class_docstr: Iterable which can be called multiple times.
class_docstr_tok: ["Iterable","which","can","be","called","multiple","times","."]
code: def __init__(
      self,
      make_iterator_fn: Callable[..., Iterator[NumpyElem]],
      ds: Union[tf.data.Dataset, Any],
      *args: Any,
      **kwargs: Any,
  ):
      self._ds = ds
      self._make_iterator_fn = functools.partial(
          make_iterator_fn, ds, *args, **kwargs
      )
  
imports: from __future__ import annotations
  import collections.abc
  import functools
  import typing
  from typing import Any, Callable, Iterable, Iterator, Union
  from etils import enp
  from etils.etree import nest
  import numpy
  from tensorflow_datasets.core import logging
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.utils import tree_utils
  from tensorflow_datasets.core.utils import type_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 1 to create a new _IterableDataset object from inherited base classes: collections.abc with example: obj = _IterableDataset(make_iterator_fn, ds)