class_docstr: Representation of a leaf node of a decision tree.
docstr: Create a leaf node representation.
  
  :param tree_id: ID of the decision tree.
  :param class_label: ID of class to which this leaf node is contributing.
  :param box: A box representing the n_feature-dimensional bounding intervals that reach this leaf node.
  :param value: Prediction value at this leaf node.
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code: def __init__(
      self,
      tree_id: Optional[int],
      class_label: int,
      node_id: Optional[int],
      box: Box,
      value: float,
  ) -> None:
      """
      Create a leaf node representation.
  
      :param tree_id: ID of the decision tree.
      :param class_label: ID of class to which this leaf node is contributing.
      :param box: A box representing the n_feature-dimensional bounding intervals that reach this leaf node.
      :param value: Prediction value at this leaf node.
      """
      self.tree_id = tree_id
      self.class_label = class_label
      self.node_id = node_id
      self.box = box
      self.value = value
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Dict, List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from tqdm.auto import trange
  from art.utils import check_and_transform_label_format
label_desc: Use image node_id 1 to create a new LeafNode object  with example: obj = LeafNode(tree_id, class_label, node_id, box, value)