code: def _build_model(self):
      self.model = TextClassifier.load_checkpoint(
          os.path.join(
              self.config["out_dir"],
              self.config.get(
                  "model_ckpt_name", Constants._SAVED_WEIGHTS_FILE
              ),
          )
      ).to(self.config["device"])
  
      self.inference_tool = ClassifierInferenceWrapper(
          cfg=self.config,
          model=self.model,
          label_names=self.model.label_model.le.classes_.tolist(),
          dataset=Text2LabelDataset,
          data_item=Text2LabelDataItem,
          lower_case=True,
          tokenizer=word_tokenize,
      )
  
imports: import argparse
  import os
  from typing import List
  import numpy
  import torch
  import torch.backends.cudnn
  import torch.multiprocessing
  import yaml
  from nltk.tokenize import word_tokenize
  from graph4nlp.pytorch.data.dataset import Text2LabelDataItem, Text2LabelDataset
  from graph4nlp.pytorch.inference_wrapper.classifier_inference_wrapper import ClassifierInferenceWrapper
  from graph4nlp.pytorch.modules.utils import constants
  from .run_text_classifier import TextClassifier
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