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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.
"""reddit_mhp dataset."""
import json
import os
import datasets
_DESCRIPTION = """ FutureWarning
"""
_CITATION = """ null """
_URLs = {
"train": "https://huggingface.co/datasets/siyangliu/reddit_mhp/resolve/main/train.json",
"valid": "https://huggingface.co/datasets/siyangliu/reddit_mhp/resolve/main/valid.json",
"test": "https://huggingface.co/datasets/siyangliu/reddit_mhp/resolve/main/test.json",
}
class redditMHP(datasets.GeneratorBasedBuilder):
"""redditMHP dataset."""
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="plain_text",
description="plain text",
version=VERSION,
)
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"question": datasets.Value("string"),
"questionID": datasets.Value("string"),
"description": datasets.Value("string"),
"topic": datasets.Value("string"),
"answer": datasets.Value("string"),
"answerID": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="https://huggingface.co/datasets/siyangliu/reddit_mhp",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
data_dir = dl_manager.download_and_extract(_URLs)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": data_dir["train"]
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": data_dir["test"]
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": data_dir["valid"]
},
),
]
def _generate_examples(self, filepath, label_filepath=None, strategy=False):
"""Yields examples."""
with open(filepath, encoding="utf-8") as input_file:
dataset = json.load(input_file)
idx = 0
for meta_data in dataset:
yield idx, {"question": meta_data["question"], "description": meta_data["description"], "questionID":meta_data['post_id'], "answerID": meta_data["comment_id"], "answer": meta_data["answer"], "topic":meta_data["topic"]}
idx += 1
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