code: def __next__(self):
      if self.counter >= len(self):
          raise StopIteration
      self.counter += self.devices
      tasks = []
      for _ in range(self.devices):
          for item in self.tasks.sample():
              tasks.append(item)
      if self.collate_fn:
          tasks = self.collate_fn(tasks)
      return tasks
  
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 3 for calling the TaskDataParallel obj's underlying member method code with example usage: obj.__next__() and returns: tasks