CyberZHG Keras Gcn Save Abandoned

Graph convolutional layers

Project README

Keras Graph Convolutional Network

Graph convolutional layers.

Install

pip install keras-gcn

Usage

GraphConv

from tensorflow import keras
from keras_gcn import GraphConv


DATA_DIM = 3

data_layer = keras.layers.Input(shape=(None, DATA_DIM))
edge_layer = keras.layers.Input(shape=(None, None))
conv_layer = GraphConv(
    units=32,
    step_num=1,
)([data_layer, edge_layer])

step_num is the maximum distance of two nodes that could be considered as neighbors. If step_num is greater than 1, then the inputs of edges must be 0-1 matrices.

GraphMaxPool & GraphAveragePool

Pooling layers with the step_num argument.

Open Source Agenda is not affiliated with "CyberZHG Keras Gcn" Project. README Source: CyberZHG/keras-gcn
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