code: def test_tmp_column_name(self):
      binary_cat_example = pd.DataFrame(
          {
              "Trend": ["UP", "UP", "DOWN", "FLAT"],
              "Trend_tmp": ["UP", "UP", "DOWN", "FLAT"],
              "target": [1, 1, 0, 0],
          },
          columns=["Trend", "Trend_tmp", "target"],
      )
      for encoder_name in encoders.__all__:
          enc = getattr(encoders, encoder_name)()
          if not enc._get_tags().get("supervised_encoder"):
              continue
          with self.subTest(encoder_name=encoder_name):
              _ = enc.fit_transform(
                  binary_cat_example, binary_cat_example["target"]
              )
  
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 22 for calling the TestEncoders obj's underlying member method code with example usage: obj.test_tmp_column_name() without return types