code: def _make_tree(self, node_id, et, criterion, depth=0):
      # traverses _tree.Tree recursively, builds intermediate
      # "_reingold_tilford.Tree" object
      name = self.node_to_str(et, node_id, criterion=criterion)
      if et.children_left[node_id] != _tree.TREE_LEAF and (
          self.max_depth is None or depth <= self.max_depth
      ):
          children = [
              self._make_tree(
                  et.children_left[node_id],
                  et,
                  criterion,
                  depth=depth + 1,
              ),
              self._make_tree(
                  et.children_right[node_id],
                  et,
                  criterion,
                  depth=depth + 1,
              ),
          ]
      else:
          return Tree(name, node_id)
      return Tree(name, node_id, *children)
  
imports: from collections.abc import Iterable
  from io import StringIO
  from numbers import Integral
  import numpy
  from ..base import is_classifier
  from ..utils._param_validation import HasMethods, Interval, StrOptions, validate_params
  from ..utils.validation import check_array, check_is_fitted
  from .None import DecisionTreeClassifier, DecisionTreeRegressor, _criterion, _tree
  from ._reingold_tilford import Tree, buchheim
label_desc: Use image node_id 2 for calling the _MPLTreeExporter obj's underlying member method code with example usage: obj._make_tree(node_id, et, criterion, depth) and returns: Tree, Tree