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Graph Neural Network Tensorflow implementation

Project description

Graph Neural Network Model

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

Install

Install the latest version of NetworkX:

$ pip install gnn

For additional details, please see INSTALL.rst.

Simple usage example

    import 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 mtiezzi@diism.unisi.it Alberto Rossi alrossi@unifi.it

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