fastGAT 0.1.0

A Fast Graph ATtention networks with ALSH.

Fast Graph ATtention neural networks

What's that?

Fast Graph ATtention neural networks(fastGAT) is a new algorithm based on GAT(graph attention networks). We designed our algorithm with AngleLSH(Angle based Local Sensity Hashing), for a faster running speed and a less memory usage. In a word, you can use our algorithm instead of GAT in everywhere with more great effect.

How to install it?

Just use:

pip install fastGAT

How to use it?

A demo for fast run.

you can just use:

import fastGAT.fastGAT as ft

proc=ft.exe()
proc.tra_val()
proc.test()

for simple demo, which will running our method in CORA dataset.

customize your own hyperparameters.

use

from fasGAT.model import fastGAT as mft

blablabla..

customize your own dataset

just try the numpy format matrix , which for example：

adj: the adj matrix
features: feature vector combination of all nodes
labels: label of all nodes

MORE INFORMATION

For more infomation, you might go to here:fastGAT

Does it well?

You can enjoy some images follow for the detail of it.

concat me.

you can send any problem and BUG using the issue in github. Or call me with: [e-mail].