code: def __init__(self, opt):
      super(Conll, self).__init__()
      self.tag_types = [
          "I-PER",
          "O",
          "B-ORG",
          "B-LOC",
          "I-ORG",
          "I-MISC",
          "I-LOC",
          "B-MISC",
      ]
      if args.gpu > -1:
          self.device = torch.device("cuda")
      else:
          self.device = torch.device("cpu")
      self.checkpoint_save_path = "./checkpoints/"
  
      print("finish building model")
      self.opt = opt
      self._build_model()
  
imports: import argparse
  import os
  import torch
  import torch.backends.cudnn
  import torch.multiprocessing
  from graph4nlp.pytorch.data.dataset import SequenceLabelingDataItem
  from graph4nlp.pytorch.inference_wrapper.classifier_inference_wrapper import ClassifierInferenceWrapper
  from graph4nlp.pytorch.modules.config import get_basic_args
  from graph4nlp.pytorch.modules.utils.config_utils import get_yaml_config, update_values
  from graph4nlp.pytorch.modules.utils.generic_utils import to_cuda
  from conll import ConllDataset_inference
  from conlleval import evaluate
  from line_graph_construction import LineBasedGraphConstruction
  from model import Word2tag
label_desc: Use image node_id 1 to create a new Conll object  with example: obj = Conll(opt)