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quarel / quarel.py

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Update files from the datasets library (from 1.6.0)

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	"""TODO(quarel): Add a description here."""


	import json
	import os

	import datasets


	# TODO(quarel): BibTeX citation
	_CITATION = """\
	@inproceedings{quarel_v1,
	title={QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships},
	author={Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, Ashish Sabharwal},
	year={2018},
	journal={arXiv:1805.05377v1}
	}
	"""

	# TODO(quarel):
	_DESCRIPTION = """
	QuaRel is a crowdsourced dataset of 2771 multiple-choice story questions, including their logical forms.
	"""
	_URL = "https://s3-us-west-2.amazonaws.com/ai2-website/data/quarel-dataset-v1-nov2018.zip"


	class Quarel(datasets.GeneratorBasedBuilder):
	"""TODO(quarel): Short description of my dataset."""

	# TODO(quarel): Set up version.
	VERSION = datasets.Version("0.1.0")

	def _info(self):
	# TODO(quarel): Specifies the datasets.DatasetInfo object
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# datasets.features.FeatureConnectors
	features=datasets.Features(
	{
	# These are the features of your dataset like images, labels ...
	"id": datasets.Value("string"),
	"answer_index": datasets.Value("int32"),
	"logical_forms": datasets.features.Sequence(datasets.Value("string")),
	"logical_form_pretty": datasets.Value("string"),
	"world_literals": datasets.features.Sequence(
	{"world1": datasets.Value("string"), "world2": datasets.Value("string")}
	),
	"question": datasets.Value("string"),
	}
	),
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage="https://allenai.org/data/quarel",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	# TODO(quarel): Downloads the data and defines the splits
	# dl_manager is a datasets.download.DownloadManager that can be used to
	# download and extract URLs
	dl_dir = dl_manager.download_and_extract(_URL)
	data_dir = os.path.join(dl_dir, "quarel-dataset-v1")
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-train.jsonl")},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-test.jsonl")},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-dev.jsonl")},
	),
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	# TODO(quarel): Yields (key, example) tuples from the dataset
	with open(filepath, encoding="utf-8") as f:
	for id_, row in enumerate(f):
	data = json.loads(row)
	yield id_, {
	"id": data["id"],
	"answer_index": data["answer_index"],
	"logical_forms": data["logical_forms"],
	"world_literals": {
	"world1": [data["world_literals"]["world1"]],
	"world2": [data["world_literals"]["world2"]],
	},
	"logical_form_pretty": data["logical_form_pretty"],
	"question": data["question"],
	}