File size: 3,558 Bytes
24a463d eb0e28b 24a463d ebf0fda dc8bb77 24a463d eb0e28b 24a463d b207441 24a463d b207441 24a463d b207441 24a463d b207441 24a463d 52ac233 eb0e28b dc8bb77 eb0e28b dc8bb77 eb0e28b |
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 |
# 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.
"""The WikiTableQuestions dataset is a large-scale dataset for the task of question answering on semi-structured tables."""
import os
import datasets
import json
_HOMEPAGE = "https://finqasite.github.io/index.html"
_GIT_ARCHIVE_URL = (
"https://github.com/czyssrs/FinQA/archive/refs/heads/main.zip"
)
class FinQA(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
def _info(self):
features = datasets.Features(
{
# "filename": datasets.Value("string"),
"id": datasets.Value("string"),
"post_text": datasets.features.Sequence(datasets.Value("string")),
"pre_text": datasets.features.Sequence(datasets.Value("string")),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"gold_evidence": datasets.features.Sequence(datasets.Value("string")),
"table": datasets.features.Sequence(datasets.features.Sequence(datasets.Value("string"))),
}
)
return datasets.DatasetInfo(
features=features,
)
def _split_generators(self, dl_manager):
extracted_path = dl_manager.download_and_extract(_GIT_ARCHIVE_URL)
print(extracted_path)
train_file = os.path.join(extracted_path, "FinQA-main", "dataset", "train.json")
dev_file = os.path.join(extracted_path, "FinQA-main", "dataset", "dev.json")
test_file = os.path.join(extracted_path, "FinQA-main", "dataset", "test.json")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"main_filepath": train_file},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"main_filepath": dev_file},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"main_filepath": test_file},
),
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, main_filepath):
# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
with open(main_filepath, encoding="utf-8") as f:
# skip the first line since it is the tsv header
lines = json.load(f)
for idx, example in enumerate(lines):
yield idx, {
"id": example['id'],
"post_text": example['post_text'],
"pre_text": example['pre_text'],
"question": example['qa']['question'],
"answer": example['qa']['answer'],
"table": example['table'],
"gold_evidence": list(example['qa']['gold_inds'].values())
}
|