File size: 2,183 Bytes
5ab80af |
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 |
import csv
from typing import List
import datasets
LANGUAGES = ["ar", "de", "es", "fr", "hi", "it", "ja", "ko", "pl", "pt", "ta", "zh"]
DATA_PATH = "test.csv"
class XPQAConfig(datasets.BuilderConfig):
def __init__(self, language, **kwargs):
super().__init__(**kwargs)
self.language = language
class XPQA(datasets.GeneratorBasedBuilder):
BUILDER_CONFIG_CLASS = XPQAConfig
BUILDER_CONFIGS = [
XPQAConfig(name=language, language=language) for language in LANGUAGES
]
def _info(self):
return datasets.DatasetInfo(
description="xPQA is a large-scale annotated cross-lingual Product QA dataset.",
features=datasets.Features(
{
"id": datasets.Value("string"),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
}
),
homepage="https://github.com/amazon-science/contextual-product-qa/tree/main?tab=readme-ov-file#xpqa",
citation="https://arxiv.org/abs/2305.09249",
)
def _split_generators(
self, dl_manager: datasets.DownloadManager
) -> List[datasets.SplitGenerator]:
return [
datasets.SplitGenerator(
name=datasets.Split.TEST, gen_kwargs={"filepath": DATA_PATH}
),
]
def _generate_examples(self, filepath):
id_ = 0
with open(filepath, newline="") as csvfile:
csvreader = csv.reader(csvfile, delimiter=",")
header = next(csvreader)
lang_pos = header.index("lang")
answer_pos = header.index("answer")
question_pos = header.index("question")
label_pos = header.index("label")
for row in csvreader:
if row[lang_pos] == self.config.language and row[label_pos] == "2":
answer = row[answer_pos]
question = row[question_pos]
if not answer or not question:
continue
yield id_, {"id": id_, "question": question, "answer": answer}
id_ += 1
|