code: def preprocess_raw_enwik9(input_filename, output_filename):
      with open(input_filename, "r") as f1:
          with open(output_filename, "w") as f2:
              while True:
                  line = f1.readline()
                  if not line:
                      break
                  line = list(enwik9_norm_transform([line]))[0]
                  if line != " " and line != "":
                      if line[0] == " ":
                          line = line[1:]
                      f2.writelines(line + "\n")
  
file_path: pytext/pytext/legacy/datasets/unsupervised_learning.py
imports: import os
  import torch
  from torchtext.data.functional import custom_replace, simple_space_split
  from torchtext.utils import download_from_url, extract_archive
  from ..vocab import build_vocab_from_iterator
label_desc: Use image node_id 3 for calling a global function with example usage: preprocess_raw_enwik9(input_filename, output_filename) without return types