code: def make_transformer(cls, name=None, submodule=None):
      if name is None:
          name = cls.__name__
      return transformer(
          cls,
          name=name,
          module=_register_submodule(submodule),
          custom_params=_get_custom_params(cls),
      )
  
imports: import inspect
  from operator import attrgetter
  import sys
  from sklearn.base import ClassifierMixin, RegressorMixin
  from h2o.utils.mixin import register_submodule
  from ..None import automl
  from ..None import estimators
  from ..None import transforms
  from .wrapper import estimator, params_as_h2o_frames, transformer, H2OConnectionMonitorMixin, H2OEstimatorPredictProbabilitiesSupport, H2OEstimatorScoreSupport, H2OEstimatorTransformSupport
label_desc: Use image node_id 11 for calling a global function with example usage: make_transformer(cls, name, submodule) and returns: transformer