# 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 """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)