Datasets:
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import os
import datasets
import json
import pandas as pd
_CITATION = """\
"""
_DESCRIPTION = """\
CSAT-QA
"""
_HOMEPAGE = "https://huggingface.co/HAERAE-HUB"
_LICENSE = "Proprietary"
split_names = ["all","WR", "GR", "RCS", "RCSS", "RCH", "LI"]
class CSATQAConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super().__init__(version=datasets.Version("1.0.0"), **kwargs)
class CSATQA(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
CSATQAConfig(
name=name,
)
for name in split_names
]
def _info(self):
features = datasets.Features(
{
"question": datasets.Value("string"),
"context" : datasets.Value("string"),
"option#1": datasets.Value("string"),
"option#2": datasets.Value("string"),
"option#3": datasets.Value("string"),
"option#4": datasets.Value("string"),
"option#5": datasets.Value("string"),
"gold": datasets.Value("int8"),
"category": datasets.Value("string"),
"human_peformance": datasets.Value("float16"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
train_path = dl_manager.download_and_extract("./data/csatqa_eval.json")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": train_path,
},
),
]
def _generate_examples(self, filepath):
with open(filepath, encoding="utf-8") as f:
buffer = []
for key, row in enumerate(f):
data = json.loads(row)
buffer.append({
"question": data["question"],
"context" : data["context"],
"option#1": data["option#1"],
"option#2": data["option#2"],
"option#3": data["option#3"],
"option#4": data["option#4"],
"option#5": data["option#5"],
"gold": data["gold"],
"category": data["category"],
"human_peformance": data["human_performance"]})
for idx, dat in enumerate(buffer):
yield idx,dat
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