class_docstr: Args:
      transform (Tree):
          A :class:`Tree` object.
      tree (nltk.tree.Tree):
          A :class:`nltk.tree.Tree` object.
class_docstr_tok: ["Args",":","transform","(","Tree",")",":","A",":","class",":","`","Tree","`","object",".","tree","(","nltk.tree.Tree",")",":","A",":","class",":","`","nltk.tree.Tree","`","object","."]
code: def __init__(self, transform, tree):
      super().__init__(transform)
  
      # the values contain words, pos tags, raw trees, and spans
      # the tree is first left-binarized before factorized
      # spans are the factorization of tree traversed in pre-order
      self.values = [
          *zip(*tree.pos()),
          tree,
          Tree.factorize(Tree.binarize(tree)[0]),
      ]
  
imports: from collections.abc import Iterable
  import nltk
  from tqdm import tqdm
  from underthesea.utils.sp_parallel import is_master
label_desc: Use image node_id 1 to create a new TreeSentence object from inherited base classes: Sentence with example: obj = TreeSentence(transform, tree)