| --- |
| license: mit |
| language: |
| - en |
| --- |
| ## Dataset Description |
|
|
| This dataset contains code snippets from Triton-based projects across GitHub, specifically filtered to include only repositories with permissive licenses (MIT, Apache, BSD, etc.). Each entry in the dataset includes: |
|
|
| - Triton code snippet |
| - Repository information |
| - File path |
| - Commit hash |
| - Direct GitHub URL to the source code |
| - License information |
| - Categorization of the code functionality |
|
|
| ## Dataset Creation |
|
|
| The dataset was created by: |
|
|
| 1. Collecting Triton code snippets from public GitHub repositories |
| 2. Categorizing the code snippets based on functionality (Using claude) |
| 3. Filtering to keep only snippets from repositories with permissive licenses using a custom `should_keep_license` function |
|
|
| ## License Information |
|
|
| This dataset is released under the MIT License. However, each code snippet in the dataset comes from a repository with its own specific license (all permissive). The license type for each snippet is included in the dataset. |
|
|
| Permissive licenses included in this dataset: |
| - MIT |
| - BSD |
| - APACHE |
| - CC0 |
|
|
| ## Format and Usage |
|
|
| The dataset is provided in two formats: |
| - JSON format (`permissive_triton_dataset.json`) |
| - Parquet format (`permissive_triton_dataset.parquet`) |
|
|
| ### Sample Data Structure |
|
|
| ```json |
| { |
| "uuid": "...", |
| "file_name": "example_triton_file.py", |
| "repo_name": "username/repo", |
| "file_path": "path/to/file.py", |
| "commit_hash": "abcdef123456", |
| "starcount": 42, |
| "input": "@triton.jit\ndef example_kernel(...):\n ...", |
| "category": { |
| "Functionality": ["Category1", "Category2"] |
| }, |
| "licenses": ["MIT"], |
| "github_url": "https://github.com/username/repo/blob/abcdef123456/path/to/file.py" |
| } |
| ``` |
|
|
| ### Field Descriptions |
|
|
| | Field | Description | |
| |-------|-------------| |
| | `uuid` | Unique identifier for the entry in the dataset | |
| | `file_name` | Name of the source code file | |
| | `repo_name` | GitHub repository name in format "username/repo" | |
| | `file_path` | Path to the file within the repository | |
| | `commit_hash` | Git commit hash for the specific version of the file | |
| | `starcount` | Number of stars the repository had at the time of data collection | |
| | `input` | The actual Triton code snippet | |
| | `category` | Categorization of the code functionality (labeled using Claude) | |
| | `licenses` | List of permissive license types applicable to this code | |
| | `github_url` | Direct URL to view the file on GitHub at the specific commit | |
|
|
| #### Category Types |
|
|
| We consider categories in the following domains: Functionality, Data Type, Performance Objective, Parallelization Strategy, and Memory Access Pattern. |
| We optinally add labels to each of these domains per entry to try and describe the data (using claude). |
|
|
| ### Loading the Dataset |
|
|
| ```python |
| # Using JSON |
| import json |
| with open('permissive_triton_dataset.json', 'r') as f: |
| dataset = json.load(f) |
| |
| # Using Parquet |
| import pandas as pd |
| df = pd.read_parquet('permissive_triton_dataset.parquet') |
| ``` |
