code: def __next__(self):
      try:
          batch = next(self._iterator)
          inputs, labels = self.inputs_labels_from_batch(batch)
      except StopIteration:
          if not self.auto_reset:
              raise
          self._iterator = iter(self.data_loader)
          batch = next(self._iterator)
          inputs, labels = self.inputs_labels_from_batch(batch)
  
      return inputs, labels
  
imports: from __future__ import annotations
  import pickle
  import types
  import warnings
  from functools import partial
  from typing import TYPE_CHECKING, Any, Callable
  import numpy
  import torch
  import torch.nn
  from torch.optim import Optimizer
  from torch.serialization import DEFAULT_PROTOCOL
  from torch.utils.data import DataLoader
  from monai.networks.utils import eval_mode
  from monai.optimizers.lr_scheduler import ExponentialLR, LinearLR
  from monai.utils import StateCacher, copy_to_device, optional_import
label_desc: Use image node_id 2 for calling the TrainDataLoaderIter obj's underlying member method code with example usage: obj.__next__() and returns: inputs,  labels