code: def compute_tree_accuracy(
      candidate_list_, reference_list_, form_manager
  ):
      candidate_list = []
      for i in range(len(candidate_list_)):
          candidate_list.append(
              Tree.norm_tree(candidate_list_[i], form_manager).to_list(
                  form_manager
              )
          )
      reference_list = []
      for i in range(len(reference_list_)):
          reference_list.append(
              Tree.norm_tree(reference_list_[i], form_manager).to_list(
                  form_manager
              )
          )
      return compute_accuracy(
          candidate_list, reference_list, form_manager
      )
  
imports: import random
  import time
  import warnings
  import numpy
  import torch
  import torch.nn.functional
  import torch.nn.init
  from torch import nn, optim
  from ....modules.prediction.generation.TreeBasedDecoder import StdTreeDecoder, create_mask
  from ....modules.utils.tree_utils import DataLoader, Tree, to_cuda
label_desc: Use image node_id 7 for calling a global function with example usage: compute_tree_accuracy(candidate_list_, reference_list_, form_manager) and returns: compute_accuracy