Datasets:
cos_e

	# coding=utf-8
	# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
	#
	# 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.

	# Lint as: python3
	"""Commonsense Explanations (CoS-E) Dataset."""


	import json

	import datasets


	_CITATION = """
	@inproceedings{rajani2019explain,
	title = {Explain Yourself! Leveraging Language models for Commonsense Reasoning},
	author = {Rajani, Nazneen Fatema and
	McCann, Bryan and
	Xiong, Caiming and
	Socher, Richard}
	year={2019}
	booktitle = {Proceedings of the 2019 Conference of the Association for Computational Linguistics (ACL2019)}
	url ={https://arxiv.org/abs/1906.02361}
	}
	"""

	_DESCRIPTION = """
	Common Sense Explanations (CoS-E) allows for training language models to
	automatically generate explanations that can be used during training and
	inference in a novel Commonsense Auto-Generated Explanation (CAGE) framework.
	"""

	_COS_E_URL = "https://raw.githubusercontent.com/salesforce/cos-e/master/data/"

	# COS E has explanations for the CQA dataset, which is joined by ID.
	_CQA_V1_11_URL_TRAIN = "https://s3.amazonaws.com/commensenseqa/train_rand_split.jsonl"
	_CQA_V1_11_URL_DEV = "https://s3.amazonaws.com/commensenseqa/dev_rand_split.jsonl"
	_CQA_V1_11_URL_TEST = "https://s3.amazonaws.com/commensenseqa/test_rand_split_no_answers.jsonl"

	_CQA_V1_0_URL_TRAIN = _COS_E_URL + "v1.0/train_rand_split.jsonl"
	_CQA_V1_0_URL_DEV = _COS_E_URL + "v1.0/dev_rand_split.jsonl"
	_CQA_V1_0_URL_TEST = _COS_E_URL + "v1.0/test_rand_split_no_answers.jsonl"


	def _download_and_index_cqa(dl_manager, name):
	"""Downloads CQA and returns it, indexed by id, for joining with Cos-E."""

	downloaded_files = dl_manager.download_and_extract(
	{
	"cqa_train": _CQA_V1_11_URL_TRAIN if name == "v1.11" else _CQA_V1_0_URL_TRAIN,
	"cqa_dev": _CQA_V1_11_URL_DEV if name == "v1.11" else _CQA_V1_0_URL_DEV,
	"cqa_test": _CQA_V1_11_URL_TEST if name == "v1.11" else _CQA_V1_0_URL_TEST,
	}
	)

	# NB: "cqa_test" is included in the files, but not in any of the CoS-E splits.
	cqa_splits = ["cqa_train", "cqa_dev"]
	cqa_complete = []
	for split in cqa_splits:
	with open(downloaded_files[split], encoding="utf-8") as f:
	for _, line in enumerate(f):
	d = json.loads(line)
	cqa_complete.append(d)

	# Index the CQA dataset by id for joining with Cos-E.
	cqa_indexed = {}
	for d in cqa_complete:
	cqa_indexed[d["id"]] = d
	return cqa_indexed


	def _get_choices_and_answer(cqa):
	"""Returns choices and the answer from a cqa example."""
	choices = []
	answer_key = cqa["answerKey"]
	answer = None
	for choice in cqa["question"]["choices"]:
	choices.append(choice["text"])
	if answer_key == choice["label"]:
	answer = choice["text"]
	return choices, answer


	class CosEConfig(datasets.BuilderConfig):

	"""BuilderConfig for CosE"""

	def __init__(self, **kwargs):
	"""

	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(CosEConfig, self).__init__(**kwargs)


	class CosE(datasets.GeneratorBasedBuilder):
	"""CoS-E: Common Sense Explanations corpus."""

	BUILDER_CONFIGS = [
	CosEConfig(
	name="v1.0",
	description="cos-e version 1.0",
	version=datasets.Version("1.0.0", ""),
	),
	CosEConfig(
	name="v1.11",
	description="cos-e version 1.11",
	version=datasets.Version("1.11.0", ""),
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"question": datasets.Value("string"),
	"choices": datasets.features.Sequence(datasets.Value("string")),
	"answer": datasets.Value("string"),
	"abstractive_explanation": datasets.Value("string"),
	"extractive_explanation": datasets.Value("string"),
	}
	),
	supervised_keys=None,
	homepage="https://github.com/salesforce/cos-e",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""

	# NB: The CQA Dataset should be read only once, and only by callers who
	# want to _create_ the Cos-E dataset from scratch.
	cqa_indexed = _download_and_index_cqa(dl_manager, self.config.name)

	if self.config.name == "v1.11":
	files = dl_manager.download_and_extract(
	{
	"dev": [_COS_E_URL + "v1.11/cose_dev_v1.11_processed.jsonl"],
	"train": [_COS_E_URL + "v1.11/cose_train_v1.11_processed.jsonl"],
	}
	)

	elif self.config.name == "v1.0":
	files = dl_manager.download_and_extract(
	{
	"dev": [_COS_E_URL + "v1.0/cose_dev_v1.0_processed.jsonl"],
	"train": [_COS_E_URL + "v1.0/cose_train_v1.0_processed.jsonl"],
	}
	)
	else:
	raise ValueError("Unknown config name")
	# We use the CoS-E/CQA dev set as our validation set.
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"files": files["train"], "cqa_indexed": cqa_indexed},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={"files": files["dev"], "cqa_indexed": cqa_indexed},
	),
	]

	def _generate_examples(self, files, **kwargs):
	"""Yields examples."""
	cqa_indexed = kwargs["cqa_indexed"]
	for filepath in files:
	with open(filepath, encoding="utf-8") as f:
	for line in f:
	cos = json.loads(line)
	cqa = cqa_indexed[cos["id"]]
	choices, answer = _get_choices_and_answer(cqa)
	yield cos["id"], {
	"id": cos["id"],
	"question": cqa["question"]["stem"],
	"choices": choices,
	"answer": answer,
	"abstractive_explanation": cos["explanation"]["open-ended"],
	"extractive_explanation": cos["explanation"]["selected"],
	}