Datasets:
math_qa

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


	import json
	import os

	import datasets


	# TODO(math_qa): BibTeX citation
	_CITATION = """
	"""

	# TODO(math_qa):
	_DESCRIPTION = """
	Our dataset is gathered by using a new representation language to annotate over the AQuA-RAT dataset. AQuA-RAT has provided the questions, options, rationale, and the correct options.
	"""
	_URL = "https://math-qa.github.io/math-QA/data/MathQA.zip"


	class MathQa(datasets.GeneratorBasedBuilder):
	"""TODO(math_qa): Short description of my dataset."""

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

	def _info(self):
	# TODO(math_qa): 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 ...
	"Problem": datasets.Value("string"),
	"Rationale": datasets.Value("string"),
	"options": datasets.Value("string"),
	"correct": datasets.Value("string"),
	"annotated_formula": datasets.Value("string"),
	"linear_formula": datasets.Value("string"),
	"category": 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://math-qa.github.io/math-QA/",
	citation=_CITATION,
	)

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

	def _generate_examples(self, filepath):
	"""Yields examples."""
	# TODO(math_qa): Yields (key, example) tuples from the dataset
	with open(filepath, encoding="utf-8") as f:
	data = json.load(f)
	for id_, row in enumerate(data):
	yield id_, row