mmarco.py

# 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
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# Lint as: python3
"""mMARCO dataset."""

from collections import defaultdict
from gc import collect
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 = """
mMARCO translated datasets
"""


_BASE_URLS = {
    "collections": "https://huggingface.co/datasets/unicamp-dl/mmarco/resolve/main/data/google/collections/",
    "queries-train": "https://huggingface.co/datasets/unicamp-dl/mmarco/resolve/main/data/google/queries/train/",
    "queries-dev": "https://huggingface.co/datasets/unicamp-dl/mmarco/resolve/main/data/google/queries/dev/",
    "runs": "https://huggingface.co/datasets/unicamp-dl/mmarco/resolve/main/data/google/runs/",
    "train": "https://huggingface.co/datasets/unicamp-dl/mmarco/resolve/main/data/triples.train.ids.small.tsv",
}

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


class MMarcoDev(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIGS = (
        [
            datasets.BuilderConfig(
                name=language,
                description=f"{language.capitalize()} dev queries",
                version=datasets.Version("2.0.0"),
            )
            for language in LANGUAGES
        ]
    )
    

    DEFAULT_CONFIG_NAME = "english"

    def _info(self):
        name = self.config.name
        assert name in LANGUAGES, f"Does not support languge {name}. Must be one of {LANGUAGES}."

        features = {
            "query_id": datasets.Value("string"),
            "query": datasets.Value("string"),
            "positive_passages": [
                {'docid': datasets.Value('string'), 'text': datasets.Value('string')}
            ],
            "negative_passages": [
                {'docid': 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."""
        languages = [self.config.name] if self.config.name in LANGUAGES else LANGUAGES
        urls = {
            # "collection": {lang: _BASE_URLS["collections"] + lang + "_collection.tsv" for lang in languages},
            "queries": {lang: _BASE_URLS["queries-dev"] + lang + "_queries.dev.small.tsv" for lang in languages},
        }
        dl_path = dl_manager.download_and_extract(urls)

        return [
            datasets.SplitGenerator(
                name="dev",
                gen_kwargs={
                    "args": {
                        "queries": dl_path["queries"],
                    },
                },
            )
        ]

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

        lang = self.config.name
        assert lang in LANGUAGES

        # loading
        queries_path = args["queries"][lang]
        with open(queries_path, encoding="utf-8") as f:
            for line in f:
                query_id, query = line.rstrip().split("\t")
                features = {
                    "query_id": query_id,
                    "query": query,
                    "positive_passages": [],
                    "negative_passages": [],
                }
                yield f"{lang}-{query_id}", features