code: def test_given_duplicate_static_features_then_generator_can_fit_transform():
      feat_generator = TimeSeriesFeatureGenerator(
          target="target", known_covariates_names=[]
      )
      data = DATAFRAME_WITH_STATIC.copy()
      data.static_features["feat5"] = data.static_features["feat1"]
      feat_generator.fit(data)
      out = feat_generator.transform(data)
      assert isinstance(out.static_features, pd.DataFrame)
  
imports: import numpy
  import pandas
  import pytest
  from autogluon.timeseries.utils.features import TimeSeriesFeatureGenerator
  from .common import DATAFRAME_WITH_STATIC, get_data_frame_with_variable_lengths
label_desc: Use image node_id 2 for calling a global function with example usage: test_given_duplicate_static_features_then_generator_can_fit_transform() without return types