code: def main():
      dataset = get_dataset("exchange_rate", regenerate=False)
  
      estimator = COPDeepAREstimator(
          freq=dataset.metadata.freq,
          prediction_length=dataset.metadata.prediction_length,
          base_estimator_name="DeepAREstimatorForCOP",
          base_estimator_hps={},
          trainer=Trainer(
              epochs=100,
              hybridize=False,
          ),
      )
  
      predictor = estimator.train(dataset.train)
  
      results = evaluate_predictor(
          predictor=predictor,
          test_dataset=dataset.test,
          evaluate_all_levels=EVALUATE_ALL_LEVELS,
          freq=dataset.metadata.freq,
      )
  
      print(results)
  
imports: from gluonts.dataset.repository.datasets import get_dataset
  from gluonts.mx.trainer import Trainer
  from gluonts.nursery.temporal_hierarchical_forecasting.model.cop_deepar import COPDeepAREstimator
  from gluonts.nursery.temporal_hierarchical_forecasting.eval.evaluation import evaluate_predictor
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types