code: def serialize_to_bundle(self, transformer, path, model_name, serialize_node=True):
          
  
          # Define attributes
          attributes = list()
          attributes.append(('num_features', transformer.n_features_))
          if isinstance(transformer, DecisionTreeClassifier):
              attributes.append(('num_classes', int(transformer.n_classes_)))
  
          inputs = []
          outputs = []
          if serialize_node:
              # define node inputs and outputs
              inputs = [{
                        "name": transformer.input_features,
                        "port": "features"
                      }]
  
              outputs = [{
                        "name": transformer.prediction_column,
                        "port": "prediction"
                      }]
  
          self.serialize(transformer, path, model_name, attributes, inputs, outputs, node=serialize_node)
  
          # Serialize tree.json
          tree_path = "{}/{}.node/tree.json".format(path, model_name)
          if not serialize_node:
              tree_path = "{}/{}/tree.json".format(path, model_name)
          with open(tree_path, 'w') as outfile:
              self.serialize_tree(transformer, transformer.feature_names, outfile)
docs: :type transformer: sklearn.tree.tree.BaseDecisionTree
          :type path: str
          :type model_name: str
          :type serialize_node: bool
          :param transformer:
          :param path:
          :param model_name:
          :return: