code: def logits2tag(logits):
      _, pred = torch.max(logits, dim=-1)
      # print(pred.size())
      return pred
  
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 3 for calling a global function with example usage: logits2tag(logits) and returns: pred