File size: 8,999 Bytes
0c72583 36680c8 0c72583 36680c8 0c72583 3060c16 0c72583 a10de01 107a243 0c72583 a10de01 0c72583 b53992d 0c72583 edc339a 0c72583 fb124e7 0c72583 fb124e7 0c72583 fb124e7 0c72583 38896f7 1252c62 0c72583 57a2830 0c72583 c459c15 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 |
---
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:** [email protected]
- **Website:** https://www.fpt-aicenter.com/ai-residency/
## 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": "<not_specify>"
"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 (20,000 samples in each). The statistic for each language is illustrated in the following section.
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 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. 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)
```
## 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). |