code: def set_seed(args):
      np.random.seed(args.seed)
      torch.manual_seed(args.seed)
      if args.n_gpu > 0:
          torch.cuda.manual_seed_all(args.seed)
  
file_path: H2O/h2o_flexgen/benchmark/xsum/run_xsum_h2o.py
imports: import argparse
  import numpy
  import torch
  import json
  import time
  from tqdm import tqdm
  import copy
  from flexgen.flex_opt import Policy, OptLM, ExecutionEnv, CompressionConfig
  from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
label_desc: Use image node_id 1 for calling a global function with example usage: set_seed(args) without return types