code: def test_fake_models_list_inputs():
      """Test model with lists as input."""
      for (X, Y, Z), types in generate_data_combinations():
          mitigator = get_instance(fake_mixin=True)
          mitigator.fit(
              X.tolist(), Y.tolist(), sensitive_features=Z.tolist()
          )
  
imports: import sys
  import pytest
  import numpy
  import pandas
  from sklearn.utils import estimator_checks
  from fairlearn.adversarial import AdversarialFairnessClassifier, AdversarialFairnessRegressor
  from fairlearn.adversarial._adversarial_mitigation import _AdversarialFairness
  from fairlearn.adversarial._preprocessor import FloatTransformer
  from fairlearn.adversarial._constants import _TYPE_COMPLIANCE_ERROR
  from .helper import get_instance, generate_data_combinations, cols, Bin2d, Bin1d, Cat, Cont2d, Cont1d, BCE, CCE, MSE, Keyword_CATEGORY, Keyword_BINARY, Keyword_CONTINUOUS, Keyword_CLASSIFICATION, Keyword_AUTO, KeywordToClass
label_desc: Use image node_id 16 for calling a global function with example usage: test_fake_models_list_inputs() without return types