code: def test_state_dict_load_state_dict(self) -> None:
      class DummyIterable:
          def __init__(self, vals: List[int]) -> None:
              self.vals = vals
              # Start at -1 since an iterator is generated when the MultiDataLoader is constructed
              # while checking for missing data
              self.iter_count = -1
  
          def __iter__(self) -> Iterator[int]:
              self.iter_count += 1
              return iter(self.vals)
  
          def state_dict(self) -> Dict[str, Any]:
              return {"iter_count": self.iter_count}
  
          def load_state_dict(self, state_dict: Dict[str, Any]) -> None:
              self.iter_count = state_dict["iter_count"]
  
      iterable_1 = DummyIterable([1, 2, 3])
      iterable_2 = DummyIterable([4, 5, 6])
      # Add an iterable which does not implement the stateful protocol
      iterable_3 = [7, 8, 9]
  
      multi_dataloader = MultiDataLoader(
          {"foo": iterable_1, "bar": iterable_2, "baz": iterable_3},
          InOrder(),
      )
  
      # Generate state dict from initial state
      original_state_dict = multi_dataloader.state_dict()
  
      # Confirm keys are appropriately set
      self.assertIn("foo", original_state_dict)
      self.assertIn("iter_count", original_state_dict["foo"])
      self.assertEqual(0, original_state_dict["foo"]["iter_count"])
      self.assertIn("bar", original_state_dict)
      self.assertIn("iter_count", original_state_dict["bar"])
      self.assertEqual(0, original_state_dict["bar"]["iter_count"])
      self.assertNotIn("baz", original_state_dict)
  
      for _ in multi_dataloader:
          pass
  
      foo_iterable = cast(
          DummyIterable, multi_dataloader.individual_dataloaders["foo"]
      )
      bar_iterable = cast(
          DummyIterable, multi_dataloader.individual_dataloaders["bar"]
      )
      self.assertEqual(foo_iterable.iter_count, 1)
      self.assertEqual(bar_iterable.iter_count, 1)
  
      new_state_dict = multi_dataloader.state_dict()
  
      # Load state dict to reset to initial state
      multi_dataloader.load_state_dict(original_state_dict)
      self.assertEqual(foo_iterable.iter_count, 0)
      self.assertEqual(bar_iterable.iter_count, 0)
  
      # instantiate a new multi-dataloader with a new different name
      new_multi_dataloader = MultiDataLoader(
          {
              "foo": DummyIterable([1, 2, 3]),
              "qux": DummyIterable([4, 5, 6]),
              "baz": [7, 8, 9],
          },
          InOrder(),
      )
      new_multi_dataloader.load_state_dict(new_state_dict)
      # foo's count should be loaded correctly
      self.assertEqual(
          cast(
              DummyIterable,
              new_multi_dataloader.individual_dataloaders["foo"],
          ).iter_count,
          1,
      )
      # qux's iter_count should still be 0 because it was not in the original state dict
      self.assertEqual(
          cast(
              DummyIterable,
              new_multi_dataloader.individual_dataloaders["qux"],
          ).iter_count,
          0,
      )
  
imports: import random
  import unittest
  from collections import Counter
  from typing import Any, cast, Dict, Iterable, Iterator, List, Mapping, Union
  import torch
  from torch.utils.data import DataLoader, Dataset
  from torchtnt.utils.data.iterators import AllDatasetBatches, DataIterationStrategy, InOrder, MultiIterator, RandomizedBatchSampler, RoundRobin, StoppingMechanism
  from torchtnt.utils.data.multi_dataloader import MultiDataLoader
label_desc: Use image node_id 14 for calling the TestMultiDataLoader obj's underlying member method code with example usage: obj.test_state_dict_load_state_dict() and returns: iter, dict