Skip to main content

Graph convolutional layers

Project description

Keras Graph Convolutional Network

Travis Coverage PyPI

Graph convolutional layers.

Install

pip install keras-gcn

Usage

GraphConv

import keras
from keras_gru 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for keras-gcn, version 0.13.0
Filename, size File type Python version Upload date Hashes
Filename, size keras-gcn-0.13.0.tar.gz (5.0 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page