code: def test_svc_pickle_nofit(
      tmpdir, datatype, nrows, ncols, n_info, params
  ):
      def create_mod():
          X_train, y_train, X_test = make_classification_dataset(
              datatype, nrows, ncols, n_info, n_classes=2
          )
          model = cuml.svm.SVC(**params)
          return model, [X_train, y_train, X_test]
  
      def assert_model(pickled_model, X):
          state = pickled_model.__dict__
  
          assert state["_fit_status_"] == -1
  
          pickled_model.fit(X[0], X[1])
          state = pickled_model.__dict__
  
          assert state["_fit_status_"] == 0
  
      pickle_save_load(tmpdir, create_mod, assert_model)
  
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 25 for calling a global function with example usage: test_svc_pickle_nofit(tmpdir, datatype, nrows, ncols, n_info, params) and returns: model,  list