code: def call(self, inputs):
      weights = inputs[:, :1]
      sources, targets = tf.split(inputs[:, 1:], 2, axis=1)
      return tf.math.reduce_sum(
          lib.pairwise_distance_wrapper(
              sources, targets, weights, self._config
          ),
          -1,
      )
  
imports: import functools
  from typing import Dict, Optional, Text
  import graph_nets
  import neural_structured_learning.configs
  import neural_structured_learning.keras
  import neural_structured_learning.lib
  import sonnet.v2
  import tensorflow
label_desc: Use image node_id 2 for calling the GraphRegularizationEdgeModel obj's underlying member method code with example usage: obj.call(inputs) and returns: tf