code: def _from_java(cls, java_stage):
          
          featuresCol = java_stage.getFeaturesCol()
          labelCol = java_stage.getLabelCol()
          predictionCol = java_stage.getPredictionCol()
          classifier = JavaParams._from_java(java_stage.getClassifier())
          models = [JavaParams._from_java(model) for model in java_stage.models()]
          py_stage = cls(models=models).setPredictionCol(predictionCol).setLabelCol(labelCol)\
              .setFeaturesCol(featuresCol).setClassifier(classifier)
          py_stage._resetUid(java_stage.uid())
          return py_stage
docs: Given a Java OneVsRestModel, create and return a Python wrapper of it.
          Used for ML persistence.