code: def test_when_models_saved_then_gluonts_predictors_can_be_loaded(
      model_class, temp_model_path
  ):
      model = model_class(
          path=temp_model_path,
          freq="H",
          quantile_levels=[0.1, 0.9],
          hyperparameters=DUMMY_HYPERPARAMETERS,
      )
      model.fit(
          train_data=DUMMY_TS_DATAFRAME,
      )
      model.save()
  
      loaded_model = model.__class__.load(path=model.path)
  
      assert (
          model._get_estimator_class()
          is loaded_model._get_estimator_class()
      )
      assert (
          loaded_model.gts_predictor.to(model.gts_predictor.device)
          == model.gts_predictor
      )
  
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 4 for calling a global function with example usage: test_when_models_saved_then_gluonts_predictors_can_be_loaded(model_class, temp_model_path) without return types