Metadata-Version: 2.4
Name: multiscreen
Version: 0.0.6
Summary: Implementation of MultiScreen
Project-URL: Homepage, https://pypi.org/project/multiscreen/
Project-URL: Repository, https://codeberg.org/lucidrains/multiscreen
Author-email: Phil Wang <lucidrains@gmail.com>
License: MIT License
        
        Copyright (c) 2026 Phil Wang
        
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License-File: LICENSE
Keywords: artificial intelligence,deep learning,non-softmax attention
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Requires-Dist: einops>=0.8.1
Requires-Dist: einx>=0.3.0
Requires-Dist: pope-pytorch
Requires-Dist: torch-einops-utils>=0.0.29
Requires-Dist: torch>=2.5
Provides-Extra: examples
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'
Description-Content-Type: text/markdown

<img src="./multiscreen.png" width="400px"></img>

## MultiScreen

Implementation of Multiscreen proposed by Ken Nakanishi for [Screening is Enough](https://arxiv.org/abs/2604.01178)

Basically it is a non-softmax attention with ReLU squared activation and a normalization on the values

## Citations

```bibtex
@misc{nakanishi2026screening,
    title   = {Screening Is Enough},
    author  = {Ken M. Nakanishi},
    year    = {2026},
    eprint  = {2604.01178},
    archivePrefix = {arXiv},
    primaryClass = {cs.LG},
    url     = {https://arxiv.org/abs/2604.01178},
}
```
