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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) |