code: def test_when_input_is_pandas_columns(df_vartypes):
      input_features = df_vartypes.columns
      transformer = MockTransformer()
  
      transformer.fit(df_vartypes)
      assert (
          transformer.get_feature_names_out(
              input_features=input_features
          )
          == variables_str
      )
  
      transformer.fit(df_vartypes.to_numpy())
      assert (
          transformer.get_feature_names_out(
              input_features=input_features
          )
          == variables_str
      )
  
imports: import numpy
  import pytest
  from sklearn.exceptions import NotFittedError
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import PolynomialFeatures
  from feature_engine._base_transformers.mixins import GetFeatureNamesOutMixin
  from feature_engine.dataframe_checks import check_X
label_desc: Use image node_id 2 for calling a global function with example usage: test_when_input_is_pandas_columns(df_vartypes) without return types