code: def check_splits(X, y, groups, cv_args, expected_results):
      cv = GroupTimeSeriesSplit(**cv_args)
      results = list(cv.split(X, y, groups))
  
      assert len(results) == len(expected_results)
  
      for split, expected_split in zip(results, expected_results):
          assert np.array_equal(split[0], expected_split[0])
          assert np.array_equal(split[1], expected_split[1])
  
      return cv
  
imports: import numpy
  import pytest
  from sklearn.dummy import DummyClassifier
  from sklearn.model_selection import cross_val_score
  from mlxtend.evaluate import GroupTimeSeriesSplit
label_desc: Use image node_id 9 for calling a global function with example usage: check_splits(X, y, groups, cv_args, expected_results) and returns: cv