This repo contains a Tensorflow implementation of the Graph Neural Network model.
- Website (including documentation): https://mtiezzi.github.io/gnn_site/
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
For additional details, please see Install.
import gnn.GNN as GNN
import gnn.gnn_utils
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))
Released under the 3-Clause BSD license (see LICENSE.txt):
Copyright (C) 2004-2019 Matteo Tiezzi Matteo Tiezzi <mtiezzi@diism.unisi.it> Alberto Rossi <alrossi@unifi.it>