README.md · Fsoft-AIC/the-vault-function at 1252c620f22a56894793cbb8cddf0fdd4f898e9e

metadata

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

Dataset Description
Dataset Summary
Supported Tasks
Languages
Dataset Structure
Dataset Statistics
Usage
Additional Information

Dataset Description

Repository: FSoft-AI4Code/TheVault
Paper: The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation
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, 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 and the full dataset version can be downloaded here.

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

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.

Datasets:

Fsoft-AIC
/

the-vault-function

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