code: def test_cols(self):
      # Test cols argument with different data types, which are array-like or scalars
      cols_list = ["extra", "invariant"]
      cols_types = [
          cols_list,
          pd.Series(cols_list),
          np.array(cols_list),
          "extra",
          set(cols_list),
          ("extra", "invariant"),
          pd.Categorical(cols_list, categories=cols_list),
      ]
  
      for encoder_name in encoders.__all__:
          for cols in cols_types:
              with self.subTest(encoder_name=encoder_name, cols=cols):
                  enc = getattr(encoders, encoder_name)(cols=cols)
                  enc.fit(X, y)
                  enc.transform(X_t)
  
imports: import warnings
  from datetime import timedelta
  import numpy
  from numpy.testing import assert_array_equal
  import pandas
  import sklearn
  import tests.helpers
  from sklearn.utils.estimator_checks import check_transformer_general, check_transformers_unfitted, check_n_features_in
  from sklearn.compose import ColumnTransformer
  from unittest import TestCase
  from copy import deepcopy
  import category_encoders
label_desc: Use image node_id 25 for calling the TestEncoders obj's underlying member method code with example usage: obj.test_cols() without return types