# coding=utf-8 # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors. # # 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. # Lint as: python3 """The General Language Understanding Evaluation (GLUE) benchmark.""" import csv import os import sys import json import io import textwrap import numpy as np import datasets _CMB_CITATION = """\ coming soon~ """ _CMB_DESCRIPTION = """\ coming soon~ """ _DATASETS_FILE = "https://huggingface.co/datasets/FreedomIntelligence/CMB/resolve/main/CMB-datasets.zip" class CMBConfig(datasets.BuilderConfig): """BuilderConfig for GLUE.""" def __init__( self, features, data_url, data_dir, citation, url, **kwargs, ): super(CMBConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs) self.features = features self.data_url = data_url self.data_dir = data_dir self.citation = citation self.url = url class CMB(datasets.GeneratorBasedBuilder): """The General Language Understanding Evaluation (GLUE) benchmark.""" BUILDER_CONFIGS = [ CMBConfig( name="main", description=textwrap.dedent( """\ 主要数据集，包含 train val test 三个组成部分.""" ), features=datasets.Features( { "id": datasets.Value("string"), "exam_type": datasets.Value("string"), "exam_class": datasets.Value("string"), "chapter": datasets.Value("string"), "exam_subject": datasets.Value("string"), "exercise": datasets.Value("string"), "question": datasets.Value("string"), "question_type": datasets.Value("string"), "option": datasets.Value("string"), "answer": datasets.Value("string"), "explanation": datasets.Value("string") } ), data_url=_DATASETS_FILE, data_dir="CMB-main", citation=textwrap.dedent( """\ }""" ), url="https://github.com/FreedomIntelligence/CMB", ), CMBConfig( name="paper-exampaper", description=textwrap.dedent( """\ 历史真题 .""" ), features=datasets.Features( { "id": datasets.Value("string"), "source": datasets.Value("string"), "exam_type": datasets.Value("string"), "exam_class": datasets.Value("string"), "exam_subject": datasets.Value("string"), "question": datasets.Value("string"), "question_type": datasets.Value("string"), "option": datasets.Value("string"), "answer": datasets.Value("string") } ), data_url=_DATASETS_FILE, data_dir="CMB-test-exampaper", citation=textwrap.dedent( """\ }""" ), url="https://github.com/FreedomIntelligence/CMB", ), CMBConfig( name="qa", description=textwrap.dedent( """\ QA 格式的考题 """ ), features=datasets.Features( { "id": datasets.Value("string"), "title": datasets.Value("string"), "description": datasets.Value("string"), "QA_pairs": datasets.Value("string") } ), data_url=_DATASETS_FILE, data_dir="CMB-test-qa", citation=textwrap.dedent( """\ }""" ), url="https://github.com/FreedomIntelligence/CMB", ), ] def _info(self): return datasets.DatasetInfo( description=_CMB_DESCRIPTION, features=self.config.features, homepage=self.config.url, citation=self.config.citation + "\n" + _CMB_CITATION, ) def _split_generators(self, dl_manager): if self.config.name == "main": data_file = dl_manager.extract(self.config.data_url) main_data_dir = os.path.join(data_file, self.config.data_dir) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_file": os.path.join(main_data_dir, 'CMB-train', 'CMB-train-merge.json'), "split": "train", }, ) , datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "data_file": os.path.join(main_data_dir, 'CMB-val', 'CMB-val-merge.json'), "split": "val", }, ) , datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_file": os.path.join(main_data_dir, 'CMB-test', 'CMB-test-choice-question-merge.json'), "split": "test", }, ) ] if self.config.name == "paper-exampaper": data_file = dl_manager.extract(self.config.data_url) main_data_dir = os.path.join(data_file, self.config.data_dir) return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_file": os.path.join(main_data_dir, 'CMB-test-zhenti-merge.json'), "split": "test", }, ) ] if self.config.name == "qa": data_file = dl_manager.extract(self.config.data_url) main_data_dir = os.path.join(data_file, self.config.data_dir) return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_file": os.path.join(main_data_dir, 'CMB-test-qa.json'), "split": "test", }, ) ] def _generate_examples(self, data_file, split, mrpc_files=None): if self.config.name == 'main': examples = json.loads(io.open(data_file, 'r').read()) for idx in range(len(examples)): vals = examples[idx] vals['explanation'] = vals.get('explanation','') vals['exercise'] = vals.get('exercise','') vals['chapter'] = vals.get('chapter','') vals['answer'] = vals.get('answer','') vals['id'] = vals.get('id',idx) yield idx, vals if self.config.name == 'paper-exampaper': examples = json.loads(io.open(data_file, 'r').read()) for idx in range(len(examples)): vals = examples[idx] vals['answer'] = vals.get('answer','') vals['source'] = vals.get('source','') vals['id'] = vals.get('id',idx) yield idx, vals if self.config.name == 'qa': examples = json.loads(io.open(data_file, 'r').read()) for idx in range(len(examples)): vals = examples[idx] vals['id'] = vals.get('id',idx) yield idx, vals if __name__ == '__main__': from datasets import load_dataset dataset = load_dataset('CMB.py', 'main') # dataset = load_dataset('CMB.py', 'qa') print()