code: def convert(model, feature_names, target):
      
      if not(_HAS_SKLEARN):
          raise RuntimeError('scikit-learn not found. scikit-learn conversion API is disabled.')
  
      _sklearn_util.check_expected_type(model, _tree.DecisionTreeRegressor)
      _sklearn_util.check_fitted(model, lambda m: hasattr(m, 'tree_') and model.tree_ is not None)
      return _MLModel(_convert_tree_ensemble(model, feature_names, target))
docs: Convert a decision tree model to protobuf format.
  
      Parameters
      ----------
      decision_tree : DecisionTreeRegressor
          A trained scikit-learn tree model.
  
      feature_names: [str]
          Name of the input columns.
  
      target: str
          Name of the output column.
  
      Returns
      -------
      model_spec: An object of type Model_pb.
          Protobuf representation of the model