docstr: Compute weighted distance between two vectors.
docstr_tok: ["Compute","weighted","distance","between","two","vectors","."]
code: def compute_dist(self, x_hat, x1):
      """Compute weighted distance between two vectors."""
      return tf.reduce_sum(
          tf.multiply(
              tf.abs(tf.subtract(x_hat, x1)), self.feature_weights
          )
      )
  
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 7 for calling the DiceTensorFlow1 obj's underlying member method code with example usage: obj.compute_dist(x_hat, x1) and returns: tf