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reddit_mhp / loading_script.py

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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