code: def test_zero_cfs_internal(
      self,
      method,
      features_to_vary,
      desired_class,
      desired_range,
      sample_custom_query_2,
      total_CFs,
      permitted_range,
      custom_public_data_interface,
      sklearn_binary_classification_model_interface,
  ):
      if method == "genetic":
          pytest.skip(
              "DiceGenetic explainer does not handle the total counterfactuals as zero"
          )
      exp = dice_ml.Dice(
          custom_public_data_interface,
          sklearn_binary_classification_model_interface,
          method=method,
      )
      features_to_vary = exp.setup(
          features_to_vary, None, sample_custom_query_2, "inverse_mad"
      )
      exp._generate_counterfactuals(
          features_to_vary=features_to_vary,
          query_instance=sample_custom_query_2,
          total_CFs=total_CFs,
          desired_class=desired_class,
          desired_range=desired_range,
          permitted_range=permitted_range,
      )
  
imports: import re
  import numpy
  import pandas
  import pytest
  from rai_test_utils.datasets.tabular import create_housing_data
  from raiutils.exceptions import UserConfigValidationException
  from sklearn.ensemble import RandomForestRegressor
  import dice_ml
  from dice_ml.diverse_counterfactuals import CounterfactualExamples
  from dice_ml.explainer_interfaces.explainer_base import ExplainerBase
  from dice_ml.utils import helpers
  from ..conftest import _load_custom_testing_binary_model
label_desc: Use image node_id 14 for calling the TestExplainerBaseBinaryClassification obj's underlying member method code with example usage: obj.test_zero_cfs_internal(method, features_to_vary, desired_class, desired_range, sample_custom_query_2, total_CFs, permitted_range, custom_public_data_interface, sklearn_binary_classification_model_interface) without return types