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import datasets
import json
import ast
import pandas as pd
import csv
_DESCRIPTION = """\
The dataset is an amendment and re-annotation of LogiQA in 2020, a large-scale logical reasoning reading comprehension dataset adapted from the Chinese Civil Service Examination. We increase the data size, refine the texts with manual translation by professionals, and improve the quality by removing items with distinctive cultural features like Chinese idioms. Furthermore, we conduct a fine-grained annotation on the dataset and turn it into a two-way natural language inference (NLI) task, resulting in 35k premise-hypothesis pairs with gold labels, making it the first large-scale NLI dataset for complex logical reasoning
"""
english_qa_datasets = ["lsat-ar", "lsat-lr", "lsat-rc", "logiqa-en", "sat-math", "sat-en", "aqua-rat",
"sat-en-without-passage", "gaokao-english"]
chinese_qa_datasets = ["logiqa-zh", "jec-qa-kd", "jec-qa-ca", "gaokao-chinese", "gaokao-geography", "gaokao-history",
"gaokao-biology", "gaokao-chemistry", "gaokao-physics", "gaokao-mathqa"]
english_cloze_datasets = ["math"]
chinese_cloze_datasets = ["gaokao-mathcloze"]
all_lst = english_qa_datasets + chinese_qa_datasets + english_cloze_datasets + chinese_cloze_datasets
HEAD= 'https://raw.githubusercontent.com/microsoft/AGIEval/main/data/v1/'
_URLS = {
e: {
"test": HEAD+e+'.jsonl',
} for e in all_lst
}
_URLS['few_shot'] ={'few_shot':'https://raw.githubusercontent.com/microsoft/AGIEval/main/data/few_shot_prompts.csv'}
class AgiEval(datasets.GeneratorBasedBuilder):
"""TODO: Short description of my dataset."""
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name= e,
version=datasets.Version("2.0.1"),
description="",
) for e in all_lst
]
DEFAULT_CONFIG_NAME = "aqua_rat"
def _info(self):
if self.config.name == "aqua_rat":
features = datasets.Features(
{
"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"options": datasets.features.Sequence(datasets.Value("string")),
"label": datasets.ClassLabel(num_classes=5, names=["A", "B", "C", "D", "E"]),
"solution": datasets.Value("string"),
}
)
elif self.config.name in ["sat_en", "sat_math", "sat-en-without-passage"]:
features = datasets.Features(
{"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"options": datasets.features.Sequence(datasets.Value("string")),
"label": datasets.ClassLabel(num_classes=4, names=["A", "B", "C", "D"]),
"solution": datasets.Value("string"),
}
)
elif self.config.name in ['logiqa-en', 'logiqa-zh']:
# remove solution from other
features = datasets.Features(
{"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"options": datasets.features.Sequence(datasets.Value("string")),
"label": datasets.ClassLabel(num_classes=4, names=["A", "B", "C", "D"]),
"solution": datasets.Value("string"),
}
)
elif self.config.name == 'math':
features = datasets.Features(
{
"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"solution": datasets.Value("string"),
"level": datasets.Value("int32"),
"type": datasets.Value("string"),
}
)
elif self.config.name == 'gaokao-mathcloze':
features = datasets.Features(
{
"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"solution": datasets.Value("string"),
}
)
elif self.config.name in ['lsat_lr', 'lsat_rc', 'lsat_ar']:
features = datasets.Features(
{
"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"options": datasets.features.Sequence(datasets.Value("string")),
"label": datasets.ClassLabel(num_classes=5, names=["A", "B", "C", "D", "E"]),
"solution": datasets.Value("string"),
}
)
elif self.config.name in ['gaokao-mathqa', 'gaokao-chinese', 'gaokao-history', 'gaokao-geography', 'gaokao-biology', 'gaokao-chemistry', 'gaokao-english']:
features = datasets.Features(
{
"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"options": datasets.features.Sequence(datasets.Value("string")),
"label": datasets.features.Sequence(datasets.Value("string")),
"solution": datasets.Value("string"),
}
)
elif self.config.name in ['gaokao-physics', 'jec-qa-ca', 'jec-qa-kd']:
features = datasets.Features(
{
"passage": datasets.Value("string"),
"question": datasets.Value("string"),
"options": datasets.features.Sequence(datasets.Value("string")),
"label": datasets.ClassLabel(num_classes=4, names=["A", "B", "C", "D"]),
"solution": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
_urls = _URLS[self.config.name]
urls = {
"test": _urls["test"],
"few_shot": _URLS["few_shot"]["few_shot"],
}
data_dir = dl_manager.download_and_extract(urls)
splits = [
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"filepath": data_dir["test"], "split": "test"},
),
]
splits.append(datasets.SplitGenerator(
name="few_shot",
gen_kwargs={"filepath": data_dir["few_shot"], "split": "few_shot"},
))
return splits
def _generate_examples(self, filepath, split):
# Mapping for column names in CSV to dataset names
names = {'aqua_rat': 'aqua-rat', 'sat_en': 'sat-en', 'sat_math': 'sat-math',
'lsat_ar': 'lsat-ar', 'lsat_lr': 'lsat-lr', 'lsat_rc': 'lsat-rc',
'logiqa': 'logiqa-en', 'math_agieval': 'math'}
if split == "few_shot":
# Load the data from the CSV
df = pd.read_csv(filepath, keep_default_na=False)
# Extract samples and explanations
samples = df[df.index % 2 == 0].reset_index(drop=True)
explanations = df[df.index % 2 != 0].reset_index(drop=True)
for key in range(samples.shape[0]):
try:
data = ast.literal_eval(samples[names[self.config.name]][key])
explanation_row = explanations[names[self.config.name]][key]
if self.config.name == "aqua_rat":
features = datasets.Features(
{
"passage": data["passage"],
"question": data["question"],
"options": data["options"],
"label": data["label"],
"solution": str(explanation_row),
}
)
elif self.config.name in ["sat_en", "sat_math", "sat-en-without-passage"]:
features = datasets.Features(
{
"passage": data["passage"],
"question": data["question"],
"options": data["options"],
"label": data["label"],
"solution": str(explanation_row),
}
)
elif self.config.name in ['logiqa-en', 'logiqa-zh']:
# remove solution from other
features = datasets.Features(
{
"passage": data["passage"],
"question": data["question"],
"options": data["options"],
"label": data["label"],
"solution": str(explanation_row),
}
)
elif self.config.name == 'math':
features = datasets.Features(
{
"passage": data["passage"],
"question": data["question"],
"answer": data["answer"],
"solution": str(explanation_row),
"level": data["level"],
"type": data["type"],
}
)
elif self.config.name == 'gaokao-mathcloze':
features = datasets.Features(
{
"passage": data["passage"],
"question": data["question"],
"answer": data["answer"],
"solution": str(explanation_row),
}
)
elif self.config.name in ['lsat_lr', 'lsat_rc', 'lsat_ar']:
features = datasets.Features(
{
"passage": data["passage"],
"question": data["passquestionage"],
"options": data["options"],
"label": data["label"],
"solution": str(explanation_row),
}
)
elif self.config.name in ['gaokao-mathqa', 'gaokao-chinese', 'gaokao-history', 'gaokao-geography', 'gaokao-biology', 'gaokao-chemistry', 'gaokao-english']:
features = datasets.Features(
{
"passage": data["passage"],
"question": data["question"],
"options": data["options"],
"label": data["label"],
"solution": str(explanation_row),
}
)
elif self.config.name in ['gaokao-physics', 'jec-qa-ca', 'jec-qa-kd']:
features = datasets.Features(
{
"passage": data["passage"],
"question": data["question"],
"options": data["options"],
"label": data["label"],
"solution": str(explanation_row),
}
)
except:
pass
else:
with open(filepath, encoding="utf-8") as f:
for key, row in enumerate(f):
data = json.loads(row)
if self.config.name == "aqua_rat":
yield key, {
"passage": data["passage"],
"question": data["question"],
"options": data["options"],
"label": data["label"],
"solution": data["other"]["solution"],
}
elif self.config.name in ["sat_en", "sat_math", "sat-en-without-passage"]:
label_index = "ABCDE".index(data["label"])
if label_index > len(data["options"]) - 1:
continue
else:
yield key, {
"passage": data["passage"],
"question": data["question"],
"options": data["options"],
"label": data["label"],
"solution": data["other"]["solution"],
}
elif self.config.name in ['logiqa-en', 'logiqa-zh']:
yield key, {
"passage": data["passage"],
"question": data["question"],
"options": data["options"],
"label": data["label"],
"solution": data["label"],
}
elif self.config.name == 'math':
if not data.get("level"):
data["level"] = data['other']['level']
if not data.get("type"):
data["type"] = data['other']['type']
yield key, {
"question": data["question"],
"answer": data["answer"],
"solution": data["other"]["solution"],
"level": data["level"],
"type": data["type"],
}
elif self.config.name == 'gaokao-mathcloze':
yield key, {
"passage": data["passage"],
"question": data["question"],
"answer": data["answer"],
"solution": data["answer"],
}
elif self.config.name in ['lsat_lr', 'lsat_rc', 'lsat_ar']:
yield key, {
"passage": data["passage"],
"question": data["passquestionage"],
"options": data["options"],
"label": data["label"],
"solution": data["label"],
}
elif self.config.name in ['gaokao-mathqa', 'gaokao-chinese', 'gaokao-history', 'gaokao-geography', 'gaokao-biology', 'gaokao-chemistry', 'gaokao-english']:
yield key, {
"passage": data["passage"],
"question": data["passquestionage"],
"options": data["options"],
"label": data["label"],
"solution": data["label"],
}
elif self.config.name in ['gaokao-physics', 'jec-qa-ca', 'jec-qa-kd']:
yield key, {
"passage": data["passage"],
"question": data["passquestionage"],
"options": data["options"],
"label": data["label"],
"solution": data["label"],
} |