Grenade

Documentation

This is an empty module which simply re-exports public definitions for machine learning with Grenade.

Exported modules

The core types and runners for Grenade.

module Grenade.Core

The neural network layer zoo

module Grenade.Layers

Overview of the library

Grenade is a purely functional deep learning library.

It provides an expressive type level API for the construction of complex neural network architectures. Backing this API is and implementation written using BLAS and LAPACK, mostly provided by the hmatrix library.

Example usage

A few examples are provided at https://github.com/HuwCampbell/grenade under the examples folder.

The starting place is to write your neural network type and a function to create a random layer of that type. The following is a simple example which runs a logistic regression.

type MyNet = Network '[ FullyConnected 10 1, Logit ] '[ 'D1 10, 'D1 1, 'D1 1 ]

randomMyNet :: MonadRandom MyNet
randomMyNet = randomNetwork

The function randomMyNet witnesses the CreatableNetwork constraint of the neural network, and in doing so, ensures the network can be built, and hence, that the architecture is sound.