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
pip install stackkernels
Quick start
from stackkernels.torch import RMSNorm
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for stackkernels 0.1.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| stackkernels-0.1.0.tar.gz | 2.4 kB | Without provenance | Details for stackkernels-0.1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| stackkernels-0.1.0-py3-none-any.whl | Python 3 | none | any | Details for stackkernels-0.1.0-py3-none-any.whl |
Total release size: 8.8 kB
Release files / stackkernels-0.1.0.tar.gz
| Download URL | stackkernels-0.1.0.tar.gz |
|---|---|
| Size | 2.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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No |
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twine/7.0.0 CPython/3.12.10
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Release files / stackkernels-0.1.0-py3-none-any.whl
| Download URL | stackkernels-0.1.0-py3-none-any.whl |
|---|---|
| Size | 6.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.10
|
Security for stackkernels 0.1.0
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