--- 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 splits: - name: python num_examples: 7825291 - name: java num_examples: 6667422 - name: javascript num_examples: 1683568 - name: php num_examples: 4696756 - name: c_sharp num_examples: 3350316 - name: c num_examples: 1685966 - name: cpp num_examples: 1709448 - name: go num_examples: 5153436 - name: rust num_examples: 864987 - name: ruby num_examples: 461585 pretty_name: The Vault 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/

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# The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation
## Dataset Summary The Vault is a multilingual code-text dataset with over 40 million pairs 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", "return_type": "", "original_string": "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}", "original_docstring": "//Determines what beepBoop function to use", "docstring": "Determines what beepBoop function to use", "docstring_tokens": [ "Determines", "what", "beepBoop", "function", "to", "use" ], "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", "{", "}", "}" ], "short_docstring": "Determines what beepBoop function to use", "short_docstring_tokens": [ "Determines", "what", "beepBoop", "function", "to", "use" ], "comment": [], "parameters": [ { "param": "inputString", "type": null }, { "param": "bbFunction", "type": null } ], "docstring_params": { "returns": [], "raises": [], "params": [ { "identifier": "inputString", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "bbFunction", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] } } ``` ### 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 - **return_type** (string): the type returned by the function - **original_string** (string): original version of function/class node - **original_docstring** (string): the raw string before tokenization or parsing - **code** (string): the part of the original that is code - **code_tokens** (list): tokenized version of `code` - **short_docstring** (string): short, brief summarization (first line of the docstring) - **short_docstring_tokens** (list): tokenized version of `short_docstring - **docstring** (string): the top-level comment or docstring (docstring version without param’s doc, return, exception fields, etc) - **docstring_tokens** (list): tokenized version of docstring - **comment** (list): list of comments (line) inside the function/class - **parameters** (list): List of parameters and its type (type can be None) - **docstring_params** (dict): Dictionary of the parsed information from docstring See [here](https://github.com/FSoft-AI4Code/TheVault/blob/main/data/README.md) for more details and examples. ### Data Splits In this repo, The Vault is divided into 5 subsets, where three training versions are split based on size of the full training set, and the remains are validation set and test set (approximate 20,000 samples in each). The statistic for languages in each split set is illustrated in the following section. Before split, the dataset is deduplicated. There are 3 versions of training set that are small (5%), medium (20%) and large (100%). ## Dataset Statistics - Compare to other benchmarks | Dataset | #Language | #Code-text pair | |:--------------------------|----------:|-----------------:| | PyMT5 | 1 | ≈ 7,700,000 | | CoDesc | 1 | 4,211,516 | | CodeSearchNet | 6 | 2,326,976 | | CodeSearchNet (CodeXGLUE) | 6 | 1,005,474 | | Deepcom | 1 | 424,028 | | CONCODE | 1 | 2,184,310 | | Funcom | 1 | 2,149,121 | | CodeT5 | 8 | 3,158,313 | | **The Vault** | **10** | **40,993,893** | - Statistic for split sets | | train/small | train/medium | train/full | validation | test | total | |:-----------|------------:|-------------:|-----------:|-----------:|-------:|--------------:| |Python | 370,657 | 1,952,110 | 7,772,647 | 30,992 | 21,652 | 7,825,291 | |Java | 351,213 | 1,612,366 | 6,629,193 | 22,677 | 15,552 | 6,667,422 | |JavaScript | 82,931 | 404,729 | 1,640,416 | 22,044 | 21,108 | 1,683,568 | |PHP | 236,638 | 1,155,476 | 4,656,371 | 21,375 | 19,010 | 4,696,756 | |C | 105,978 | 381,207 | 1,639,319 | 27,525 | 19,122 | 1,685,966 | |C# | 141,090 | 783,166 | 3,305,891 | 24,787 | 19,638 | 3,350,316 | |C++ | 87,420 | 410,907 | 1,671,268 | 20,011 | 18,169 | 1,709,448 | |Go | 267,535 | 1,319,547 | 5,109,020 | 19,102 | 25,314 | 5,153,436 | |Ruby | 23,921 | 112,574 | 424,339 | 17,338 | 19,908 | 461,585 | |Rust | 35,367 | 224,015 | 825,130 | 16,716 | 23,141 | 864,987 | |TOTAL | 1,702,750 | 8,356,097 |33,673,594 |222,567 |202,614 |**34,098,775** | ## 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-function") # Load function level train/validation/test set dataset = load_dataset("Fsoft-AIC/the-vault-function", split_set=["train"]) # Load "small" (or "medium", "full") version of function level training set dataset = load_dataset("Fsoft-AIC/the-vault-function", split_set=["train/small"]) # specific language (e.g. Python) dataset = load_dataset("Fsoft-AIC/the-vault-function", split_set=["train"], languages=['Python']) # dataset streaming data = load_dataset("Fsoft-AIC/the-vault-function", split_set= ["train"]) 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).