File size: 3,960 Bytes
71ad985 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 |
# 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.
"""Spider: A Large-Scale Human-Labeled Dataset for Text-to-SQL Tasks"""
import json
import os
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@article{yu2018spider,
title={Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task},
author={Yu, Tao and Zhang, Rui and Yang, Kai and Yasunaga, Michihiro and Wang, Dongxu and Li, Zifan and Ma, James and Li, Irene and Yao, Qingning and Roman, Shanelle and others},
journal={arXiv preprint arXiv:1809.08887},
year={2018}
}
"""
_DESCRIPTION = """\
Spider is a large-scale complex and cross-domain semantic parsing and text-toSQL dataset annotated by 11 college students
"""
_HOMEPAGE = "https://yale-lily.github.io/spider"
_LICENSE = "CC BY-SA 4.0"
_URL = "https://huggingface.co/datasets/amitdanin/s3_spyder/resolve/main/data/spider_santa.zip"
class Spider(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="spider",
version=VERSION,
description="Spider: A Large-Scale Human-Labeled Dataset for Text-to-SQL Tasks",
),
]
def _info(self):
features = datasets.Features(
{
"db_id": datasets.Value("string"),
"query": datasets.Value("string"),
"question": datasets.Value("string"),
"query_toks": datasets.features.Sequence(datasets.Value("string")),
"query_toks_no_value": datasets.features.Sequence(datasets.Value("string")),
"question_toks": datasets.features.Sequence(datasets.Value("string")),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
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, "spider/train_spider.json"),
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"data_filepath": os.path.join(downloaded_filepath, "spider/dev.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:
spider = json.load(f)
for idx, sample in enumerate(spider):
yield idx, {
"db_id": sample["db_id"],
"query": sample["query"],
"question": sample["question"],
"query_toks": sample["query_toks"],
"query_toks_no_value": sample["query_toks_no_value"],
"question_toks": sample["question_toks"],
}
|