Delete loading script

exams.py

@@ -1,266 +0,0 @@
-# coding=utf-8
-# 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.
-"""EXAMS: a benchmark dataset for multilingual and cross-lingual question answering"""
-
-
-import json
-
-import datasets
-
-
-_CITATION = """\
-@article{hardalov2020exams,
-  title={EXAMS: A Multi-subject High School Examinations Dataset for Cross-lingual and Multilingual Question Answering},
-  author={Hardalov, Momchil and Mihaylov, Todor and Dimitrina Zlatkova and Yoan Dinkov and Ivan Koychev and Preslav Nvakov},
-  journal={arXiv preprint arXiv:2011.03080},
-  year={2020}
-}
-"""
-
-_DESCRIPTION = """\
-EXAMS is a benchmark dataset for multilingual and cross-lingual question answering from high school examinations.
-It consists of more than 24,000 high-quality high school exam questions in 16 languages,
-covering 8 language families and 24 school subjects from Natural Sciences and Social Sciences, among others.
-"""
-
-_HOMEPAGE = "https://github.com/mhardalov/exams-qa"
-
-_LICENSE = "CC-BY-SA-4.0"
-
-_URLS_LIST = [
-    ("alignments", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/parallel_questions.jsonl"),
-]
-_URLS_LIST += [
-    (
-        "multilingual_train",
-        "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/train.jsonl.tar.gz",
-    ),
-    ("multilingual_dev", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/dev.jsonl.tar.gz"),
-    ("multilingual_test", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/test.jsonl.tar.gz"),
-    (
-        "multilingual_with_para_train",
-        "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/train_with_para.jsonl.tar.gz",
-    ),
-    (
-        "multilingual_with_para_dev",
-        "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/dev_with_para.jsonl.tar.gz",
-    ),
-    (
-        "multilingual_with_para_test",
-        "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/test_with_para.jsonl.tar.gz",
-    ),
-]
-
-_CROSS_LANGUAGES = ["bg", "hr", "hu", "it", "mk", "pl", "pt", "sq", "sr", "tr", "vi"]
-_URLS_LIST += [
-    ("crosslingual_test", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/test.jsonl.tar.gz"),
-    (
-        "crosslingual_with_para_test",
-        "https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/test_with_para.jsonl.tar.gz",
-    ),
-]
-for ln in _CROSS_LANGUAGES:
-    _URLS_LIST += [
-        (
-            f"crosslingual_{ln}_train",
-            f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/train_{ln}.jsonl.tar.gz",
-        ),
-        (
-            f"crosslingual_with_para_{ln}_train",
-            f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/train_{ln}_with_para.jsonl.tar.gz",
-        ),
-        (
-            f"crosslingual_{ln}_dev",
-            f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/dev_{ln}.jsonl.tar.gz",
-        ),
-        (
-            f"crosslingual_with_para_{ln}_dev",
-            f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/dev_{ln}_with_para.jsonl.tar.gz",
-        ),
-    ]
-_URLs = dict(_URLS_LIST)
-
-
-class ExamsConfig(datasets.BuilderConfig):
-    def __init__(self, lang, with_para, **kwargs):
-        super(ExamsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-        self.lang = lang
-        self.with_para = "_with_para" if with_para else ""
-
-
-class Exams(datasets.GeneratorBasedBuilder):
-    """Exams dataset"""
-
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIG_CLASS = ExamsConfig
-    BUILDER_CONFIGS = [
-        ExamsConfig(
-            lang="",
-            with_para=False,
-            name="alignments",
-            description="loads the alignment between question IDs across languages",
-        ),
-        ExamsConfig(
-            lang="all",
-            with_para=False,
-            name="multilingual",
-            description="Loads the unified multilingual train/dev/test split",
-        ),
-        ExamsConfig(
-            lang="all",
-            with_para=True,
-            name="multilingual_with_para",
-            description="Loads the unified multilingual train/dev/test split with Wikipedia support paragraphs",
-        ),
-        ExamsConfig(
-            lang="all", with_para=False, name="crosslingual_test", description="Loads crosslingual test set only"
-        ),
-        ExamsConfig(
-            lang="all",
-            with_para=True,
-            name="crosslingual_with_para_test",
-            description="Loads crosslingual test set only with Wikipedia support paragraphs",
-        ),
-    ]
-    for ln in _CROSS_LANGUAGES:
-        BUILDER_CONFIGS += [
-            ExamsConfig(
-                lang=ln,
-                with_para=False,
-                name=f"crosslingual_{ln}",
-                description=f"Loads crosslingual train and dev set for {ln}",
-            ),
-            ExamsConfig(
-                lang=ln,
-                with_para=True,
-                name=f"crosslingual_with_para_{ln}",
-                description=f"Loads crosslingual train and dev set for {ln} with Wikipedia support paragraphs",
-            ),
-        ]
-
-    DEFAULT_CONFIG_NAME = (
-        "multilingual_with_para"  # It's not mandatory to have a default configuration. Just use one if it make sense.
-    )
-
-    def _info(self):
-        if self.config.name == "alignments":  # This is the name of the configuration selected in BUILDER_CONFIGS above
-            features = datasets.Features(
-                {
-                    "source_id": datasets.Value("string"),
-                    "target_id_list": datasets.Sequence(datasets.Value("string")),
-                }
-            )
-        else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
-            features = datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "question": {
-                        "stem": datasets.Value("string"),
-                        "choices": datasets.Sequence(
-                            {
-                                "text": datasets.Value("string"),
-                                "label": datasets.Value("string"),
-                                "para": datasets.Value("string"),
-                            }
-                        ),
-                    },
-                    "answerKey": datasets.Value("string"),
-                    "info": {
-                        "grade": datasets.Value("int32"),
-                        "subject": datasets.Value("string"),
-                        "language": datasets.Value("string"),
-                    },
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,  # Here we define them above because they are different between the two configurations
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        archives = dl_manager.download(_URLs)
-        if self.config.name == "alignments":
-            return [
-                datasets.SplitGenerator(
-                    name="full",
-                    gen_kwargs={"filepath": archives["alignments"]},
-                ),
-            ]
-        elif self.config.name in ["multilingual", "multilingual_with_para"]:
-            return [
-                datasets.SplitGenerator(
-                    name=spl_enum,
-                    gen_kwargs={
-                        "filepath": f"{spl}{self.config.with_para}.jsonl",
-                        "files": dl_manager.iter_archive(archives[f"{self.config.name}_{spl}"]),
-                    },
-                )
-                for spl, spl_enum in [
-                    ("train", datasets.Split.TRAIN),
-                    ("dev", datasets.Split.VALIDATION),
-                    ("test", datasets.Split.TEST),
-                ]
-            ]
-        elif self.config.name in ["crosslingual_test", "crosslingual_with_para_test"]:
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    gen_kwargs={
-                        "filepath": f"test{self.config.with_para}.jsonl",
-                        "files": dl_manager.iter_archive(archives[self.config.name]),
-                    },
-                ),
-            ]
-        else:
-            return [
-                datasets.SplitGenerator(
-                    name=spl_enum,
-                    gen_kwargs={
-                        "filepath": f"{spl}_{self.config.lang}{self.config.with_para}.jsonl",
-                        "files": dl_manager.iter_archive(archives[f"{self.config.name}_{spl}"]),
-                    },
-                )
-                for spl, spl_enum in [
-                    ("train", datasets.Split.TRAIN),
-                    ("dev", datasets.Split.VALIDATION),
-                ]
-            ]
-
-    def _generate_examples(self, filepath, files=None):
-        if self.config.name == "alignments":
-            with open(filepath, encoding="utf-8") as f:
-                for id_, line in enumerate(f):
-                    line_dict = json.loads(line.strip())
-                    in_id, out_list = list(line_dict.items())[0]
-                    yield id_, {"source_id": in_id, "target_id_list": out_list}
-        else:
-            for path, f in files:
-                if path == filepath:
-                    for id_, line in enumerate(f):
-                        line_dict = json.loads(line.strip())
-                        for choice in line_dict["question"]["choices"]:
-                            choice["para"] = choice.get("para", "")
-                        yield id_, {
-                            "id": line_dict["id"],
-                            "question": line_dict["question"],
-                            "answerKey": line_dict["answerKey"],
-                            "info": line_dict["info"],
-                        }
-                    break