class_docstr: Test class for cross-validation tests.
class_docstr_tok: ["Test","class","for","cross-validation","tests","."]
docstr: Clean up after tests.
docstr_tok: ["Clean","up","after","tests","."]
code: def tearDownClass(cls):
      """Clean up after tests."""
      fold_file_path = other_dir / "custom_folds.csv"
      unlink(fold_file_path)
  
      config_dir_obj = config_dir
      cfg_files = [
          config_dir_obj / "test_save_cv_folds.cfg",
          config_dir_obj / "test_save_cv_models.cfg",
          config_dir_obj / "test_custom_cv_seed_classifier.cfg",
          config_dir_obj / "test_custom_cv_seed_regressor.cfg",
          config_dir_obj / "test_folds_file.cfg",
          config_dir_obj / "test_folds_file_grid.cfg",
      ]
      for cfg_file in cfg_files:
          unlink(cfg_file)
  
      for output_file in itertools.chain(
          output_dir.glob("test_save_cv_folds*"),
          output_dir.glob("test_int_labels_cv_*"),
          output_dir.glob("test_save_cv_models*"),
          output_dir.glob("test_custom_cv_seed*"),
          output_dir.glob("test_folds_file*"),
      ):
          unlink(output_file)
  
      remove_jsonlines_feature_files(train_dir)
  
imports: import csv
  import itertools
  import json
  import re
  import unittest
  import numpy
  from numpy.testing import assert_almost_equal
  from sklearn.datasets import make_classification
  from sklearn.feature_extraction import FeatureHasher
  from skll.config import load_cv_folds
  from skll.data import FeatureSet
  from skll.experiments import load_featureset, run_configuration
  from skll.learner import Learner
  from skll.utils.testing import compute_expected_folds_for_cv_testing, config_dir, create_jsonlines_feature_files, fill_in_config_paths_for_single_file, other_dir, output_dir, remove_jsonlines_feature_files, train_dir, unlink
label_desc: Use image node_id 2 for calling the TestCrossValidation obj's underlying member method code with example usage: obj.tearDownClass(cls) without return types