Datasets:

tianyang
/

repobench-c

	# 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.

	"""RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems"""

	import gzip
	import pickle
	import textwrap
	import datasets

	_CITATION = """\
	@misc{liu2023repobench,
	title={RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems},
	author={Tianyang Liu and Canwen Xu and Julian McAuley},
	year={2023},
	eprint={2306.03091},
	archivePrefix={arXiv},
	primaryClass={cs.CL}
	}
	"""

	_DESCRIPTION = """\
	RepoBench is a dataset that benchmarks repository-level code auto-completion systems.

	RepoBench-C denotes RepoBench for code completion,
	which is subtask of RepoBench for next-line code prediction given both cross-file and in-file context.
	"""

	_HOMEPAGE = "https://github.com/Leolty/repobench"

	_LICENSE = "Apache License 2.0"

	_URLs = {
	"python_cff": "https://raw.githubusercontent.com/Leolty/repobench/main/data/completion/python/cross_file_first.gz",
	"python_cfr": "https://raw.githubusercontent.com/Leolty/repobench/main/data/completion/python/cross_file_random.gz",
	"python_if": "https://raw.githubusercontent.com/Leolty/repobench/main/data/completion/python/in_file.gz",
	"java_cff": "https://raw.githubusercontent.com/Leolty/repobench/main/data/completion/java/cross_file_first.gz",
	"java_cfr": "https://raw.githubusercontent.com/Leolty/repobench/main/data/completion/java/cross_file_random.gz",
	"java_if": "https://raw.githubusercontent.com/Leolty/repobench/main/data/completion/java/in_file.gz"
	}


	def construct_prompt(data_point:dict, language:str):

	if language == "python":
	path = f"# Path: {data_point['file_path']}"

	elif language == "java":
	path = f"// Path: {data_point['file_path']}"

	prompt = f"""{data_point['context']}
	{path}
	{data_point['import_statement']}

	{data_point['code']}"""

	return prompt

	class RepoBenchC(datasets.GeneratorBasedBuilder):
	"""RepoBench"""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="python_cff",
	description=textwrap.dedent(
	"""
	cff: cross_file_first -> mask the the line that a cross-file module is first used
	"""
	)
	),
	datasets.BuilderConfig(
	name="python_cfr",
	description=textwrap.dedent(
	"""
	cfr: cross_file_random -> mask a random line that a cross-file module is used (not the first time)
	"""
	)
	),
	datasets.BuilderConfig(
	name="python_if",
	description=textwrap.dedent(
	"""
	if: in_file -> mask a random line with no cross-file module
	"""
	)
	),
	datasets.BuilderConfig(
	name="java_cff",
	description=textwrap.dedent(
	"""
	cff: cross_file_first -> mask the the line that a cross-file module is first used
	"""
	)
	),
	datasets.BuilderConfig(
	name="java_cfr",
	description=textwrap.dedent(
	"""
	cfr: cross_file_random -> mask a random line that a cross-file module is used (not the first time)
	"""
	)
	),
	datasets.BuilderConfig(
	name="java_if",
	description=textwrap.dedent(
	"""
	if: in_file -> mask a random line with no cross-file module
	"""
	)
	)
	]

	def _info(self):
	features = datasets.Features(
	{
	"repo_name": datasets.Value("string"),
	"file_path": datasets.Value("string"),
	"context": datasets.Value("string"),
	"import_statement": datasets.Value("string"),
	"code": datasets.Value("string"),
	"prompt": datasets.Value("string"),
	"next_line": datasets.Value("string")
	}
	)

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	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(config_urls)

	return [
	datasets.SplitGenerator(
	name=datasets.Split("train"),
	gen_kwargs={"data_dir": data_dir, "split": "train"},
	),
	datasets.SplitGenerator(
	name=datasets.Split("dev"),
	gen_kwargs={"data_dir": data_dir, "split": "dev"},
	),
	datasets.SplitGenerator(
	name=datasets.Split("test"),
	gen_kwargs={"data_dir": data_dir, "split": "test"},
	)
	]

	def _generate_examples(self, data_dir, split):
	""" Yields examples. """
	with gzip.open(data_dir, "rb") as f:
	data = pickle.load(f)

	for i, example in enumerate(data[split]):

	prompt = construct_prompt(example, self.config.name.split("_")[0])

	yield i, {
	"repo_name": example["repo_name"],
	"file_path": example["file_path"],
	"context": example["context"],
	"import_statement": example["import_statement"],
	"code": example["code"],
	"prompt": prompt,
	"next_line": example["next_line"]
	}