code: def test_unfit_pickle(model_name):
      # Any model xfailed in this test cannot be used for hyperparameter sweeps
      # with dask or sklearn
      if (
          model_name in decomposition_models_xfail.keys()
          or model_name in unfit_pickle_xfail
      ):
          pytest.xfail()
  
      # Pickling should work even if fit has not been called
      mod = all_models[model_name]()
      mod_pickled_bytes = pickle.dumps(mod)
      mod_unpickled = pickle.loads(mod_pickled_bytes)
      assert mod_unpickled is not None
  
imports: from sklearn.model_selection import train_test_split
  from sklearn.manifold import trustworthiness
  from sklearn.datasets import load_iris, make_classification, make_regression
  from sklearn.base import clone
  from cuml.testing.utils import array_equal, unit_param, stress_param, ClassEnumerator, get_classes_from_package, compare_svm, compare_probabilistic_svm
  from cuml.tsa.arima import ARIMA
  import pytest
  import pickle
  import cuml
  from cuml.internals.safe_imports import cpu_only_import, cpu_only_import_from
label_desc: Use image node_id 11 for calling a global function with example usage: test_unfit_pickle(model_name) without return types