--- language: - code - en multilinguality: - multiprogramming languages task_categories: - text-generation license: mit dataset_info: features: - name: identifier dtype: string - name: return_type dtype: string - name: repo dtype: string - name: path dtype: string - name: language dtype: string - name: code dtype: string - name: code_tokens dtype: string - name: original_docstring dtype: string - name: comment dtype: string - name: docstring_tokens dtype: string - name: docstring dtype: string - name: original_string dtype: string pretty_name: The Vault Function viewer: false --- ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Statistics](#dataset-statistics) - [Usage](#usage) - [Additional Information](#additional-information) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Repository:** [FSoft-AI4Code/TheVault](https://github.com/FSoft-AI4Code/TheVault) - **Paper:** [The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation](https://arxiv.org/abs/2305.06156) - **Contact:** support.ailab@fpt.com - **Website:** https://www.fpt-aicenter.com/ai-residency/

logo

# The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation
## Dataset Summary The Vault is a multilingual code-text dataset with over 69 million pairs in inline-level covering 10 popular programming languages. It is the largest corpus containing parallel code-text data. By building upon [The Stack](https://huggingface.co/datasets/bigcode/the-stack), a massive raw code sample collection, the Vault offers a comprehensive and clean resource for advancing research in code understanding and generation. It provides a high-quality dataset that includes code-text pairs at multiple levels, such as class and inline-level, in addition to the function level. The Vault can serve many purposes at multiple levels. ## Supported Tasks The Vault can be used for pretraining LLMs or downstream code-text interaction tasks. A number of tasks related to code understanding and geneartion can be constructed using The Vault such as *code summarization*, *text-to-code generation* and *code search*. ## Languages The natural language text (docstring) is in English. 10 programming languages are supported in The Vault: `Python`, `Java`, `JavaScript`, `PHP`, `C`, `C#`, `C++`, `Go`, `Ruby`, `Rust` ## Dataset Structure ### Data Instances ``` { "hexsha": "5c47f0b4c173a8fd03e4e633d9b3dd8211e67ad0", "repo": "neumanna94/beepboop", "path": "js/scripts.js", "license": [ "MIT" ], "language": "JavaScript", "identifier": "beepBoopSelector", "code": "function beepBoopSelector(inputString, bbFunction){\n if(bbFunction==1){\n return beepBoop(inputString);\n } else if(bbFunction==2){\n return beepBoop2(inputString);\n } else if(bbFunction==3){\n return beepBoop3(inputString);\n } else {\n }\n}", "code_tokens": [ "function", "beepBoopSelector", "(", "inputString", ",", "bbFunction", ")", "{", "if", "(", "bbFunction", "==", "1", ")", "{", "return", "beepBoop", "(", "inputString", ")", ";", "}", "else", "if", "(", "bbFunction", "==", "2", ")", "{", "return", "beepBoop2", "(", "inputString", ")", ";", "}", "else", "if", "(", "bbFunction", "==", "3", ")", "{", "return", "beepBoop3", "(", "inputString", ")", ";", "}", "else", "{", "}", "}" ], } ``` ### Data Fields Data fields for function level: - **hexsha** (string): the unique git hash of file - **repo** (string): the owner/repo - **path** (string): the full path to the original file - **license** (list): licenses in the repo - **language** (string): the programming language - **identifier** (string): the function or method name - **code** (string): the part of the original that is code - **code_tokens** (list): tokenized version of `code` - **original_comment** (string): original text of comment , - **comment** (string): clean version of comment, - **comment_tokens** (list): tokenized version of `comment`, - **start_point** (int): start position of `original_comment` in `code`, - **end_point** (int): end position of `original_comment` in `code`, - **prev_context** (dict): block of code before `original_comment`, - **next_context** (dict): block of code after `original_comment` ### Data Splits In this repo, the inline level data is not split, and contain in only train set. ## Dataset Statistics | | Number of inline comments | |:-----------|---------------------------:| |Python | 14,013,238 | |Java | 17,062,277 | |JavaScript | 1,438,110 | |PHP | 5,873,744 | |C | 6,778,239 | |C# | 6,274,389 | |C++ | 10,343,650 | |Go | 4,390,342 | |Ruby | 767,563 | |Rust | 2,063,784 | |TOTAL | **69,005,336** | ## Usage You can load The Vault dataset using datasets library: ```pip install datasets``` ```python from datasets import load_dataset # Load full function level dataset (40M samples) dataset = load_dataset("Fsoft-AIC/the-vault-inline") # specific language (e.g. Python) dataset = load_dataset("Fsoft-AIC/the-vault-inline", languages=['Python']) # dataset streaming data = load_dataset("Fsoft-AIC/the-vault-inline", streaming= True) for sample in iter(data['train']): print(sample) ``` A back up dataset can be downloaded in azure storage. See [Download The Vault from Azure blob storage](https://github.com/FSoft-AI4Code/TheVault#download-via-link). ## Additional information ### Licensing Information MIT License ### Citation Information ``` @article{manh2023vault, title={The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation}, author={Manh, Dung Nguyen and Hai, Nam Le and Dau, Anh TV and Nguyen, Anh Minh and Nghiem, Khanh and Guo, Jin and Bui, Nghi DQ}, journal={arXiv preprint arXiv:2305.06156}, year={2023} } ``` ### Contributions This dataset is developed by [FSOFT AI4Code team](https://github.com/FSoft-AI4Code).