Datasets:

ZoneTwelve
/

tmmluplus

	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	import os

	import datasets
	import pandas as pd


	_DESCRIPTION = """\
	TMMLU2 data loader
	"""
	_DATA_PATH = "data"

	task_list = [
	'dentistry', 'traditional_chinese_medicine_clinical_medicine', 'clinical_psychology',
	'technical', 'culinary_skills', 'mechanical', 'logic_reasoning', 'real_estate',
	'general_principles_of_law', 'finance_banking', 'anti_money_laundering', 'ttqav2',
	'marketing_management', 'business_management', 'organic_chemistry', 'advance_chemistry',
	'physics', 'secondary_physics', 'human_behavior', 'national_protection', 'jce_humanities',
	'politic_science', 'agriculture', 'official_document_management',
	'financial_analysis', 'pharmacy', 'educational_psychology', 'statistics_and_machine_learning',
	'management_accounting', 'introduction_to_law', 'computer_science', 'veterinary_pathology',
	'accounting', 'fire_science', 'optometry', 'insurance_studies', 'pharmacology', 'taxation',
	'education_(profession_level)', 'economics',
	'veterinary_pharmacology', 'nautical_science', 'occupational_therapy_for_psychological_disorders',
	'trust_practice', 'geography_of_taiwan', 'physical_education', 'auditing', 'administrative_law',
	'basic_medical_science', 'macroeconomics', 'trade', 'chinese_language_and_literature',
	'tve_design', 'junior_science_exam', 'junior_math_exam', 'junior_chinese_exam',
	'junior_social_studies', 'tve_mathematics', 'tve_chinese_language',
	'tve_natural_sciences', 'junior_chemistry', 'music', 'education',
	'three_principles_of_people', 'taiwanese_hokkien',
	'engineering_math', 'linear_algebra'
	]

	_URLs = {
	task_name: {
	split_name: [
	os.path.join(
	_DATA_PATH, task_name+"_"+split_name+".csv"
	), # TODO -> handle multiple shards
	]
	for split_name in ['dev', 'test', 'val']
	}
	for task_name in task_list
	}


	class TMMLU2Config(datasets.BuilderConfig):
	def __init__(self, **kwargs):
	super().__init__(version=datasets.Version("1.0.0"), **kwargs)


	class TMMLU2(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [
	TMMLU2Config(
	name=task_name,
	)
	for task_name in task_list
	]

	def _info(self):
	features = datasets.Features(
	{
	"question": datasets.Value("string"),
	"A": datasets.Value("string"),
	"B": datasets.Value("string"),
	"C": datasets.Value("string"),
	"D": datasets.Value("string"),
	"answer": datasets.Value("string"),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	)

	def _split_generators(self, dl_manager):
	task_name = self.config.name
	data_dir = dl_manager.download(_URLs[task_name])
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": data_dir['test'],
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": data_dir['val'],
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": data_dir['dev'],
	},
	),
	]

	def _generate_examples(self, filepath):
	if isinstance(filepath, list):
	filepath = filepath[0]
	df = pd.read_csv(filepath)

	for i, instance in enumerate(df.to_dict(orient="records")):
	yield i, {'question': instance['question'],
	'A': instance['A'],
	'B': instance['B'],
	'C': instance['C'],
	'D': instance['D'],
	'answer': instance['answer']
	}