code: def test_rotbaum_smoke(datasets):
      dataset_train, dataset_test = datasets
      hps = {
          "freq": "D",
          "prediction_length": 3,
          "context_length": 3,
      }
      estimator = TreeEstimator.from_inputs(dataset_train, **hps)
  
      predictor = estimator.train(dataset_train)
      forecasts = list(predictor.predict(dataset_test))
      assert len(forecasts) == len(dataset_test)
  
imports: import pytest
  import numpy
  from gluonts.ext.rotbaum import TreeEstimator, TreePredictor
  from gluonts.testutil.dummy_datasets import make_dummy_datasets_with_features
  from gluonts.dataset.common import ListDataset
label_desc: Use image node_id 1 for calling a global function with example usage: test_rotbaum_smoke(datasets) without return types