gnn 1.0.5

Graph Neural Network Tensorflow implementation

Graph Neural Network Model

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

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 [e-mail] Alberto Rossi [e-mail]