class_docstr: Single graph isomorphism layer.
class_docstr_tok: ["Single","graph","isomorphism","layer","."]
docstr: Initializes the GraphIsomorphismLayer.
  
  Args:
    mlp_layers: (int) Number of mlp layers
    output_dim: (int) Output dimension of gcn layer
    dropout_rate: (float) Dropout probability
    learn_eps: (bool) Whether to learn the epsilon weighting
    sparse: (bool) sparse: Whether features are sparse
    **kwargs: Keyword arguments for `tf.keras.layers.Layer`.
docstr_tok: ["Initializes","the","GraphIsomorphismLayer",".","Args",":","mlp_layers",":","(","int",")","Number","of","mlp","layers","output_dim",":","(","int",")","Output","dimension","of","gcn","layer","dropout_rate",":","(","float",")","Dropout","probability","learn_eps",":","(","bool",")","Whether","to","learn","the","epsilon","weighting","sparse",":","(","bool",")","sparse",":","Whether","features","are","sparse","*","*","kwargs",":","Keyword","arguments","for","`","tf.keras.layers.Layer","`","."]
code: def __init__(
      self,
      mlp_layers,
      output_dim,
      dropout_rate,
      learn_eps=False,
      sparse=True,
      **kwargs,
  ):
      """Initializes the GraphIsomorphismLayer.
  
      Args:
        mlp_layers: (int) Number of mlp layers
        output_dim: (int) Output dimension of gcn layer
        dropout_rate: (float) Dropout probability
        learn_eps: (bool) Whether to learn the epsilon weighting
        sparse: (bool) sparse: Whether features are sparse
        **kwargs: Keyword arguments for `tf.keras.layers.Layer`.
      """
      super(GraphIsomorphismLayer, self).__init__(**kwargs)
      self.mlp_layers = mlp_layers
      self.output_dim = output_dim
      self.dropout_rate = dropout_rate
      self.learn_eps = learn_eps
      self.sparse = sparse
  
      self.relu = tf.keras.layers.ReLU()
      self.dropout = tf.keras.layers.Dropout(self.dropout_rate)
      self.batch_norm = []
      for _ in range(self.mlp_layers - 1):
          self.batch_norm.append(tf.keras.layers.BatchNormalization())
      self.weight = []
  
imports: import tensorflow
label_desc: Use image node_id 1 to create a new GraphIsomorphismLayer object from inherited base classes: tf.keras.layers with example: obj = GraphIsomorphismLayer(mlp_layers, output_dim, dropout_rate, learn_eps, sparse)