code: def test_model_kw_error_torch():
      """Test kw error."""
      (X, Y, Z) = Bin2d, Bin1d, Bin1d
      other = get_instance(
          torch=True,
          tensorflow=False,
          fake_mixin=False,
          fake_training=True,
      )
  
      with pytest.raises(ValueError):
          mitigator = get_instance(
              torch=False,
              tensorflow=True,
              fake_mixin=False,
              fake_training=True,
              predictor_model=other.predictor_model,
              adversary_model=other.adversary_model,
              backend="torch",
          )
          mitigator.fit(X, Y, sensitive_features=Z)
  
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 11 for calling a global function with example usage: test_model_kw_error_torch() without return types