docstr: Compute weighted distance between two vectors.
docstr_tok: ["Compute","weighted","distance","between","two","vectors","."]
code: def compute_sparsity_loss(self, cfs):
      """Compute weighted distance between two vectors."""
      sparsity_loss = np.count_nonzero(cfs - self.x1, axis=1)
      return sparsity_loss / len(self.data_interface.feature_names)
  
imports: import copy
  import random
  import timeit
  import numpy
  import pandas
  from raiutils.exceptions import UserConfigValidationException
  from dice_ml import diverse_counterfactuals
  from dice_ml.constants import ModelTypes
  from dice_ml.explainer_interfaces.explainer_base import ExplainerBase
label_desc: Use image node_id 14 for calling the DiceGenetic obj's underlying member method code with example usage: obj.compute_sparsity_loss(cfs) and returns: unknown