# coding=utf-8 # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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. """PAUQ: Text-to-SQL in Russian""" import json import os import datasets logger = datasets.logging.get_logger(__name__) _CITATION = """\ @inproceedings{bakshandaeva-etal-2022-pauq, title = "{PAUQ}: Text-to-{SQL} in {R}ussian", author = "Bakshandaeva, Daria and Somov, Oleg and Dmitrieva, Ekaterina and Davydova, Vera and Tutubalina, Elena", booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022", month = dec, year = "2022", address = "Abu Dhabi, United Arab Emirates", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.findings-emnlp.175", """ _DESCRIPTION = """\ Pauq is a first Russian text-to-SQL dataset translated from original Spider dataset with corrections and refinements of question, queries and databases. """ _LICENSE = "CC BY-SA 4.0" _HOMEPAGE = "https://github.com/ai-spiderweb/pauq" _URL = "https://huggingface.co/datasets/composite/pauq/resolve/main/formatted_pauq.zip" RUSSIAN_PAUQ_TL_DESCRIPTION = "Russian PAUQ train/test split based on target length of SQL query. Long queries in train, short queries in test." ENGLISH_PAUQ_TL_DESCRIPTION = "English PAUQ train/test split based on target length of SQL query. Long queries in train, short queries in test." RUSSIAN_PAUQ_IID_DESCRIPTION = "Independent and identical Russian PAUQ train/test split. Сorresponds to original Spider splitting." ENGLISH_PAUQ_IID_DESCRIPTION = "Independent and identical English PAUQ train/test split. Сorresponds to original Spider splitting." class Pauq(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("1.0.0") BUILDER_CONFIGS = [ datasets.BuilderConfig( name="ru_pauq_tl", version=VERSION, description=RUSSIAN_PAUQ_TL_DESCRIPTION, ), datasets.BuilderConfig( name="en_pauq_tl", version=VERSION, description=ENGLISH_PAUQ_TL_DESCRIPTION, ), datasets.BuilderConfig( name="ru_pauq_iid", version=VERSION, description=RUSSIAN_PAUQ_IID_DESCRIPTION, ), datasets.BuilderConfig( name="en_pauq_iid", version=VERSION, description=ENGLISH_PAUQ_IID_DESCRIPTION, ), ] def _info(self): features = datasets.Features( { "id": datasets.Value("string"), "db_id": datasets.Value("string"), "source": datasets.Value("string"), "type": datasets.Value("string"), "question": datasets.Value("string"), "query": datasets.Value("string"), "sql": datasets.features.Sequence(datasets.Value("string")), "question_toks": datasets.features.Sequence(datasets.Value("string")), "query_toks": datasets.features.Sequence(datasets.Value("string")), "query_toks_no_value": datasets.features.Sequence(datasets.Value("string")), "masked_query": datasets.Value("string") } ) dataset_info = None if self.config.name == 'ru_pauq_tl': dataset_info = datasets.DatasetInfo( description=RUSSIAN_PAUQ_TL_DESCRIPTION, features=features, supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, config_name="ru_pauq_tl") elif self.config.name == "en_pauq_tl": dataset_info = datasets.DatasetInfo( description=ENGLISH_PAUQ_TL_DESCRIPTION, features=features, supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, config_name="en_pauq_tl") elif self.config.name == 'ru_pauq_iid': dataset_info = datasets.DatasetInfo( description=RUSSIAN_PAUQ_IID_DESCRIPTION, features=features, supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, config_name="ru_pauq_iid") elif self.config.name == 'en_pauq_iid': dataset_info = datasets.DatasetInfo( description=ENGLISH_PAUQ_IID_DESCRIPTION, features=features, supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, config_name="en_pauq_iid") return dataset_info def _split_generators(self, dl_manager): downloaded_filepath = dl_manager.download_and_extract(_URL) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_iid_train.json"), }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_iid_test.json"), }, ), datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_tl_train.json"), }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_tl_test.json"), }, ), datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_iid_train.json"), }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_iid_test.json"), }, ), datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_tl_train.json"), }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_tl_test.json"), }, ), ] def _generate_examples(self, data_filepath): """This function returns the examples in the raw (text) form.""" logger.info("generating examples from = %s", data_filepath) with open(data_filepath, encoding="utf-8") as f: pauq = json.load(f) for idx, sample in enumerate(pauq): yield idx, { "id": sample["id"], "db_id": sample["db_id"], "source": sample["source"], "type": sample["type"], "query": sample["query"], "sql": datasets.Value("string"), "question": sample["question"], "question_toks": sample["question_toks"], "query_toks": sample["query_toks"], "query_toks_no_values": sample["query_toks_no_values"], "masked_query": sample["masked_query"] }