code: def module_extensions():
      class H2OAutoEncoderEstimator(H2ODeepLearningEstimator):
          """
          :examples:
  
          >>> import h2o as ml
          >>> from h2o.estimators.deeplearning import H2OAutoEncoderEstimator
          >>> ml.init()
          >>> rows = [[1,2,3,4,0]*50, [2,1,2,4,1]*50, [2,1,4,2,1]*50, [0,1,2,34,1]*50, [2,3,4,1,0]*50]
          >>> fr = ml.H2OFrame(rows)
          >>> fr[4] = fr[4].asfactor()
          >>> model = H2OAutoEncoderEstimator()
          >>> model.train(x=list(range(4)), training_frame=fr)
          """
  
          supervised_learning = False
  
          def __init__(self, **kwargs):
              super(H2OAutoEncoderEstimator, self).__init__(**kwargs)
              self.autoencoder = True
  
label_desc: Use image node_id 1 for calling a global function with example usage: module_extensions() without return types