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mrobust / mrobust.py

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	# 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
	"""mrobust dataset."""

	import datasets


	# _CITATION = """
	# @misc{bonifacio2021mmarco,
	# title={mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset},
	# author={Luiz Henrique Bonifacio and Israel Campiotti and Vitor Jeronymo and Hugo Queiroz Abonizio and Roberto Lotufo and Rodrigo Nogueira},
	# year={2021},
	# eprint={2108.13897},
	# archivePrefix={arXiv},
	# primaryClass={cs.CL}
	# }
	# """

	# _URL = "https://github.com/unicamp-dl/mMARCO"

	_DESCRIPTION = """
	Robust04 translated datasets
	"""

	def generate_examples_tuples(filepath):
	with open(filepath, encoding="utf-8") as f:
	for (idx, line) in enumerate(f):
	idx, text = line.rstrip().split("\t")
	features = {
	"id": idx,
	"text": text,
	}
	yield idx, features

	_BASE_URLS = {
	"collections": "https://huggingface.co/datasets/unicamp-dl/mrobust/resolve/main/data/collections/",
	"queries": "https://huggingface.co/datasets/unicamp-dl/mrobust/resolve/main/data/queries/",
	}

	LANGUAGES = [
	"chinese",
	"dutch",
	"english",
	"french",
	"german",
	"indonesian",
	"italian",
	"portuguese",
	"russian",
	"spanish",
	"vietnamese",
	]


	class MRobust(datasets.GeneratorBasedBuilder):

	BUILDER_CONFIGS = (
	[
	datasets.BuilderConfig(
	name=f"collection-{language}",
	description=f"{language.capitalize()} collection",
	version=datasets.Version("1.0.0"),
	)
	for language in LANGUAGES
	]
	+ [
	datasets.BuilderConfig(
	name=f"queries-{language}",
	description=f"{language.capitalize()} queries",
	version=datasets.Version("1.0.0"),
	)
	for language in LANGUAGES
	]
	)

	DEFAULT_CONFIG_NAME = "english"

	def _info(self):
	name = self.config.name
	if name.startswith("collection") or name.startswith("queries"):
	features = {
	"id": datasets.Value("string"),
	"text": datasets.Value("string"),
	}

	return datasets.DatasetInfo(
	description=f"{_DESCRIPTION}\n{self.config.description}",
	features=datasets.Features(features),
	supervised_keys=None,
	# homepage=_URL,
	# citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""

	if self.config.name.startswith("collection"):
	url = _BASE_URLS["collections"] + self.config.name[11:] + "_collection.tsv"
	dl_path = dl_manager.download_and_extract(url)
	return (datasets.SplitGenerator(name="collection", gen_kwargs={"filepath": dl_path}),)
	elif self.config.name.startswith("queries"):
	url = _BASE_URLS["queries"] + self.config.name[8:] + "_queries.tsv"
	dl_path = dl_manager.download_and_extract(url)
	return (datasets.SplitGenerator(name="queries", gen_kwargs={"filepath": dl_path}),)

	def _generate_examples(self, filepath, args=None):
	"""Yields examples."""

	if self.config.name.startswith("collection") or self.config.name.startswith("queries"):
	return generate_examples_tuples(filepath)