Metadata-Version: 2.1
Name: complex-attn
Version: 0.0.2
Summary: ct - Pytorch
Home-page: https://github.com/kyegomez/ct
License: MIT
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering
Author: Kye Gomez
Author-email: kye@apac.ai
Requires-Python: >=3.6,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: einops
Requires-Dist: torch
Project-URL: Repository, https://github.com/kyegomez/ct
Description-Content-Type: text/markdown

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# Complex Transformer
The open source implementation of the attention and transformer from "Building Blocks for a Complex-Valued Transformer Architecture" where they propose an an attention mechanism for complex valued signals or images such as MRI and remote sensing.

They present:
- complex valued scaled dot product attention
- complex valued layer normalization
- results show improved robustness to overfitting while maintaing performance wbhen compared to real valued transformer

## Install
`pip install ct`

# License
MIT




