Metadata-Version: 2.5
Name: stackkernels
Version: 0.1.0
Summary: Fast, fused Triton kernels for transformer models — PyTorch and JAX backends.
Project-URL: Homepage, https://github.com/stackformer-labs/stackkernels
License: MIT
License-File: LICENSE
Requires-Python: >=3.9
Requires-Dist: torch<3.0,>=2.3
Requires-Dist: triton>=2.3
Provides-Extra: dev
Requires-Dist: pytest; extra == 'dev'
Requires-Dist: pytest-benchmark; extra == 'dev'
Provides-Extra: jax
Requires-Dist: jax-triton; extra == 'jax'
Requires-Dist: jax>=0.4; extra == 'jax'
Description-Content-Type: text/markdown

# stackkernels

Fast, fused Triton kernels for transformer models — built as the kernel backbone for [Stackformer](#).

Supports **PyTorch** and **JAX**, with a shared, framework-agnostic Triton core.

## Status
🚧 Early development. Build order: RMSNorm → LayerNorm → Flash Attention → Dropout → Activations (SiLU/GELU/SwiGLU) → Cross-Entropy → RoPE.

## Install
```bash
pip install stackkernels
```

## Quick start
```python
from stackkernels.torch import RMSNorm
```

## License
MIT