code: def train_generated_model(cmd, num_epochs, train_folder, pbar_sub):
      """Trains a generated model script in a Python subprocess,
         and maintains a progress bar of the subprocess training.
  
         Each subprocess must output a stdout flush + an
         "EPOCH_END" string accordingly
  
      # Arguments:
          cmd: A generate command
          num_epochs: number of epochs
          train_folder: subfolder where the training occurs.
          pbar_sub: tqdm progress bar for the subprocess
      """
  
      p = Popen(
          cmd,
          cwd=train_folder,
          stdout=PIPE,
          bufsize=1,
          universal_newlines=True,
      )
  
      for line in iter(p.stdout.readline, ""):
          if line == "EPOCH_END\n":
              pbar_sub.update(1)
  
      if p.returncode is not None:
          raise CalledProcessError(p.returncode, p.args)
  
      p.stdout.close()
  
      # Reset the subprogress bar without destroying it
      # https://github.com/tqdm/tqdm/issues/545#issuecomment-471090550
      pbar_sub.n = 0
      pbar_sub.last_print_n = 0
      pbar_sub.start_t = time()
      pbar_sub.last_print_t = time()
      pbar_sub.refresh()
  
imports: import re
  import pandas
  import random
  import yaml
  import os
  import shutil
  from time import time
  from pkg_resources import resource_filename
  from tqdm import tqdm, tqdm_notebook
  from tqdm._utils import _term_move_up
  from subprocess import Popen, PIPE, DEVNULL, CalledProcessError
  from autopep8 import fix_code
  from collections import OrderedDict
label_desc: Use image node_id 8 for calling a global function with example usage: train_generated_model(cmd, num_epochs, train_folder, pbar_sub) without return types