code: def set_seed(args):
      random.seed(args.seed)
      np.random.seed(args.seed)
      torch.manual_seed(args.seed)
      if args.n_gpu > 0:
          torch.cuda.manual_seed_all(args.seed)
  
imports: import argparse
  import glob
  import logging
  import os
  import sys
  import json
  import random
  import numpy
  import torch
  import hydra
  from hydra import utils
  from omegaconf import OmegaConf, open_dict
  from seqeval.metrics import f1_score, precision_score, recall_score
  from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
  from torch.utils.data.distributed import DistributedSampler
  from tqdm import tqdm, trange
  from transformers import WEIGHTS_NAME, AdamW, BertConfig, BertTokenizer, get_linear_schedule_with_warmup
  from deepke.event_extraction.standard.bertcrf.processor_ee import convert_examples_to_features, PROCESSORS
  from deepke.event_extraction.standard.bertcrf.bert_crf import *
label_desc: Use image node_id 1 for calling a global function with example usage: set_seed(args) without return types