code: def inf_generator(iterable):
      """Allows training with DataLoaders in a single infinite loop:
      for i, (x, y) in enumerate(inf_generator(train_loader)):
      """
      iterator = iterable.__iter__()
      while True:
          try:
              yield iterator.__next__()
          except StopIteration:
              iterator = iterable.__iter__()
  
imports: import os
  import argparse
  import logging
  import time
  import numpy
  import torch
  import torch.nn
  from torch.utils.data import DataLoader
  import torchvision.datasets
  import torchvision.transforms
label_desc: Use image node_id 5 for calling a global function with example usage: inf_generator(iterable) without return types