Graph Neural Network Tensorflow implementation
Project description
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.gnn_utils as gnn_utils import gnn.GNN as 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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