Metadata-Version: 2.1
Name: keras-gcn
Version: 0.14.0
Summary: Graph convolutional layers
Home-page: https://github.com/CyberZHG/keras-gcn
Author: CyberZHG
Author-email: CyberZHG@users.noreply.github.com
License: MIT
Description: # Keras Graph Convolutional Network
        
        [![Travis](https://travis-ci.org/CyberZHG/keras-gcn.svg)](https://travis-ci.org/CyberZHG/keras-gcn)
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        [![PyPI](https://img.shields.io/pypi/pyversions/keras-gcn.svg)](https://pypi.org/project/keras-gcn/)
        
        Graph convolutional layers.
        
        ## Install
        
        ```bash
        pip install keras-gcn
        ```
        
        ## Usage
        
        ### `GraphConv`
        
        ![](https://user-images.githubusercontent.com/853842/46645052-88d54f00-cbb5-11e8-9acb-70f4ae5ec654.png)
        
        ```python
        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.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
