Datasets:
File size: 5,220 Bytes
2189da0 8c87b52 2189da0 b4d852c bb75bc1 b4d852c 2189da0 a978908 2189da0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 |
# 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
}
|