class_docstr: Single graph attention layer.
class_docstr_tok: ["Single","graph","attention","layer","."]
docstr: Initializes the GraphAttnLayer.
  
  Args:
    output_dim: (int) Output dimension of gat layer
    dropout_rate: (float) Dropout probability
    alpha: (float) LeakyReLU angle of alpha
    **kwargs: Keyword arguments for `tf.keras.layers.Layer`.
docstr_tok: ["Initializes","the","GraphAttnLayer",".","Args",":","output_dim",":","(","int",")","Output","dimension","of","gat","layer","dropout_rate",":","(","float",")","Dropout","probability","alpha",":","(","float",")","LeakyReLU","angle","of","alpha","*","*","kwargs",":","Keyword","arguments","for","`","tf.keras.layers.Layer","`","."]
code: def __init__(self, output_dim, dropout_rate, alpha=0.2, **kwargs):
      """Initializes the GraphAttnLayer.
  
      Args:
        output_dim: (int) Output dimension of gat layer
        dropout_rate: (float) Dropout probability
        alpha: (float) LeakyReLU angle of alpha
        **kwargs: Keyword arguments for `tf.keras.layers.Layer`.
      """
      super(GraphAttnLayer, self).__init__(**kwargs)
      self.output_dim = output_dim
      self.dropout_rate = dropout_rate
      self.alpha = alpha
  
      self.leakyrelu = tf.keras.layers.LeakyReLU(self.alpha)
      self.dropout = tf.keras.layers.Dropout(self.dropout_rate)
  
imports: import tensorflow
label_desc: Use image node_id 1 to create a new GraphAttnLayer object from inherited base classes: tf.keras.layers with example: obj = GraphAttnLayer(output_dim, dropout_rate, alpha)