Datasets:
mbpp

	import json

	import datasets


	_DESCRIPTION = """\
	The MBPP (Mostly Basic Python Problems) dataset consists of around 1,000 crowd-sourced Python
	programming problems, designed to be solvable by entry level programmers, covering programming
	fundamentals, standard library functionality, and so on. Each problem consists of a task
	description, code solution and 3 automated test cases. The sanitized subset of the data has been
	hand-verified by the authors.
	"""

	_URLs = {
	"full": "https://raw.githubusercontent.com/google-research/google-research/master/mbpp/mbpp.jsonl",
	"sanitized": "https://raw.githubusercontent.com/google-research/google-research/master/mbpp/sanitized-mbpp.json",
	}

	_CITATION = """\
	@article{austin2021program,
	title={Program Synthesis with Large Language Models},
	author={Austin, Jacob and Odena, Augustus and Nye, Maxwell and Bosma, Maarten and Michalewski, Henryk and Dohan, David and Jiang, Ellen and Cai, Carrie and Terry, Michael and Le, Quoc and others},
	journal={arXiv preprint arXiv:2108.07732},
	year={2021}
	}"""

	_HOMEPAGE = "https://github.com/google-research/google-research/tree/master/mbpp"

	_LICENSE = "CC-BY-4.0"


	class MBPP(datasets.GeneratorBasedBuilder):
	"""MBPP: Mostly Basic Python Problems Dataset"""

	VERSION = datasets.Version("1.0.2")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="full",
	version=datasets.Version("1.0.2"),
	description=_DESCRIPTION,
	),
	datasets.BuilderConfig(name="sanitized", version=datasets.Version("1.0.2"), description=_DESCRIPTION),
	]

	DEFAULT_CONFIG_NAME = "full"

	def _info(self):
	if self.config.name == "full":
	features = datasets.Features(
	{
	"task_id": datasets.Value("int32"),
	"text": datasets.Value("string"),
	"code": datasets.Value("string"),
	"test_list": datasets.Sequence(datasets.Value("string")),
	"test_setup_code": datasets.Value("string"),
	"challenge_test_list": datasets.Sequence(datasets.Value("string")),
	}
	)
	elif self.config.name == "sanitized":
	features = datasets.Features(
	{
	"source_file": datasets.Value("string"),
	"task_id": datasets.Value("int32"),
	"prompt": datasets.Value("string"),
	"code": datasets.Value("string"),
	"test_imports": datasets.Sequence(datasets.Value("string")),
	"test_list": datasets.Sequence(datasets.Value("string")),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	config_urls = _URLs[self.config.name]
	data_dir = dl_manager.download_and_extract(config_urls)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"filepath": data_dir, "split": "train"},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"filepath": data_dir, "split": "test"},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={"filepath": data_dir, "split": "validation"},
	),
	datasets.SplitGenerator(
	name=datasets.Split("prompt"),
	gen_kwargs={"filepath": data_dir, "split": "prompt"},
	),
	]

	def _generate_examples(self, filepath, split):
	if self.config.name == "full":

	def _read_lines(fn, start, end):
	data = []
	with open(fn, encoding="utf-8") as f:
	for line in f:
	sample = json.loads(line)
	if start <= sample["task_id"] <= end:
	data.append(sample)
	elif sample["task_id"] > end:
	break
	return data

	if split == "test":
	data = _read_lines(filepath, 11, 510)
	elif split == "train":
	data = _read_lines(filepath, 601, 974)
	elif split == "validation":
	data = _read_lines(filepath, 511, 600)
	elif split == "prompt":
	data = _read_lines(filepath, 1, 10)
	elif self.config.name == "sanitized":
	with open(filepath, encoding="utf-8") as f:
	data = json.load(f)
	if split == "test":
	data = [sample for sample in data if 11 <= sample["task_id"] <= 510]
	elif split == "train":
	data = [sample for sample in data if 601 <= sample["task_id"] <= 974]
	elif split == "validation":
	data = [sample for sample in data if 511 <= sample["task_id"] <= 600]
	elif split == "prompt":
	data = [sample for sample in data if 1 <= sample["task_id"] <= 10]
	id_ = 0
	for sample in data:
	yield id_, sample
	id_ += 1