code: def test_mqcnn_covariate_smoke_test(
      use_past_feat_dynamic_real,
      use_feat_dynamic_real,
      add_time_feature,
      add_age_feature,
      enable_encoder_dynamic_feature,
      enable_decoder_dynamic_feature,
      hybridize,
      quantiles,
      distr_output,
      is_iqf,
  ):
      hps = {
          "seed": 42,
          "freq": "Y",
          "context_length": 5,
          "prediction_length": 3,
          "quantiles": quantiles,
          "distr_output": distr_output,
          "epochs": 1,
          "num_batches_per_epoch": 1,
          "use_past_feat_dynamic_real": use_past_feat_dynamic_real,
          "use_feat_dynamic_real": use_feat_dynamic_real,
          "add_time_feature": add_time_feature,
          "add_age_feature": add_age_feature,
          "enable_encoder_dynamic_feature": enable_encoder_dynamic_feature,
          "enable_decoder_dynamic_feature": enable_decoder_dynamic_feature,
          "hybridize": hybridize,
          "is_iqf": is_iqf,
      }
  
      dataset_train, dataset_test = make_dummy_datasets_with_features(
          cardinality=[3, 10],
          num_feat_dynamic_real=2,
          num_past_feat_dynamic_real=4,
          freq=hps["freq"],
          prediction_length=hps["prediction_length"],
      )
  
      estimator = MQCNNEstimator.from_hyperparameters(**hps)
  
      predictor = estimator.train(dataset_train, num_workers=None)
      forecasts = list(predictor.predict(dataset_test))
      assert len(forecasts) == len(dataset_test)
  
file_path: gluonts/test/mx/model/seq2seq/test_model.py
imports: import pytest
  from gluonts.mx import MQCNNEstimator, MQRNNEstimator
  from gluonts.mx.distribution import GaussianOutput, ISQFOutput
  from gluonts.testutil.dummy_datasets import make_dummy_datasets_with_features
label_desc: Use image node_id 4 for calling a global function with example usage: test_mqcnn_covariate_smoke_test(use_past_feat_dynamic_real, use_feat_dynamic_real, add_time_feature, add_age_feature, enable_encoder_dynamic_feature, enable_decoder_dynamic_feature, hybridize, quantiles, distr_output, is_iqf) without return types