code: def test_when_known_covariates_present_then_they_are_passed_to_dataset(
      model_class, df_with_covariates
  ):
      df, metadata = df_with_covariates
      model = model_class(
          hyperparameters=DUMMY_HYPERPARAMETERS,
          metadata=metadata,
          freq=df.freq,
      )
      with mock.patch(
          "autogluon.timeseries.models.gluonts.abstract_gluonts.SimpleGluonTSDataset.__init__"
      ) as patch_dataset:
          try:
              model.fit(train_data=df)
          except TypeError:
              pass
          finally:
              call_kwargs = patch_dataset.call_args[1]
              feat_dynamic_real = call_kwargs["feat_dynamic_real"]
              assert (feat_dynamic_real.dtypes == "float").all()
  
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 11 for calling a global function with example usage: test_when_known_covariates_present_then_they_are_passed_to_dataset(model_class, df_with_covariates) without return types