Yet another optimization toolkit for jax.
Project description
CrayNN
Yet Another toolkit for Neural Network slightly flavoured by Ultra-High Energy Cosmic Rays.
Philosophy
CrayNN is highly influenced by Lasange:
Simplicity: Be easy to use, easy to understand and easy to extend, to facilitate use in research
Transparency: Do not hide Theano behind abstractions, directly process and return Theano expressions or Python / numpy data types
Modularity: Allow all parts (layers, regularizers, optimizers, ...) to be used independently of Lasagne
Pragmatism: Make common use cases easy, do not overrate uncommon cases
Restraint: Do not obstruct users with features they decide not to use
Focus: "Do one thing and do it well"
Just replace theano with tensorflow.
Installation
via PyPi
pip install craynn
via git
CrayNN can be installed directly from gitlab.com:
pip install git+https://gitlab.com/craynn/craynn.git
however, as repository updates quite often, it is recommend to clone the repository
and install the package in development mode:
git clone git@gitlab.com:craynn/craynn.git
cd craynn/
pip install -e .
Usage
Check out jupyter notebooks in examples/.
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