code: def get_random_data(
      num_lines=100,
      max_vocab_size=100,
      min_words_line=0,
      max_words_line=20,
      min_len_word=1,
      max_len_word=10,
      unique_words=True,
  ):
      random_words = get_random_words(
          max_vocab_size,
          min_len_word,
          max_len_word,
          unique=unique_words,
      )
      lines = []
      for _ in range(num_lines):
          line = []
          line_length = random.randint(min_words_line, max_words_line)
          for _ in range(line_length):
              i = random.randint(0, max_vocab_size - 1)
              line.append(random_words[i])
          line = " ".join(line)
          lines.append(line)
      return lines
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from fasttext import train_supervised
  from fasttext import train_unsupervised
  from fasttext import util
  import fasttext
  import os
  import subprocess
  import unittest
  import tempfile
  import random
  import sys
  import copy
  import numpy
  from fasttext.tests.test_configurations import get_supervised_models
label_desc: Use image node_id 4 for calling a global function with example usage: get_random_data(num_lines, max_vocab_size, min_words_line, max_words_line, min_len_word, max_len_word, unique_words) and returns: lines