code: def test_inverse_wrong_feature_count(self):
      x1 = [["A", "B", "C"], ["D", "E", "F"], ["G", "H", "I"]]
      x2 = [["A", "B"], ["C", "D"]]
      # @ToDo parametrize
      for encoder_name in {
          "BaseNEncoder",
          "BinaryEncoder",
          "OrdinalEncoder",
          "OneHotEncoder",
      }:
          with self.subTest(encoder_name=encoder_name):
              enc = getattr(encoders, encoder_name)()
              enc.fit(x1)
              self.assertRaises(ValueError, enc.inverse_transform, x2)
  
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 16 for calling the TestEncoders obj's underlying member method code with example usage: obj.test_inverse_wrong_feature_count() without return types