Upload 2 files
Browse files- CMB-datasets.zip +2 -2
- CMB.py +269 -0
CMB-datasets.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:4ea94b865030f847fc56b5e81f240b9ed7135de904af9b66bc867b85813b2f58
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size 36507969
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CMB.py
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@@ -0,0 +1,269 @@
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# coding=utf-8
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# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Lint as: python3
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"""The General Language Understanding Evaluation (GLUE) benchmark."""
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import csv
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import os
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import sys
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import json
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import io
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import textwrap
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import numpy as np
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import datasets
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_CMB_CITATION = """\
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coming soon~
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"""
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_CMB_DESCRIPTION = """\
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coming soon~
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"""
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_DATASETS_FILE = "CMB-datasets.zip"
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class CMBConfig(datasets.BuilderConfig):
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"""BuilderConfig for GLUE."""
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def __init__(
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self,
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features,
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data_url,
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data_dir,
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citation,
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url,
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**kwargs,
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):
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super(CMBConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
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self.features = features
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self.data_url = data_url
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self.data_dir = data_dir
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self.citation = citation
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self.url = url
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class CMB(datasets.GeneratorBasedBuilder):
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"""The General Language Understanding Evaluation (GLUE) benchmark."""
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BUILDER_CONFIGS = [
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CMBConfig(
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name="main",
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description=textwrap.dedent(
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"""\
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ไธป่ฆๆฐๆฎ้๏ผๅ
ๅซ train val test ไธไธช็ปๆ้จๅ."""
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),
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features=datasets.Features(
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{
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"id": datasets.Value("string"),
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"exam_type": datasets.Value("string"),
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"exam_class": datasets.Value("string"),
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"chapter": datasets.Value("string"),
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"exam_subject": datasets.Value("string"),
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"exercise": datasets.Value("string"),
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"question": datasets.Value("string"),
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"question_type": datasets.Value("string"),
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"option": datasets.Value("string"),
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"answer": datasets.Value("string"),
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"explanation": datasets.Value("string")
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}
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),
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data_url=_DATASETS_FILE,
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data_dir="CMB-main",
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citation=textwrap.dedent(
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"""\
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}"""
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),
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url="https://github.com/FreedomIntelligence/CMB",
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),
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CMBConfig(
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name="paper-exampaper",
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description=textwrap.dedent(
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"""\
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ๅๅฒ็้ข
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."""
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),
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features=datasets.Features(
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{
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"id": datasets.Value("string"),
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"source": datasets.Value("string"),
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"exam_type": datasets.Value("string"),
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"exam_class": datasets.Value("string"),
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"exam_subject": datasets.Value("string"),
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"question": datasets.Value("string"),
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"question_type": datasets.Value("string"),
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"option": datasets.Value("string"),
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"answer": datasets.Value("string")
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}
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),
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data_url=_DATASETS_FILE,
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data_dir="CMB-test-exampaper",
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citation=textwrap.dedent(
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"""\
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}"""
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),
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url="https://github.com/FreedomIntelligence/CMB",
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),
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CMBConfig(
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name="qa",
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description=textwrap.dedent(
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"""\
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QA ๆ ผๅผ็่้ข
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"""
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),
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features=datasets.Features(
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{
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"id": datasets.Value("string"),
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"title": datasets.Value("string"),
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"description": datasets.Value("string"),
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"QA_pairs": datasets.Value("string")
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}
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),
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data_url=_DATASETS_FILE,
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data_dir="CMB-test-qa",
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citation=textwrap.dedent(
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"""\
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}"""
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),
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url="https://github.com/FreedomIntelligence/CMB",
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),
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_CMB_DESCRIPTION,
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features=self.config.features,
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homepage=self.config.url,
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citation=self.config.citation + "\n" + _CMB_CITATION,
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)
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def _split_generators(self, dl_manager):
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if self.config.name == "main":
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data_file = dl_manager.extract(self.config.data_url)
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main_data_dir = os.path.join(data_file, self.config.data_dir)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"data_file": os.path.join(main_data_dir, 'CMB-train', 'CMB-train-merge.json'),
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"split": "train",
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},
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)
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,
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"data_file": os.path.join(main_data_dir, 'CMB-val', 'CMB-val-merge.json'),
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"split": "val",
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},
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)
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,
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"data_file": os.path.join(main_data_dir, 'CMB-test', 'CMB-test-choice-question-merge.json'),
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"split": "test",
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},
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)
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]
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if self.config.name == "paper-exampaper":
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data_file = dl_manager.extract(self.config.data_url)
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main_data_dir = os.path.join(data_file, self.config.data_dir)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"data_file": os.path.join(main_data_dir, 'CMB-test-zhenti-merge.json'),
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"split": "test",
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},
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)
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]
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if self.config.name == "qa":
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data_file = dl_manager.extract(self.config.data_url)
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main_data_dir = os.path.join(data_file, self.config.data_dir)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"data_file": os.path.join(main_data_dir, 'CMB-test-qa.json'),
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"split": "test",
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},
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)
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]
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def _generate_examples(self, data_file, split, mrpc_files=None):
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if self.config.name == 'main':
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examples = json.loads(io.open(data_file, 'r').read())
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for idx in range(len(examples)):
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vals = examples[idx]
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vals['explanation'] = vals.get('explanation','')
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vals['exercise'] = vals.get('exercise','')
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vals['chapter'] = vals.get('chapter','')
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vals['answer'] = vals.get('answer','')
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vals['id'] = vals.get('id',idx)
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yield idx, vals
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if self.config.name == 'paper-exampaper':
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examples = json.loads(io.open(data_file, 'r').read())
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for idx in range(len(examples)):
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vals = examples[idx]
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vals['answer'] = vals.get('answer','')
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vals['source'] = vals.get('source','')
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vals['id'] = vals.get('id',idx)
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yield idx, vals
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if self.config.name == 'qa':
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examples = json.loads(io.open(data_file, 'r').read())
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for idx in range(len(examples)):
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vals = examples[idx]
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vals['id'] = vals.get('id',idx)
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yield idx, vals
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if __name__ == '__main__':
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from datasets import load_dataset
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dataset = load_dataset('CMB.py', 'main')
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# dataset = load_dataset('CMB.py', 'qa')
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print()
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