gnn 1.1.3

Graph Neural Network Tensorflow implementation

This repo contains a Tensorflow implementation of the Graph Neural Network model.

• Website (including documentation): https://sailab.diism.unisi.it/gnn/index.html

Install

The GNN framework requires the packages tensorflow, numpy, scipy

To install the requirements you can use the following command:

pip install -U -r requirements.txt

Install the latest version of GNN:

pip install gnn

Simple usage example

import gnn.GNN as GNN import Net as n

# Provide your own functions to generate input data inp, arcnode, nodegraph, labels = set_load()

# Create the state transition function, output function, loss function and metrics net = n.Net(input_dim, state_dim, output_dim)

# Create the graph neural network model g = GNN.GNN(net, input_dim, output_dim, state_dim)

#Training

for j in range(0, num_epoch):

g.Train(inp, arcnode, labels, count, nodegraph)

# Validate print(g.Validate(inp_val, arcnode_val, labels_val, count, nodegraph_val))

License

Released under the 3-Clause BSD license (see LICENSE)

Copyright (C) 2004-2019 Matteo Tiezzi Matteo Tiezzi <[e-mail]> Alberto Rossi <[e-mail]>