code: def _build_model(self):
      self.model = SumModel.load_checkpoint(
          self.stopper.save_model_path
      )
      self.model.vocab_model = self.model.vocab
  
      self.inference_tool = GeneratorInferenceWrapper(
          cfg=self.config,
          model=self.model,
          beam_size=3,
          lower_case=True,
          tokenizer=word_tokenize,
      )
  
imports: import argparse
  import os
  import numpy
  import torch
  import torch.backends.cudnn
  from nltk.tokenize import word_tokenize
  from graph4nlp.pytorch.inference_wrapper.generator_inference_wrapper import GeneratorInferenceWrapper
  from graph4nlp.pytorch.modules.config import get_basic_args
  from graph4nlp.pytorch.modules.utils import constants
  from graph4nlp.pytorch.modules.utils.config_utils import get_yaml_config, update_values
  from graph4nlp.pytorch.modules.utils.generic_utils import EarlyStopping, to_cuda
  from main import SumModel
label_desc: Use image node_id 2 for calling the ModelHandler obj's underlying member method code with example usage: obj._build_model() without return types