code: def test_desired_range(
      self,
      desired_range,
      sample_custom_query_2,
      total_CFs,
      initialization,
  ):
      ans = self.exp.generate_counterfactuals(
          query_instances=sample_custom_query_2,
          total_CFs=total_CFs,
          desired_range=desired_range,
          initialization=initialization,
      )
      for cfs_example in ans.cf_examples_list:
          assert all(
              [desired_range[0]] * total_CFs
              <= cfs_example.final_cfs_df[
                  self.exp.data_interface.outcome_name
              ].values
          )
          assert all(
              cfs_example.final_cfs_df[
                  self.exp.data_interface.outcome_name
              ].values
              <= [desired_range[1]] * total_CFs
          )
  
imports: import pytest
  import sklearn
  from raiutils.exceptions import UserConfigValidationException
  import dice_ml
  from dice_ml.utils import helpers
  from dice_ml.utils.neuralnetworks import MulticlassNetwork
label_desc: Use image node_id 2 for calling the TestDiceGeneticRegressionMethods obj's underlying member method code with example usage: obj.test_desired_range(desired_range, sample_custom_query_2, total_CFs, initialization) without return types