docstr: For encoder-decoder
docstr_tok: ["For","encoder-decoder"]
code: def _build_model(self):
      """For encoder-decoder"""
      self.model = Graph2Tree.load_checkpoint(
          self.opt["checkpoint_save_path"], "best.pt"
      ).to(self.device)
  
file_path: graph4nlp/examples/pytorch/math_word_problem/mawps/src/inference_advance.py
imports: import copy
  import random
  import time
  import warnings
  import numpy
  import torch
  from torch.utils.data import DataLoader
  from graph4nlp.pytorch.datasets.mawps import MawpsDatasetForTree
  from graph4nlp.pytorch.models.graph2tree import Graph2Tree
  from evaluation import SolutionMatch
label_desc: Use image node_id 3 for calling the Mawps obj's underlying member method code with example usage: obj._build_model() without return types