Metadata-Version: 2.2
Name: slangpy
Version: 0.19.5
Summary: Easily call Slang functions and integrate with PyTorch auto diff directly from Python.
Author-email: Chris Cummings <chriscummings@nvidia.com>, Benedikt Bitterli <bbitterli@nvidia.com>, Sai Bangaru <sbangaru@nvidia.com>, Yong He <yhe@nvidia.com>
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: typing_extensions
Requires-Dist: numpy
Requires-Dist: nv-sgl==0.12.4

# SlangPy

SlangPy is a library designed to make calling GPU code written in Slang extremely simple and easy.
It's core objectives are to:
- Make it quick and simple to call Slang functions on the GPU from Python
- Eradicate the boilerplate and bugs associated with writing compute kernels
- Grant easy access to Slang's auto-diff features
- Provide optional PyTorch support out of the box

It is built upon 2 core technologies:
- [Slang shading language](https://shader-slang.com/): A modern, platform agnostic shading language with full auto-diff support.
- [Slang graphics library (SGL)](https://github.com/shader-slang/sgl): A powerful Python extension providing a thin wrapper around the graphics layer.

By bringing these 2 technologies together with a simple and flexible Python library, calling GPU code from Python is as simple and easy as calling a function.

## Documentation

For more detailed information and examples, see [the Documentation here](https://slangpy.shader-slang.org/).

## Installation

As SlangPy is coupled with a specific version of SGL, we recommend the use of a virtual environment,
typically VEnv on Linux or Anaconda on Windows. Whether in a global or virtual environment, basic
installation is:

```
pip install slangpy
```

To download the repo and run locally, checkout either the `main` or `stable` branch, 

```
git clone https://github.com/shader-slang/slangpy.git
git checkout stable
pip install -r ./requirements.txt
pip install .
```

Note that if using the `main` branch, you may need to clone and build the latest revision of SGL rather than the package installed with pip.

To enable PyTorch integration, simply `pip install pytorch` as usual and it will be detected automatically by SlangPy.
