code: def _algo_for_estimator_(shortname, cls):
      if shortname == "H2OAutoEncoderEstimator":
          return "autoencoder"
      return cls.algo
  
imports: import inspect
  import sys
  from .adaboost import H2OAdaBoostEstimator
  from .aggregator import H2OAggregatorEstimator
  from .anovaglm import H2OANOVAGLMEstimator
  from .coxph import H2OCoxProportionalHazardsEstimator
  from .decision_tree import H2ODecisionTreeEstimator
  from .deeplearning import H2OAutoEncoderEstimator
  from .deeplearning import H2ODeepLearningEstimator
  from .estimator_base import H2OEstimator
  from .extended_isolation_forest import H2OExtendedIsolationForestEstimator
  from .gam import H2OGeneralizedAdditiveEstimator
  from .gbm import H2OGradientBoostingEstimator
  from .generic import H2OGenericEstimator
  from .glm import H2OGeneralizedLinearEstimator
  from .glrm import H2OGeneralizedLowRankEstimator
  from .infogram import H2OInfogram
  from .isolation_forest import H2OIsolationForestEstimator
  from .isotonicregression import H2OIsotonicRegressionEstimator
  from .kmeans import H2OKMeansEstimator
  from .model_selection import H2OModelSelectionEstimator
  from .naive_bayes import H2ONaiveBayesEstimator
  from .pca import H2OPrincipalComponentAnalysisEstimator
  from .psvm import H2OSupportVectorMachineEstimator
  from .random_forest import H2ORandomForestEstimator
  from .rulefit import H2ORuleFitEstimator
  from .stackedensemble import H2OStackedEnsembleEstimator
  from .svd import H2OSingularValueDecompositionEstimator
  from .targetencoder import H2OTargetEncoderEstimator
  from .uplift_random_forest import H2OUpliftRandomForestEstimator
  from .word2vec import H2OWord2vecEstimator
  from .xgboost import H2OXGBoostEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: _algo_for_estimator_(shortname, cls) and returns: cls, str