code: def __init__(
      self,
      iterables: List[Iterable],
      limits: Optional[List[Union[int, float]]] = None,
  ) -> None:
      super().__init__(iterables, limits)
      self._consumed: List[bool] = []
  
imports: import contextlib
  from collections.abc import Iterable
  from typing import Any, Callable, Dict, Iterator, List, Literal, Optional, Tuple, Type, Union
  from torch.utils.data.dataloader import _BaseDataLoaderIter, _MultiProcessingDataLoaderIter
  from typing_extensions import Self, TypedDict
  from lightning.fabric.utilities.data import sized_len
  from lightning.pytorch.utilities._pytree import _map_and_unflatten, _tree_flatten, tree_unflatten
label_desc: Use image node_id 1 to create a new _MaxSizeCycle object from inherited base classes: _ModeIterator with example: obj = _MaxSizeCycle(iterables, limits)