code: def __next__(self):
      if self.counter >= len(self):
          raise StopIteration
      task_descriptions = []
      for _ in range(self.worker_world_size):
          task_descriptions.append(
              self.taskset.sample_task_description()
          )
  
      self.counter += 1
      return self.taskset.get_task(task_descriptions[self.worker_rank])
  
file_path: lightning-flash/src/flash/image/classification/integrations/learn2learn.py
imports: from typing import Any, Callable, Optional
  import pytorch_lightning
  from torch.utils.data import IterableDataset
  from torch.utils.data._utils.worker import get_worker_info
  from flash.core.data.utilities.collate import default_collate
  from flash.core.utilities.imports import requires
label_desc: Use image node_id 6 for calling the TaskDistributedDataParallel obj's underlying member method code with example usage: obj.__next__() and returns: self