code: def df_with_covariates():
      known_covariates_names = [
          col
          for col in DATAFRAME_WITH_COVARIATES.columns
          if col != "target"
      ]
      feature_generator = TimeSeriesFeatureGenerator(
          target="target", known_covariates_names=known_covariates_names
      )
      df = DATAFRAME_WITH_COVARIATES.copy(deep=False)
      df = feature_generator.fit_transform(df)
      return df, feature_generator.covariate_metadata
  
imports: from unittest import mock
  import numpy
  import pytest
  from gluonts.model.predictor import Predictor
  from autogluon.timeseries.models.gluonts import DeepARModel, DLinearModel, PatchTSTModel, SimpleFeedForwardModel, TemporalFusionTransformerModel, WaveNetModel
  from autogluon.timeseries.utils.features import TimeSeriesFeatureGenerator
  from ..common import DATAFRAME_WITH_COVARIATES, DATAFRAME_WITH_STATIC, DUMMY_TS_DATAFRAME
label_desc: Use image node_id 6 for calling a global function with example usage: df_with_covariates() and returns: df,  feature_generator