code: def test_deeplearning_works_as_autoencoder():
      df = h2o.import_file(
          path=pu.locate("smalldata/iris/iris_wheader.csv")
      )
      ae = H2ODeepLearningEstimator(
          autoencoder=True, hidden=[4], seed=1234
      )
      ae.train(x=[0, 1, 2, 3], training_frame=df)
  
imports: import sys, os
  import h2o
  from h2o.estimators import H2ODeepLearningEstimator, H2OAutoEncoderEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_deeplearning_works_as_autoencoder() without return types