code: def convert_fire_2013(
      input_path, train_csv_file, dev_csv_file, test_csv_file
  ):
      random.seed(1234)
  
      filenames = glob.glob(os.path.join(input_path, "*"))
  
      # won't be numerically sorted... shouldn't matter
      filenames = sorted(filenames)
      random.shuffle(filenames)
  
      sentences = read_fileset(filenames)
      random.shuffle(sentences)
  
      train_cutoff = int(0.8 * len(sentences))
      dev_cutoff = int(0.9 * len(sentences))
  
      train_sentences = sentences[:train_cutoff]
      dev_sentences = sentences[train_cutoff:dev_cutoff]
      test_sentences = sentences[dev_cutoff:]
  
      random.shuffle(train_sentences)
      random.shuffle(dev_sentences)
      random.shuffle(test_sentences)
  
      assert len(train_sentences) > 0
      assert len(dev_sentences) > 0
      assert len(test_sentences) > 0
  
      write_fileset(train_csv_file, train_sentences)
      write_fileset(dev_csv_file, dev_sentences)
      write_fileset(test_csv_file, test_sentences)
  
imports: import argparse
  import glob
  import os
  import random
label_desc: Use image node_id 4 for calling a global function with example usage: convert_fire_2013(input_path, train_csv_file, dev_csv_file, test_csv_file) without return types