Update molgan.py

    List

        List of shapes used as an input for distriminator.

    """

    return [(self.vertices, self.vertices, self.edges),

            (self.vertices, self.nodes), (self.vertices,

                                          self.vertices), (self.vertices)]

    return [

        (self.vertices, self.vertices, self.edges),

        (self.vertices, self.nodes),

    ]

  def create_generator(self) -> keras.Model:

    """

        shape=(self.vertices, self.vertices, self.edges))

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

    # this is actually not used, added due to generator

    # output/discriminator input mismatch

    # will be removed in the future release

    e_argmax = layers.Input(shape=(self.vertices, self.vertices))

    n_argmax = layers.Input(shape=(self.vertices))

    graph = MolGANEncoderLayer(

        units=[(128, 64), 128],

        dropout_rate=self.dropout_rate,

    output = layers.Dense(units=1)(dense)

    return keras.Model(

        inputs=[adjacency_tensor, node_tensor, e_argmax, n_argmax],

        outputs=[output])

        inputs=[

            adjacency_tensor,

            node_tensor,

        ], outputs=[output])

  def predict_gan_generator(self,

                            batch_size: int = 1,