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lsat_qa / lsat_qa.py

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clefourrier HF staff

assignment typo

e710031 about 1 year ago

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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.
	"""Covid Dialog dataset in English and Chinese"""


	import copy
	import os
	import re
	import textwrap
	import json

	import datasets


	# BibTeX citation
	_CITATION = """
	"""

	# Official description of the dataset
	_DESCRIPTION = textwrap.dedent(
	"""
	"""
	)

	# Link to an official homepage for the dataset here
	_HOMEPAGE = ""

	_LICENSE = ""


	import datasets
	import os
	import json

	names = ["all", "assignment", "grouping", "miscellaneous", "ordering"]

	class LsatQA(datasets.GeneratorBasedBuilder):
	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [datasets.BuilderConfig(name=name, version=datasets.Version("1.0.0"), description=_DESCRIPTION) for name in names]

	def _info(self):
	features = datasets.Features(
	{
	"passage": datasets.Value("string"),
	"question": datasets.Value("string"),
	"references": datasets.Sequence(datasets.Value("string")),
	"gold_index": datasets.Value("int64"),
	}
	)
	return datasets.DatasetInfo(
	description=f"LSAT QA dataset, as preprocessed and shuffled in HELM",
	features=features,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	test = dl_manager.download(os.path.join(self.config.name, "test.jsonl"))
	train = dl_manager.download(os.path.join(self.config.name, "train.jsonl"))
	val = dl_manager.download(os.path.join(self.config.name, "valid.jsonl"))

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"file": train},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={"file": val},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"file": test},
	),
	]

	# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
	def _generate_examples(self, file):
	with open(file, encoding="utf-8") as f:
	for ix, line in enumerate(f):
	yield ix, json.loads(line)