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Download mqa.py from clips/mqa: direct link, hf CLI and curl.
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https://huggingface.co/datasets/clips/mqa/resolve/main/mqa.py
- Command line
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hf download hf://datasets/clips/mqa/mqa.py
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curl -L -o mqa.py https://huggingface.co/datasets/clips/mqa/resolve/main/mqa.py
6.74 kB
| # coding=utf-8 | |
| # Copyright 2020 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 | |
| # ok | |
| import os | |
| import json | |
| import datasets | |
| _DESCRIPTION = """MQA is a multilingual corpus of questions and answers parsed from the Common Crawl. Questions are divided between Frequently Asked Questions (FAQ) pages and Community Question Answering (CQA) pages.""" | |
| _HOMEPAGE_URL = "https://huggingface.co/datasets/clips/mqa" | |
| _CITATION = """ | |
| @misc{debruyn2021mfaq, | |
| title={MFAQ: a Multilingual FAQ Dataset}, | |
| author={Maxime {De Bruyn} and Ehsan Lotfi and Jeska Buhmann and Walter Daelemans}, | |
| year={2021}, | |
| booktitle={MRQA@EMNLP2021}, | |
| } | |
| """ | |
| _VERSION = "0.1" | |
| _BASE_NAME = "" | |
| _BASE_URL = "data/data.{}.{}.json.gz" | |
| _LANGUAGES = [ | |
| "ca", "en", "de", "es", "fr", | |
| "ru", "ja", "it", "zh", "pt", | |
| "nl", "tr", "pl", "vi", "ar", | |
| "id", "uk", "ro", "no", "th", | |
| "sv", "el", "fi", "he", "da", | |
| "cs", "ko", "fa", "hi", "hu", | |
| "sk", "lt", "et", "hr", "is", | |
| "lv", "ms", "bg", "sr", | |
| ] | |
| _SCOPES = ["faq", "cqa"] | |
| _LEVELS = ["domain", "page", "question"] | |
| class MQAConfig(datasets.BuilderConfig): | |
| def __init__(self, *args, language="en", scope="all", level="question", **kwargs): | |
| super().__init__( | |
| *args, | |
| name=f"{language}-{scope}-{level}", | |
| **kwargs, | |
| ) | |
| self.language = language | |
| self.scope = scope | |
| self.level = level | |
| class MQA(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [] | |
| for language in _LANGUAGES: | |
| for scope in _SCOPES: | |
| for level in _LEVELS: | |
| BUILDER_CONFIGS.append(MQAConfig(language=language, scope=scope, level=level)) | |
| for language in _LANGUAGES: | |
| BUILDER_CONFIGS.append(MQAConfig(language=language, scope="all", level=level)) | |
| for scope in _SCOPES: | |
| BUILDER_CONFIGS.append(MQAConfig(language="all", scope=scope, level=level)) | |
| BUILDER_CONFIG_CLASS = MQAConfig | |
| def _info(self): | |
| question = { | |
| "id": datasets.Value("string"), | |
| "text": datasets.Value("string"), | |
| "name": datasets.Value("string"), | |
| "domain": datasets.Value("string"), | |
| "bucket": datasets.Value("string"), | |
| "answers": [{ | |
| "text": datasets.Value("string"), | |
| "name": datasets.Value("string"), | |
| "is_accepted": datasets.Value("bool"), | |
| }] | |
| } | |
| page = { | |
| "id": datasets.Value("string"), | |
| "bucket": datasets.Value("string"), | |
| "domain": datasets.Value("string"), | |
| # "description": datasets.Value("string"), | |
| # "title": datasets.Value("string"), | |
| "questions": [question] | |
| } | |
| domain = { | |
| "domain": datasets.Value("string"), | |
| "pages": [page] | |
| } | |
| if self.config.level == "question": | |
| features = question | |
| elif self.config.level == "page": | |
| features = page | |
| elif self.config.level == "domain": | |
| features = domain | |
| else: | |
| raise NotImplementedError() | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features(features), | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE_URL, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| filenames = [] | |
| languages = _LANGUAGES if self.config.language == "all" else [self.config.language] | |
| scopes = _SCOPES if self.config.scope == "all" else [self.config.scope] | |
| for language in languages: | |
| for scope in scopes: | |
| path = dl_manager.download_and_extract(_BASE_URL.format(language, scope)) | |
| filenames.append(path) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"filenames": filenames}, | |
| ) | |
| ] | |
| def _generate_examples(self, filenames): | |
| def default(e, key, default_value=""): | |
| if e[key] is None: | |
| return default_value | |
| return e[key] | |
| for filename in filenames: | |
| with open(filename, "r") as f: | |
| domain = [] | |
| previous_domain = '' | |
| for line in f: | |
| page = json.loads(line) | |
| questions = [{ | |
| "text": default(question, "text"), | |
| "name": default(question, "name"), | |
| "domain": page["domain"], | |
| "bucket": page["bucket"], | |
| "id": question["hash"], | |
| "answers": [{ | |
| "text": default(answer, "text"), | |
| "name": default(answer, "name"), | |
| "is_accepted": answer["is_accepted"] | |
| } for answer in question["answers"]] | |
| } for question in page["questions"]] | |
| page = { | |
| "id": page["page_hash"], | |
| "domain": page["domain"], | |
| "bucket": page["bucket"], | |
| # "title": default(page, "title"), | |
| # "description": default(page, "description"), | |
| "questions": questions | |
| } | |
| if self.config.level == "question": | |
| for question in questions: | |
| yield question["id"], question | |
| if self.config.level == "page": | |
| yield page["id"], page | |
| if self.config.level == "domain": | |
| if page["domain"] == previous_domain or previous_domain == "": | |
| domain.append(page) | |
| else: | |
| yield previous_domain, { | |
| "domain": previous_domain, | |
| "pages": domain | |
| } | |
| domain = [] | |
| previous_domain = page["domain"] |