| Name | gnnnas JSON |
| Version |
0.0.2
JSON |
| download |
| home_page | |
| Summary | Library to help write symbolic programs to generate expressive message passing neural networks. |
| upload_time | 2023-10-19 18:55:21 |
| maintainer | |
| docs_url | None |
| author | Your Name |
| requires_python | >=3.10,<3.13 |
| license | MIT |
| keywords |
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| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<h1 align="center">
<br>
<img src="https://github.com/akhilpandey95/gnnNAS/blob/main/images/gnnnas-logo.png?raw=true" width="400" height="400" alt="gnnnas logo"/>
<br>
</h1>
<h2 align="center">Library to write symbolic programs to generate expressive message passing neural networks</h2>
<h1 align="center"><a href="https://akhilpandey95.github.io/gnnNAS/">kgforge Documentation</h1>
<p align="center">
<a alt="Tests" href="https://github.com/akhilpandey95/gnnNAS/actions/workflows/publish-to-pypi.yml/badge.svg">
<img src="https://github.com/akhilpandey95/kgforge/actions/workflows/publish-to-pypi.yml/badge.svg?branch=main">
</a>
<img alt="Code Style" src="https://img.shields.io/badge/ code%20style-black-000000.svg" />
<a href="https://www.python.org/downloads/release/python-390/">
</a>
<a href="https://pypi.org/project/gnnNAS" target="_blank">
<img src="https://img.shields.io/badge/python-3.10-blue.svg" alt="Supported Python versions">
</a>
<a href="https://img.shields.io/pypi/dw/gnnNAS" target="_blank">
<img src="https://img.shields.io/pypi/dw/gnnNAS" alt="Downloads per week">
</a>
<a href="https://img.shields.io/badge/License-MIT-yellow.svg" target="_blank">
<img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License">
</a>
<a href="https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square" target="_blank">
<img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square" alt="Contribute">
</a>
</p>
<p align="center">
<a href="#what-is-it">What is it?</a> •
<a href="#features">Features</a> •
<a href="#installation">Installation</a> •
<a href="#usage">Usage</a> •
<a href="#contributing">Contributing</a>
</p>
## What is it?
`kgforge` is a library which automates the generation of knowledge graphs from scholarly text.
## Features:
- **TODO**: TODO: Description.
## Installation:
### Poetry
```bash
poetry add kgforge
```
### Pip
```bash
pip install kgforge
```
Setup your local environment:
Any necessary environment variables description:
```shell
export SAMPLE_ENV_VARIABLE=${VALUE}
```
## Usage
Now that `kgforge` is installed, you're ready to start using it!
It's time to point you to the official [Documentation Website](https://akhilpandey95.github.io/gnnNAS/) for more information on how to use `kgforge`
## Contributing
If you'd like to contribute, be sure to check out our [contributing guide](./CONTRIBUTING.md)! If you'd like to work on any outstanding items, check out the `roadmap` section in the docs and get started :smiley:
Thanks goes to these incredible people.
<a href="https://github.com/akhilpandey95/gnnNAS/graphs/contributors">
<img style="border-radius: 50%" src="https://contrib.rocks/image?repo=akhilpandey95/gnnNAS" />
</a>
<a href="https://github.com/akhilpandey95/gnnNAS/graphs/contributors">
<img style="border-radius: 50%" src="https://contrib.rocks/image?repo=harishsiravuri/kgforge" />
</a>
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"description": "<h1 align=\"center\">\n <br>\n <img src=\"https://github.com/akhilpandey95/gnnNAS/blob/main/images/gnnnas-logo.png?raw=true\" width=\"400\" height=\"400\" alt=\"gnnnas logo\"/>\n <br>\n</h1>\n\n<h2 align=\"center\">Library to write symbolic programs to generate expressive message passing neural networks</h2>\n\n<h1 align=\"center\"><a href=\"https://akhilpandey95.github.io/gnnNAS/\">kgforge Documentation</h1>\n\n<p align=\"center\">\n\n <a alt=\"Tests\" href=\"https://github.com/akhilpandey95/gnnNAS/actions/workflows/publish-to-pypi.yml/badge.svg\">\n <img src=\"https://github.com/akhilpandey95/kgforge/actions/workflows/publish-to-pypi.yml/badge.svg?branch=main\">\n </a>\n <img alt=\"Code Style\" src=\"https://img.shields.io/badge/ code%20style-black-000000.svg\" />\n <a href=\"https://www.python.org/downloads/release/python-390/\">\n </a>\n <a href=\"https://pypi.org/project/gnnNAS\" target=\"_blank\">\n <img src=\"https://img.shields.io/badge/python-3.10-blue.svg\" alt=\"Supported Python versions\">\n </a>\n <a href=\"https://img.shields.io/pypi/dw/gnnNAS\" target=\"_blank\">\n <img src=\"https://img.shields.io/pypi/dw/gnnNAS\" alt=\"Downloads per week\">\n </a>\n <a href=\"https://img.shields.io/badge/License-MIT-yellow.svg\" target=\"_blank\">\n <img src=\"https://img.shields.io/badge/License-MIT-yellow.svg\" alt=\"License\">\n </a>\n <a href=\"https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square\" target=\"_blank\">\n <img src=\"https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square\" alt=\"Contribute\">\n </a>\n\n</p>\n\n<p align=\"center\">\n <a href=\"#what-is-it\">What is it?</a> \u2022\n <a href=\"#features\">Features</a> \u2022\n <a href=\"#installation\">Installation</a> \u2022\n <a href=\"#usage\">Usage</a> \u2022\n <a href=\"#contributing\">Contributing</a>\n</p>\n\n## What is it?\n`kgforge` is a library which automates the generation of knowledge graphs from scholarly text.\n\n## Features:\n - **TODO**: TODO: Description.\n\n## Installation:\n\n### Poetry\n\n```bash\npoetry add kgforge\n```\n\n### Pip\n\n```bash\npip install kgforge\n```\n\nSetup your local environment:\n\nAny necessary environment variables description:\n\n\n```shell\nexport SAMPLE_ENV_VARIABLE=${VALUE}\n```\n\n## Usage\n\nNow that `kgforge` is installed, you're ready to start using it!\n\nIt's time to point you to the official [Documentation Website](https://akhilpandey95.github.io/gnnNAS/) for more information on how to use `kgforge`\n\n\n## Contributing\nIf you'd like to contribute, be sure to check out our [contributing guide](./CONTRIBUTING.md)! If you'd like to work on any outstanding items, check out the `roadmap` section in the docs and get started :smiley:\n\nThanks goes to these incredible people.\n\n<a href=\"https://github.com/akhilpandey95/gnnNAS/graphs/contributors\">\n <img style=\"border-radius: 50%\" src=\"https://contrib.rocks/image?repo=akhilpandey95/gnnNAS\" />\n</a>\n<a href=\"https://github.com/akhilpandey95/gnnNAS/graphs/contributors\">\n <img style=\"border-radius: 50%\" src=\"https://contrib.rocks/image?repo=harishsiravuri/kgforge\" />\n</a>",
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