code: def __init__(
      self, dim, activation=tf.nn.relu, renorm=False, **kwargs
  ):
      super(SingleAttentionAggregator, self).__init__(**kwargs)
      self.dense = layers.Dense(dim, use_bias=False)
      self.self_layer = layers.Dense(1, use_bias=False)
      self.neigh_layer = layers.Dense(1, use_bias=False)
      self.activation = activation
      self.renorm = renorm
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_euler.python.utils import layers
label_desc: Use image node_id 1 to create a new SingleAttentionAggregator object from inherited base classes: layers with example: obj = SingleAttentionAggregator(dim, activation, renorm)