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Graph Neural Network Tensorflow implementation

Project description

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

Install

Requirements

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)

#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.txt):

Copyright (C) 2004-2019 Matteo Tiezzi
Matteo Tiezzi <mtiezzi@diism.unisi.it>
Alberto Rossi <alrossi@unifi.it>

Project details


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