class_docstr: Class for importing XGBoost models.
docstr: Get the decision trees.
  
  :return: A list of decision trees.
docstr_tok: ["Get","the","decision","trees",".",":","return",":","A","list","of","decision","trees","."]
code: def get_trees(self) -> List["Tree"]:
      """
      Get the decision trees.
  
      :return: A list of decision trees.
      """
      from art.metrics.verification_decisions_trees import Box, Tree
  
      booster_dump = self._model.get_booster().get_dump(
          dump_format="json"
      )
      trees = []
  
      for i_tree, tree_dump in enumerate(booster_dump):
          box = Box()
  
          if self._model.n_classes_ == 2:
              class_label = -1
          else:
              class_label = i_tree % self._model.n_classes_
  
          tree_json = json.loads(tree_dump)
          trees.append(
              Tree(
                  class_id=class_label,
                  leaf_nodes=self._get_leaf_nodes(
                      tree_json, i_tree, class_label, box
                  ),
              )
          )
  
      return trees
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  from copy import deepcopy
  import json
  import logging
  import os
  import pickle
  from typing import List, Optional, Union, Tuple, TYPE_CHECKING
  import numpy
  from art.estimators.classification.classifier import ClassifierDecisionTree
  from art.utils import to_categorical
  from art import config
label_desc: Use image node_id 9 for calling the XGBoostClassifier obj's underlying member method code with example usage: obj.get_trees() and returns: trees