code: def test_inverse_transform(self):
      # we do not allow None in these data (but "none" column without any missing value is ok)
      X = th.create_dataset(n_rows=100, has_missing=False)
      X_t = th.create_dataset(n_rows=50, has_missing=False)
      cols = ["underscore", "none", "categorical", "categorical_int"]
  
      for encoder_name in [
          "BaseNEncoder",
          "BinaryEncoder",
          "OneHotEncoder",
          "OrdinalEncoder",
      ]:
          with self.subTest(encoder_name=encoder_name):
              # simple run
              enc = getattr(encoders, encoder_name)(
                  verbose=1, cols=cols
              )
              enc.fit(X)
              th.verify_inverse_transform(
                  X_t, enc.inverse_transform(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 14 for calling the TestEncoders obj's underlying member method code with example usage: obj.test_inverse_transform() without return types