Datasets:
Sub-tasks:
document-retrieval
Languages:
code
Multilinguality:
multilingual
Language Creators:
found
Source Datasets:
original
ArXiv:
Tags:
code
License:
# 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-P denotes RepoBench for pipeline, | |
which is subtask of RepoBench including both relevant code retrieval and next-line code prediction. | |
""" | |
_HOMEPAGE = "https://github.com/Leolty/repobench" | |
_LICENSE = "Apache License 2.0" | |
_URLs = { | |
"python": "https://raw.githubusercontent.com/Leolty/repobench/main/data/pipeline/python/", | |
"java": "https://raw.githubusercontent.com/Leolty/repobench/main/data/pipeline/java/" | |
} | |
class RepoBenchP(datasets.GeneratorBasedBuilder): | |
"""RepoBench""" | |
VERSION = datasets.Version("1.0.0") | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig( | |
name="python", | |
description=textwrap.dedent( | |
""" | |
This part of RepoBench-P is for python language. | |
""" | |
) | |
), | |
datasets.BuilderConfig( | |
name="java", | |
description=textwrap.dedent( | |
""" | |
This part of RepoBench-P is for java language. | |
""" | |
) | |
) | |
] | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"repo_name": datasets.Value("string"), | |
"file_path": datasets.Value("string"), | |
"context": [{ | |
"path": datasets.Value("string"), | |
"identifier": datasets.Value("string"), | |
"snippet": datasets.Value("string") | |
}], | |
"import_statement": datasets.Value("string"), | |
"code": datasets.Value("string"), | |
"next_line": datasets.Value("string"), | |
"gold_snippet_index": datasets.Value("int32"), | |
} | |
) | |
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({ | |
"cff": config_urls + "cross_file_first.gz", | |
"cfr": config_urls + "cross_file_random.gz", | |
"if": config_urls + "in_file.gz" | |
} | |
) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split("cff"), | |
gen_kwargs={"data_dir": data_dir, "split": "cff"} | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split("cfr"), | |
gen_kwargs={"data_dir": data_dir, "split": "cfr"} | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split("if"), | |
gen_kwargs={"data_dir": data_dir, "split": "if"} | |
) | |
] | |
def _generate_examples(self, data_dir, split): | |
""" Yields examples. """ | |
with gzip.open(data_dir[split], "rb") as f: | |
data = pickle.load(f) | |
if split == "cff" or split == "cfr": | |
for i, example in enumerate(data): | |
yield i, { | |
"repo_name": example["repo_name"], | |
"file_path": example["file_path"], | |
"context": example["context"], | |
"import_statement": example["import_statement"], | |
"code": example["code"], | |
"next_line": example["next_line"], | |
"gold_snippet_index": example["gold_snippet_index"] | |
} | |
elif split == "if": | |
for i, example in enumerate(data): | |
yield i, { | |
"repo_name": example["repo_name"], | |
"file_path": example["file_path"], | |
"context": example["context"], | |
"import_statement": example["import_statement"], | |
"code": example["code"], | |
"next_line": example["next_line"], | |
# in-file data has no gold_snippet_index | |
"gold_snippet_index": -1 | |
} | |