code: def call(self, inputs):
      self_embedding, neigh_embedding, adj = inputs
      adj = _sparse_ones_like(adj)
  
      degree = tf.reshape(tf.sparse_reduce_sum(adj, 1), [-1, 1])
      agg_embedding = tf.sparse_tensor_dense_matmul(
          adj, neigh_embedding
      ) / tf.maximum(degree, 1e-7)
  
      from_self = self.self_layer(self_embedding)
      from_neighs = self.neigh_layer(agg_embedding)
  
      if self.concat:
          return tf.concat([from_self, from_neighs], 1)
      else:
          return tf.add(from_self, from_neighs)
  
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 2 for calling the MeanAggregator obj's underlying member method code with example usage: obj.call(inputs) and returns: tf, tf