code: def split_train_dev(original_train, train_file, dev_file, split_rate):
      """Split train and dev data set."""
      with open(
          original_train, encoding="utf-8"
      ) as original_train_f, open(
          train_file, "w", encoding="utf-8"
      ) as train_f, open(
          dev_file, "w", encoding="utf-8"
      ) as dev_f:
          lines = original_train_f.readlines()
          lines_train, lines_dev = train_test_split(
              lines, test_size=split_rate, random_state=2019
          )
  
          logging.info("Save train file to {}".format(train_file))
          for line in lines_train:
              train_f.write(line)
  
          logging.info("Save train file to {}".format(dev_file))
          for line in lines_dev:
              dev_f.write(line)
  
file_path: delta/delta/data/datasets/utils.py
imports: import os
  import pickle
  import numpy
  from pathlib import Path
  import tempfile
  from absl import logging
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 3 for calling a global function with example usage: split_train_dev(original_train, train_file, dev_file, split_rate) without return types