docstr: Compute the second part (distance from x1) of the loss function.
docstr_tok: ["Compute","the","second","part","(","distance","from","x1",")","of","the","loss","function","."]
code: def compute_proximity_loss(self):
      """Compute the second part (distance from x1) of the loss function."""
      proximity_loss = 0.0
      for i in range(self.total_CFs):
          proximity_loss = tf.add(
              proximity_loss,
              self.compute_dist(self.cfs_frozen[i], self.x1),
          )
      return tf.divide(
          proximity_loss,
          tf.cast(
              tf.multiply(len(self.minx[0]), self.total_CFs),
              dtype=tf.float32,
          ),
      )
  
imports: import collections
  import copy
  import random
  import timeit
  import numpy
  import tensorflow
  from dice_ml import diverse_counterfactuals
  from dice_ml.counterfactual_explanations import CounterfactualExplanations
  from dice_ml.explainer_interfaces.explainer_base import ExplainerBase
label_desc: Use image node_id 8 for calling the DiceTensorFlow1 obj's underlying member method code with example usage: obj.compute_proximity_loss() and returns: tf