code: def convert(model, input_name, output_features):
      
      if not(HAS_SKLEARN):
          raise RuntimeError('scikit-learn not found. scikit-learn conversion API is disabled.')
  
      _sklearn_util.check_expected_type(model, _tree.DecisionTreeClassifier)
      _sklearn_util.check_fitted(model, lambda m: hasattr(m, 'tree_') and model.tree_ is not None)
  
      return _MLModel(convert_tree_ensemble(model, input_name, output_features,
              mode = 'classifier',
              class_labels = model.classes_))
docs: Convert a decision tree model to protobuf format.
  
      Parameters
      ----------
      decision_tree : DecisionTreeClassifier
          A trained scikit-learn tree model.
  
      input_name: str
          Name of the input columns.
  
      output_name: str
          Name of the output columns.
  
      Returns
      -------
      model_spec: An object of type Model_pb.
          Protobuf representation of the model