset = ir_datasets.load(IRDS_ID)
for i, item in enumerate(getattr(dataset, self.config.name)):
key = i
if self.config.name == 'docs':
key = item.doc_id
elif self.config.name == 'queries':
key = item.query_id
yield key, item._asdict()
def as_dataset(self, split=None, *args, **kwargs):
split = self.config.name # always return split corresponding with this config to avid returning a redundant DatasetDict layer
return super().as_dataset(split, *args, **kwargs)
|