就下游任务而言,GraphCodeBERT 文中主要完成了 Natural Language Code Search、Clone Detection、Code Translation 和 Code Refinement 这几个任务,它同样适用 CodeXGLUE Benchmark 中的其他任务,比如 Code Summarization 等。 GraphCodeBERT 相较于前作 CodeBERT 解决了 CodePTM 只学习自然语义,而不学代码结构/语法的问题。
Transformer networks such as CodeBERT already achieve outstanding results for code clone detection in benchmark datasets, so one could assume that this task has already been solved. However, code clone detection is not a trivial task. Semantic code clones, in particular, are challenging to detect....
代码搜索任务的含义是给定一种自然语言输入,要求从一组候选代码中找到语义最相关的代码,使用的数据集是CodeSearchNet的数据集,使用代码文档的第一段作为query,以MRR(Mean Reciprocal Rank)作为评价指标,由上图可见,GraphCodeBert模型在每个语言的数据集上都表现优异。 代码克隆检测任务 code clone detection 代码克隆检测...
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class CloneDetectionHandler(BaseHandler,ABC): def __int__(self): super(CloneDetectionHandler,self).__init__() self.initialized = False def initialize(self, ctx): self.manifest = ctx.manifest logger.info(self.manifest) properties = ctx.system_properties ...
torch-model-archiver --model-name BERTClass --version 1.0 \ --serialized-file ./CloneDetection.bin \ --model-file ./model.py \ --handler ./handler.py \ 启动服务 创建modelstore 目录,将上一步打包生成的 BERTClass.mar 包文件放入 modelstore 目录中,启动模型服务。 torchserve --start --ncs...
Furthermore, because fine-tuning pre-trained CodeBERT with solidity code yields an efficient model, we will extend the fine-tuning method to other solidity code tasks, such as clone detection and code summarization. 0 Introduction 1 Fine-Tuning CodeBERT for Code Search 2 Evaluation 3 Conclusion...
For downstream tasks like code search, clone detection, code refinement and code translation, please refer to the GraphCodeBERT folder. UniXcoder This repo will provide the code for reproducing the experiments in UniXcoder: Unified Cross-Modal Pre-training for Code Representation. UniXcoder is a un...
Code SearchCodeSearchNetGraphCodeBERTOverall77.4# 3 Compare Go84.1# 5 Compare Ruby73.2# 5 Compare Python87.9# 3 Compare Java75.7# 6 Compare JS71.1# 5 Compare PHP72.5# 3 Compare Type predictionManyTypes4TypeScriptGraphCodeBERTAverage Accuracy62.51# 3 ...
increases CodeBERT’s performance in three code-related tasks, i.e., algorithm classification, code clone detection, and code search. An empirical evaluation of several pre-trained models for code diagnostic tasks, called probes, has been conducted by Karmakar and Robbes (2022). To enable the ...