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
  import torch.optim
  from torch.utils.data import DataLoader
  from graph4nlp.pytorch.data.data import from_batch
  from graph4nlp.pytorch.modules.evaluation.accuracy import Accuracy
  from graph4nlp.pytorch.modules.graph_construction import NodeEmbeddingBasedRefinedGraphConstruction
  from graph4nlp.pytorch.modules.graph_construction.node_embedding_based_graph_construction import NodeEmbeddingBasedGraphConstruction
  from graph4nlp.pytorch.modules.utils.generic_utils import to_cuda
  from conll import ConllDataset
  from conlleval import evaluate
  from dependency_graph_construction_without_tokenize import DependencyBasedGraphConstruction_without_tokenizer
  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