code: def test_train_data_iter_step(self) -> None:
      class TrainIteratorUnit(
          TrainUnit[Iterator[Tuple[torch.Tensor, torch.Tensor]]]
      ):
          def __init__(self, input_dim: int) -> None:
              super().__init__()
              self.module = nn.Linear(input_dim, 2)
              self.loss_fn = nn.CrossEntropyLoss()
  
          def train_step(
              self,
              state: State,
              data: Iterator[Tuple[torch.Tensor, torch.Tensor]],
          ) -> Tuple[torch.Tensor, torch.Tensor]:
              batch = next(data)
              inputs, targets = batch
  
              outputs = self.module(inputs)
              loss = self.loss_fn(outputs, targets)
              return loss, outputs
  
      input_dim = 2
      dataset_len = 10
      batch_size = 2
      expected_steps = dataset_len / batch_size
  
      my_unit = TrainIteratorUnit(input_dim=input_dim)
      initial_training_mode = my_unit.module.training
  
      dataloader = generate_random_dataloader(
          dataset_len, input_dim, batch_size
      )
  
      train(my_unit, dataloader, max_epochs=1)
  
      self.assertEqual(my_unit.train_progress.num_epochs_completed, 1)
      self.assertEqual(
          my_unit.train_progress.num_steps_completed_in_epoch, 0
      )
      self.assertEqual(
          my_unit.train_progress.num_steps_completed, expected_steps
      )
      self.assertEqual(my_unit.module.training, initial_training_mode)
  
imports: import unittest
  from typing import Any, Iterator, Mapping, Tuple
  from unittest.mock import MagicMock
  import torch
  from torch import nn
  from torchtnt.framework._test_utils import DummyTrainUnit, generate_random_dataloader
  from torchtnt.framework.callback import Callback
  from torchtnt.framework.state import State
  from torchtnt.framework.train import train
  from torchtnt.framework.unit import TrainUnit, TTrainUnit
  from torchtnt.utils.timer import Timer
label_desc: Use image node_id 6 for calling the TrainTest obj's underlying member method code with example usage: obj.test_train_data_iter_step() and returns: loss,  outputs