code: def __split_into_train_dev(
      in_file: str, train_file: str, dev_file: str, percent_dev: float
  ):
      """
      Create train and dev split of the dataset.
      Args:
          in_file: local filepath to the dataset
          train_file: local filepath to the train dataset
          dev_file: local filepath to the dev dataset
          percent_dev: Percent of the sentences in the dev set
      """
      if not os.path.exists(in_file):
          raise FileNotFoundError(f"{in_file} not found.")
  
      lines = open(in_file, "r").readlines()
      train_file = open(train_file, "w")
      dev_file = open(dev_file, "w")
  
      dev_size = int(len(lines) * percent_dev)
      train_file.write(" ".join(lines[:-dev_size]))
      dev_file.write(" ".join(lines[-dev_size:]))
  
file_path: NeMo/examples/nlp/token_classification/data/get_tatoeba_data.py
imports: import argparse
  import logging
  import os
  import random
  import re
  import subprocess
  from nemo.collections.nlp.data.token_classification.token_classification_utils import create_text_and_labels
  from nemo.utils import logging
label_desc: Use image node_id 3 for calling a global function with example usage: __split_into_train_dev(in_file, train_file, dev_file, percent_dev) without return types