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# 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_TRL_DESCRIPTION = "Russian PAUQ train/test split based on target length of SQL query. Long query template in train, short query template in test."
ENGLISH_PAUQ_TRL_DESCRIPTION = "English PAUQ train/test split based on target length of SQL query. Long query template in train, short query template in test."
RUSSIAN_PAUQ_TSL_DESCRIPTION = "Russian PAUQ train/test split based on target length of SQL query. Short query template in train, long query template in test."
ENGLISH_PAUQ_TSL_DESCRIPTION = "English PAUQ train/test split based on target length of SQL query. Short query template in train, long query template in test."
RUSSIAN_PAUQ_OS_DESCRIPTION = "Independent and identical Russian PAUQ train/test split. Сorresponds to original Spider splitting."
ENGLISH_PAUQ_OS_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_trl",
version=VERSION,
description=RUSSIAN_PAUQ_TRL_DESCRIPTION,
),
datasets.BuilderConfig(
name="en_trl",
version=VERSION,
description=ENGLISH_PAUQ_TRL_DESCRIPTION,
),
datasets.BuilderConfig(
name="ru_tsl",
version=VERSION,
description=RUSSIAN_PAUQ_TSL_DESCRIPTION,
),
datasets.BuilderConfig(
name="en_tsl",
version=VERSION,
description=ENGLISH_PAUQ_TSL_DESCRIPTION,
),
datasets.BuilderConfig(
name="ru_os",
version=VERSION,
description=RUSSIAN_PAUQ_OS_DESCRIPTION,
),
datasets.BuilderConfig(
name="en_os",
version=VERSION,
description=ENGLISH_PAUQ_OS_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_values": datasets.features.Sequence(datasets.Value("string")),
"template": datasets.Value("string")
}
)
dataset_info = None
if self.config.name == 'ru_trl':
dataset_info = datasets.DatasetInfo(
description=RUSSIAN_PAUQ_TRL_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
config_name="ru_trl")
elif self.config.name == "en_trl":
dataset_info = datasets.DatasetInfo(
description=ENGLISH_PAUQ_TRL_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
config_name="en_trl")
elif self.config.name == 'ru_os':
dataset_info = datasets.DatasetInfo(
description=RUSSIAN_PAUQ_OS_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
config_name="ru_os")
elif self.config.name == 'en_os':
dataset_info = datasets.DatasetInfo(
description=ENGLISH_PAUQ_OS_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
config_name="en_os")
elif self.config.name == 'ru_tsl':
dataset_info = datasets.DatasetInfo(
description=RUSSIAN_PAUQ_TSL_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
config_name="ru_tsl")
elif self.config.name == "en_tsl":
dataset_info = datasets.DatasetInfo(
description=ENGLISH_PAUQ_TSL_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
config_name="en_tsl")
return dataset_info
def _split_generators(self, dl_manager):
downloaded_filepath = dl_manager.download_and_extract(_URL)
dataset_name = self.config.name
splits = []
if dataset_name == 'ru_trl':
splits = [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_trl_train.json"),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_trl_test.json"),
},
)
]
elif dataset_name == 'en_trl':
splits = [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_trl_train.json"),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_trl_test.json"),
},
)]
elif dataset_name == 'ru_os':
splits = [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_os_train.json"),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_os_test.json"),
},
)
]
elif dataset_name == 'en_os':
splits = [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_os_train.json"),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_os_test.json"),
},
)
]
elif dataset_name == 'ru_tsl':
splits = [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_tsl_train.json"),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_tsl_test.json"),
},
)
]
elif dataset_name == 'en_tsl':
splits = [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_tsl_train.json"),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_tsl_test.json"),
},
)]
return splits
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": sample['sql'],
"question": sample["question"],
"question_toks": sample["question_toks"],
"query_toks": sample["query_toks"],
"query_toks_no_values": sample["query_toks_no_values"],
"template": sample["template"]
} |