GraphAggregation example

  >>> output = layer_3(hidden_2[2])

  >>> model = Model(inputs=[adjacency_tensor,node_tensor], outputs=[output])

  Example

  --------

  vertices = 9

  nodes = 5

  edges = 5

  units = 128

  layer_1 = GraphConvolutionLayer(units=units,edges=edges)

  layer_2 = GraphConvolutionLayer(units=units,edges=edges)

  layer_3 = GraphAggregationLayer(units=128)

  adjacency_tensor= layers.Input(shape=(vertices, vertices, edges))

  node_tensor = layers.Input(shape=(vertices,nodes))

  hidden_1 = layer_1([adjacency_tensor,node_tensor])

  hidden_2 = layer_2(hidden_1)

  output = layer_3(hidden_2[2])

  model = keras.Model(inputs=[adjacency_tensor,node_tensor], outputs=[output])

  References

  ----------

  .. [1] Nicola De Cao et al. "MolGAN: An implicit generative model