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 jax.

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 frequently, it is recommended 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

Take a look at jupyter notebooks in examples/.

Quick guide

craynn is designed for rapidly defining networks of all sorts:

from craynn import network, conv, max_pool

net = network((None, 1, 28, 28))(
  conv(16), conv(24), max_pool(),
  conv(16), conv(24), max_pool(),
  conv(16), conv(24), max_pool(),
)