code: def test_smoke_automl():
      nmodels = 20  # enough models to run every step (all base models, all grids, all SEs...)
  
      ds = import_dataset()
      aml = H2OAutoML(
          project_name="py_aml_smoke",
          max_models=nmodels,
          nfolds=3,
          stopping_tolerance=0.5,
          stopping_rounds=2,
          seed=42,
          verbosity="debug",
      )
      model = aml.train(y=ds.target, training_frame=ds.train)
  
      assert isinstance(model, ModelBase)
      lb = get_leaderboard(aml, ["algos", "provider", "step", "group"])
      print(lb)
      assert lb.nrows > nmodels
  
imports: import os
  import sys
  from h2o.automl import H2OAutoML, get_leaderboard
  from h2o.model import ModelBase
  from tests import pyunit_utils
  from _automl_utils import import_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: test_smoke_automl() without return types