code: def validate_arguments(args):
      if args.num_pss < 1:
          print(
              "Value error: must have ore than one parameter servers."
          )
          exit(1)
  
      if not GPU_IDS:
          num_cpus = multiprocessing.cpu_count()
          if args.cpu_trainers > num_cpus:
              print(
                  "Value error: there are %s available CPUs but you are requiring %s."
                  % (num_cpus, args.cpu_trainers)
              )
              exit(1)
  
      if not os.path.isfile(args.file):
          print("Value error: model trainning file does not exist")
          exit(1)
  
file_path: TensorLayer/tensorlayer/cli/train.py
imports: import argparse
  import json
  import multiprocessing
  import os
  import platform
  import re
  import subprocess
  import sys
label_desc: Use image node_id 4 for calling a global function with example usage: validate_arguments(args) without return types