code: def __init__(
      self, dim, activation=tf.nn.relu, concat=False, **kwargs
  ):
      super(BaseAggregator, self).__init__(**kwargs)
      if concat:
          if dim % 2:
              raise ValueError(
                  "dim must be divided exactly "
                  "by 2 if concat is True."
              )
          dim //= 2
      self.concat = concat
      self.self_layer = layers.Dense(
          dim, activation=activation, use_bias=False
      )
      self.neigh_layer = layers.Dense(
          dim, activation=activation, use_bias=False
      )
  
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 BaseAggregator object from inherited base classes: layers with example: obj = BaseAggregator(dim, activation, concat)