Skip to main content

Graph Neural Network Tensorflow implementation

Project description

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



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.

Simple usage example

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)


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 <>
Alberto Rossi <>

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for gnn, version 1.1.8
Filename, size File type Python version Upload date Hashes
Filename, size gnn-1.1.8-py3-none-any.whl (10.6 kB) File type Wheel Python version py3 Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page