--- 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_bytes: 30797754227 num_examples: 9893858 - name: java num_bytes: 23130202517 num_examples: 7886299 - name: javascript num_bytes: 6833869001 num_examples: 2562158 - name: php num_bytes: 13072500520 num_examples: 5455989 - name: c_sharp num_bytes: 11144245789 num_examples: 4011467 - name: c num_bytes: 6205820571 num_examples: 1978551 - name: cpp num_bytes: 6228306797 num_examples: 1934958 - name: go num_bytes: 11339059495 num_examples: 5649158 - name: rust num_bytes: 2661037428 num_examples: 1076588 - name: ruby num_bytes: 1224195690 num_examples: 544867 download_size: 26404353470 dataset_size: 112636992035 pretty_name: The Vault viewer: true --- ## 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/ ![thevault-logo](https://raw.githubusercontent.com/FSoft-AI4Code/TheVault/main/assets/thevault-title.png) ## 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 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 ``` { "repo": "irshadbhat/sndpcs", "path": "arc_eager.py", "license": "MIT" "identifier": "REDUCE", "return_type": "" "language": "Python", "code": "def REDUCE(self, configuration, label=None):\n b0 = configuration.b0\n configuration.stack.pop()", "code_tokens": "def REDUCE ( self , configuration , label = None ) : b0 = configuration . b0 configuration . stack . pop ( )", "original_docstring": "\n pops the top of the stack if it has got its head.\n ", "comment": "\"\"\"\n pops the top of the stack if it has got its head.\n \"\"\"", "docstring_tokens": "pops the top of the stack if it has got its head .", "docstring": "pops the top of the stack if it has got its head." } ``` ### Data Fields Data fields for function level: - **repo** (string): the owner/repo - **path** (string): the full path to the original file - **license** (string): license 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** (string): tokenized version of `code`, separated by whitespace - **short_docstring** (string): short, brief summarization (first line of the docstring) - **short_docstring_tokens** (string): tokenized version of `short_docstring`, separated by whitespace - **docstring** (string): the top-level comment or docstring (docstring version without param’s doc, return, exception, etc) - **docstring_tokens** tokenized version of docstring, separated by whitespace - **comment** (string): comment (line) inside the function/class, separated by `$SEP$` token - **parameters** (dict): Dictionary of parameters and its type (type can be None) - **docstring_params** (dict): Dictionary of the parsed information from docstring Due to the limitation of the huggingface data structure, we do not contain **parameters** and **docstring_params** fields in this repo. The detail of data fields can be found in [The Vault data format](https://github.com/FSoft-AI4Code/TheVault/blob/main/data/README.md) and the full dataset version can be downloaded [here](https://github.com/FSoft-AI4Code/TheVault/). ### Data Splits In this repo, The Vault is divided into 5 subsets, where three training versions are split based on dataset size, and the remains are validation set and test set. The statistic for each language is illustrated in the following section. ## 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 each language in The Vault | Language | #Code-text pair | #Repository | |:-----------|-----------------:|------------:| | Python | 9,893,858 | 628,069 | | PHP | 5,455,989 | 439,514 | | JavaScript | 2,562,158 | 355,761 | | Java | 7,886,299 | 321,129 | | C# | 4,011,467 | 150,657 | | C++ | 1,934,958 | 116,897 | | C | 1,978,551 | 88,556 | | Go | 5,649,158 | 241,238 | | Rust | 1,076,588 | 68,615 | | Ruby | 544,867 | 61,804 | ## 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", "large") function level training set dataset = load_dataset("Fsoft-AIC/the-vault-function", split_set=["train/small"]) # specific language (e.g. Golang) dataset = load_dataset("Fsoft-AIC/the-vault-function", split_set=["train"], languages=['Go']) ``` ## Additional information ### Licensing Information [More information needed] ### Citation Information ``` @misc{manh2023vault, title={The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation}, author={Dung Nguyen Manh and Nam Le Hai and Anh T. V. Dau and Anh Minh Nguyen and Khanh Nghiem and Jin Guo and Nghi D. Q. Bui}, year={2023}, } ``` ### Contributions This dataset is developed by [FSOFT AI4Code team](https://github.com/FSoft-AI4Code).