code: def test_get_feature_names_out_from_pipeline(
      df_datetime, df_datetime_transformed
  ):
      transformer = Pipeline([("transformer", DatetimeFeatures())])
      X = transformer.fit_transform(df_datetime)
      assert list(X.columns) == transformer.get_feature_names_out()
      assert list(X.columns) == transformer.get_feature_names_out(
          df_datetime.columns
      )
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from sklearn.pipeline import Pipeline
  from feature_engine.datetime import DatetimeFeatures
  from feature_engine.datetime._datetime_constants import FEATURES_DEFAULT, FEATURES_SUFFIXES, FEATURES_SUPPORTED
label_desc: Use image node_id 24 for calling a global function with example usage: test_get_feature_names_out_from_pipeline(df_datetime, df_datetime_transformed) without return types