code: def convert_split_ijc(input_files, train_csv, dev_csv):
      """
      Randomly splits the given list of input files into a train/dev with 85/15 split
  
      The original datasets only have train & test
      """
      random.seed(1234)
      train_files = []
      dev_files = []
      for filename in input_files:
          if random.random() < 0.85:
              train_files.append(filename)
          else:
              dev_files.append(filename)
  
      if len(train_files) == 0 or len(dev_files) == 0:
          raise RuntimeError(
              "Not enough files to split into train & dev"
          )
  
      convert_ijc(train_files, train_csv)
      convert_ijc(dev_files, dev_csv)
  
imports: import argparse
  import random
  import sys
label_desc: Use image node_id 5 for calling a global function with example usage: convert_split_ijc(input_files, train_csv, dev_csv) without return types