Datasets:
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# 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.
# TODO: Address all TODOs and remove all explanatory comments
"""IndoQA: Indonesian Question Answering Dataset."""
import csv
import json
import os
import gdown
import datasets
_DESCRIPTION = """\
This dataset is built for question answering task.
"""
_HOMEPAGE = "https://github.com/jakartaresearch"
_TRAIN_URL = "https://drive.google.com/uc?id=1ND893H5x2gaPRRMJVajQ4hgqpopHoD0u"
_VAL_URL = "https://drive.google.com/uc?id=1mq_foV72riXb1KVBirJzTFZEe7oa8f4f"
class GooglePlayReview(datasets.GeneratorBasedBuilder):
"""IndoQA: Indonesian Question Answering Dataset."""
VERSION = datasets.Version("1.0.0")
def _info(self):
features = datasets.Features(
{
"id": datasets.Value("string"),
"context": datasets.Value("string"),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"category": datasets.Value("string"),
"span_start": datasets.Value("int16"),
"span_end": datasets.Value("int16")
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE
)
def _split_generators(self, dl_manager):
train_path = dl_manager.download_and_extract(_TRAIN_URL)
val_path = dl_manager.download_and_extract(_VAL_URL)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": val_path})
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, filepath):
"""Generate examples."""
with open(filepath, encoding="utf-8") as file:
contents = json.load(file)
for id_, row in enumerate(contents):
yield id_, row
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