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- # coding=utf-8
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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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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- """EXAMS: a benchmark dataset for multilingual and cross-lingual question answering"""
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-
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-
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- import json
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-
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- import datasets
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-
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-
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- _CITATION = """\
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- @article{hardalov2020exams,
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- title={EXAMS: A Multi-subject High School Examinations Dataset for Cross-lingual and Multilingual Question Answering},
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- author={Hardalov, Momchil and Mihaylov, Todor and Dimitrina Zlatkova and Yoan Dinkov and Ivan Koychev and Preslav Nvakov},
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- journal={arXiv preprint arXiv:2011.03080},
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- year={2020}
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- }
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- """
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-
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- _DESCRIPTION = """\
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- EXAMS is a benchmark dataset for multilingual and cross-lingual question answering from high school examinations.
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- It consists of more than 24,000 high-quality high school exam questions in 16 languages,
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- covering 8 language families and 24 school subjects from Natural Sciences and Social Sciences, among others.
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- """
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-
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- _HOMEPAGE = "https://github.com/mhardalov/exams-qa"
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-
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- _LICENSE = "CC-BY-SA-4.0"
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-
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- _URLS_LIST = [
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- ("alignments", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/parallel_questions.jsonl"),
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- ]
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- _URLS_LIST += [
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- (
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- "multilingual_train",
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- "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/train.jsonl.tar.gz",
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- ),
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- ("multilingual_dev", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/dev.jsonl.tar.gz"),
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- ("multilingual_test", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/test.jsonl.tar.gz"),
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- (
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- "multilingual_with_para_train",
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- "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/train_with_para.jsonl.tar.gz",
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- ),
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- (
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- "multilingual_with_para_dev",
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- "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/dev_with_para.jsonl.tar.gz",
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- ),
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- (
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- "multilingual_with_para_test",
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- "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/test_with_para.jsonl.tar.gz",
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- ),
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- ]
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-
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- _CROSS_LANGUAGES = ["bg", "hr", "hu", "it", "mk", "pl", "pt", "sq", "sr", "tr", "vi"]
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- _URLS_LIST += [
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- ("crosslingual_test", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/test.jsonl.tar.gz"),
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- (
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- "crosslingual_with_para_test",
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- "https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/test_with_para.jsonl.tar.gz",
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- ),
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- ]
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- for ln in _CROSS_LANGUAGES:
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- _URLS_LIST += [
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- (
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- f"crosslingual_{ln}_train",
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- f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/train_{ln}.jsonl.tar.gz",
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- ),
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- (
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- f"crosslingual_with_para_{ln}_train",
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- f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/train_{ln}_with_para.jsonl.tar.gz",
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- ),
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- (
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- f"crosslingual_{ln}_dev",
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- f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/dev_{ln}.jsonl.tar.gz",
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- ),
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- (
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- f"crosslingual_with_para_{ln}_dev",
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- f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/dev_{ln}_with_para.jsonl.tar.gz",
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- ),
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- ]
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- _URLs = dict(_URLS_LIST)
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-
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-
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- class ExamsConfig(datasets.BuilderConfig):
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- def __init__(self, lang, with_para, **kwargs):
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- super(ExamsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
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- self.lang = lang
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- self.with_para = "_with_para" if with_para else ""
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-
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-
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- class Exams(datasets.GeneratorBasedBuilder):
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- """Exams dataset"""
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-
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- VERSION = datasets.Version("1.0.0")
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- BUILDER_CONFIG_CLASS = ExamsConfig
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- BUILDER_CONFIGS = [
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- ExamsConfig(
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- lang="",
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- with_para=False,
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- name="alignments",
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- description="loads the alignment between question IDs across languages",
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- ),
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- ExamsConfig(
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- lang="all",
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- with_para=False,
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- name="multilingual",
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- description="Loads the unified multilingual train/dev/test split",
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- ),
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- ExamsConfig(
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- lang="all",
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- with_para=True,
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- name="multilingual_with_para",
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- description="Loads the unified multilingual train/dev/test split with Wikipedia support paragraphs",
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- ),
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- ExamsConfig(
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- lang="all", with_para=False, name="crosslingual_test", description="Loads crosslingual test set only"
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- ),
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- ExamsConfig(
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- lang="all",
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- with_para=True,
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- name="crosslingual_with_para_test",
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- description="Loads crosslingual test set only with Wikipedia support paragraphs",
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- ),
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- ]
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- for ln in _CROSS_LANGUAGES:
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- BUILDER_CONFIGS += [
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- ExamsConfig(
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- lang=ln,
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- with_para=False,
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- name=f"crosslingual_{ln}",
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- description=f"Loads crosslingual train and dev set for {ln}",
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- ),
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- ExamsConfig(
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- lang=ln,
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- with_para=True,
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- name=f"crosslingual_with_para_{ln}",
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- description=f"Loads crosslingual train and dev set for {ln} with Wikipedia support paragraphs",
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- ),
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- ]
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-
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- DEFAULT_CONFIG_NAME = (
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- "multilingual_with_para" # It's not mandatory to have a default configuration. Just use one if it make sense.
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- )
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-
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- def _info(self):
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- if self.config.name == "alignments": # This is the name of the configuration selected in BUILDER_CONFIGS above
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- features = datasets.Features(
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- {
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- "source_id": datasets.Value("string"),
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- "target_id_list": datasets.Sequence(datasets.Value("string")),
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- }
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- )
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- else: # This is an example to show how to have different features for "first_domain" and "second_domain"
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- features = datasets.Features(
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- {
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- "id": datasets.Value("string"),
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- "question": {
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- "stem": datasets.Value("string"),
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- "choices": datasets.Sequence(
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- {
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- "text": datasets.Value("string"),
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- "label": datasets.Value("string"),
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- "para": datasets.Value("string"),
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- }
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- ),
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- },
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- "answerKey": datasets.Value("string"),
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- "info": {
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- "grade": datasets.Value("int32"),
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- "subject": datasets.Value("string"),
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- "language": datasets.Value("string"),
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- },
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- }
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- )
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=features, # Here we define them above because they are different between the two configurations
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- supervised_keys=None,
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- homepage=_HOMEPAGE,
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- license=_LICENSE,
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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- archives = dl_manager.download(_URLs)
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- if self.config.name == "alignments":
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- return [
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- datasets.SplitGenerator(
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- name="full",
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- gen_kwargs={"filepath": archives["alignments"]},
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- ),
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- ]
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- elif self.config.name in ["multilingual", "multilingual_with_para"]:
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- return [
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- datasets.SplitGenerator(
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- name=spl_enum,
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- gen_kwargs={
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- "filepath": f"{spl}{self.config.with_para}.jsonl",
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- "files": dl_manager.iter_archive(archives[f"{self.config.name}_{spl}"]),
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- },
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- )
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- for spl, spl_enum in [
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- ("train", datasets.Split.TRAIN),
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- ("dev", datasets.Split.VALIDATION),
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- ("test", datasets.Split.TEST),
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- ]
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- ]
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- elif self.config.name in ["crosslingual_test", "crosslingual_with_para_test"]:
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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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- "filepath": f"test{self.config.with_para}.jsonl",
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- "files": dl_manager.iter_archive(archives[self.config.name]),
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- },
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- ),
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- ]
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- else:
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- return [
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- datasets.SplitGenerator(
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- name=spl_enum,
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- gen_kwargs={
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- "filepath": f"{spl}_{self.config.lang}{self.config.with_para}.jsonl",
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- "files": dl_manager.iter_archive(archives[f"{self.config.name}_{spl}"]),
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- },
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- )
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- for spl, spl_enum in [
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- ("train", datasets.Split.TRAIN),
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- ("dev", datasets.Split.VALIDATION),
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- ]
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- ]
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-
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- def _generate_examples(self, filepath, files=None):
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- if self.config.name == "alignments":
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- with open(filepath, encoding="utf-8") as f:
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- for id_, line in enumerate(f):
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- line_dict = json.loads(line.strip())
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- in_id, out_list = list(line_dict.items())[0]
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- yield id_, {"source_id": in_id, "target_id_list": out_list}
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- else:
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- for path, f in files:
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- if path == filepath:
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- for id_, line in enumerate(f):
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- line_dict = json.loads(line.strip())
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- for choice in line_dict["question"]["choices"]:
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- choice["para"] = choice.get("para", "")
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- yield id_, {
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- "id": line_dict["id"],
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- "question": line_dict["question"],
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- "answerKey": line_dict["answerKey"],
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- "info": line_dict["info"],
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- }
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- break