upload data config file

repobench-c.py

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+# 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
+from utils import construct_prompt
+
+_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/code_completion/python/cross_file_first.gz",
+    "python_cfr": "https://raw.githubusercontent.com/Leolty/repobench/main/data/code_completion/python/cross_file_random.gz",
+    "python_if": "https://raw.githubusercontent.com/Leolty/repobench/main/data/code_completion/python/in_file.gz",
+    "java_cff": "https://raw.githubusercontent.com/Leolty/repobench/main/data/code_completion/java/cross_file_first.gz",
+    "java_cfr": "https://raw.githubusercontent.com/Leolty/repobench/main/data/code_completion/java/cross_file_random.gz",
+    "java_if": "https://raw.githubusercontent.com/Leolty/repobench/main/data/code_completion/java/in_file.gz"
+}
+
+class RepoBenchR(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.Sequence(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"]
+            }
+

utils.py

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+
+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