Graph Neural Network Tensorflow implementation
Project description
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
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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
gnn-1.0.3.tar.gz
(7.1 kB
view details)
File details
Details for the file gnn-1.0.3.tar.gz
.
File metadata
- Download URL: gnn-1.0.3.tar.gz
- Upload date:
- Size: 7.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.5.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c8b34a41f6e93253f4c73f0511097c214659f757891681a5db47ab70bdc03bad |
|
MD5 | e5e8c18c7143225a18b37f2ec3ab4b5b |
|
BLAKE2b-256 | 28ba211b76a8384d3107acbcca81bd74c0de71afaac9d957263a85ec45c77071 |