quati.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
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# Lint as: python3
"""Quati dataset."""

import datasets


_CITATION = """
place holder
"""

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

_DESCRIPTION = """
Quati ― Portuguese Native Information Retrieval dataset.
"""



QUATI_10M_DATASET_PARTS=["part_00", "part_01", "part_02", "part_03", "part_04"]



_URLS = {
    "quati_1M_passages": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_1M.tsv",
    "quati_10M_passages_part_00": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_00.tsv",
    "quati_10M_passages_part_01": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_01.tsv",
    "quati_10M_passages_part_02": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_02.tsv",
    "quati_10M_passages_part_03": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_03.tsv",
    "quati_10M_passages_part_04": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_04.tsv",
    "quati_1M_qrels": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/qrels/quati_1M_qrels.txt",
    "quati_10M_qrels": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/qrels/quati_10M_qrels.txt",
    "quati_test_topics": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/topics/quati_test_topics.tsv",
    "quati_all_topics": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/topics/quati_all_topics.tsv"
}



def generate_examples_passages(filepath):

    with open(filepath, encoding="utf-8") as input_file:
        for (idx, line) in enumerate(input_file):
            
            passage_id, passage = line.rstrip().split("\t")
            
            features = {"passage_id": passage_id,
                        "passage": passage}

            yield idx, features



def generate_examples_qrels(filepath):

    with open(filepath, encoding="utf-8") as input_file:
        for (idx, line) in enumerate(input_file):
            if idx > 0:
                query_id, _, passage_id, score = line.rstrip().split(" ")

                features = {"query_id": int(query_id),
                            "passage_id": passage_id,
                            "score": int(score)}

                yield idx - 1, features


def generate_examples_topics(filepath):

    with open(filepath, encoding="utf-8") as input_file:
        for (idx, line) in enumerate(input_file):
            query_id, query = line.rstrip().split("\t")

            features = {"query_id": int(query_id),
                        "query": query}

            yield idx, features



class Quati(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIGS = (
        [
            datasets.BuilderConfig(
                name="quati_10M_passages",
                description="Portugues Brazilian passages, composing the complete Quati 10M dataset.",
                version=datasets.Version("1.0.0"),
            ),

            datasets.BuilderConfig(
                name="quati_1M_passages",
                description="Portugues Brazilian passages, composing the Quati 1M dataset.",
                version=datasets.Version("1.0.0"),
            ),

            datasets.BuilderConfig(
                name="quati_10M_qrels",
                description="Qrels for the annotated passages from the Quati 10M dataset.",
                version=datasets.Version("1.0.0"),
            ),

            datasets.BuilderConfig(
                name="quati_1M_qrels",
                description="Qrels for the annotated passages from the Quati 1M dataset.",
                version=datasets.Version("1.0.0"),
            ),

            datasets.BuilderConfig(
                name="quati_test_topics",
                description="50 test topics, corresponding to Quati dataset qrels.",
                version=datasets.Version("1.0.0"),
            ),

            datasets.BuilderConfig(
                name="quati_all_topics",
                description="All 200 topics created for the Quati dataset, including the 50 ones corresponding to Quati dataset qrels.",
                version=datasets.Version("1.0.0"),
            )
        ]
        + [
            datasets.BuilderConfig(
                name="quati_10M_passages_{}".format(which_part),
                description="Portugues Brazilian passages, composing the Quati 10M dataset {}.".format(which_part),
                version=datasets.Version("1.0.0"),
            )
            for which_part in QUATI_10M_DATASET_PARTS
        ]
    )

    DEFAULT_CONFIG_NAME = "quati_1M_passages"


    def _info(self):
        name = self.config.name
        if "passages" in name:
            features = {
                "passage_id": datasets.Value("string"),
                "passage": datasets.Value("string"),
            }
        elif name.endswith("qrels"):
            features = {
                "query_id": datasets.Value("int32"),
                "passage_id": datasets.Value("string"),
                "score": datasets.Value("int32"),
            }
        else:
            features = {
                "query_id": datasets.Value("int32"),
                "query": 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 == "quati_10M_passages":

            urls = {which_part: _URLS["quati_10M_passages_{}".format(which_part)] for which_part in QUATI_10M_DATASET_PARTS}

            dl_path = dl_manager.download_and_extract(urls)

            return [datasets.SplitGenerator(name="quati_10M_passages_{}".format(which_part), gen_kwargs={"filepath": dl_path[which_part]}) for which_part in QUATI_10M_DATASET_PARTS]

        else:
            url = _URLS[self.config.name]
            dl_path = dl_manager.download_and_extract(url)

            return (datasets.SplitGenerator(name=self.config.name, gen_kwargs={"filepath": dl_path}),)


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

        if "passages" in self.config.name:
            return generate_examples_passages(filepath)
        
        if self.config.name.endswith("qrels"):
            return generate_examples_qrels(filepath)
        
        else:
            return generate_examples_topics(filepath)