code: def test_inverse_e_plus_user_passes_var_list(df_vartypes):
      # test case 7: inverse log, user passes variables
      transformer = LogTransformer(variables="Age")
      Xt = transformer.fit_transform(df_vartypes)
      X = transformer.inverse_transform(Xt)
  
      # convert floats to int
      X["Age"] = X["Age"].round().astype("int64")
  
      # test init params
      assert transformer.base == "e"
      assert transformer.variables == "Age"
      # test fit attr
      assert transformer.variables_ == ["Age"]
      assert transformer.n_features_in_ == 5
      # test transform output
      pd.testing.assert_frame_equal(X, df_vartypes)
  
file_path: feature_engine/tests/test_transformation/test_log_transformer.py
imports: import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from feature_engine.transformation import LogTransformer
label_desc: Use image node_id 8 for calling a global function with example usage: test_inverse_e_plus_user_passes_var_list(df_vartypes) without return types