class_docstr: Return a patch generator with predefined properties such as `patch_size`.
  Typically used with :py:class:`monai.data.GridPatchDataset`.
class_docstr_tok: ["Return","a","patch","generator","with","predefined","properties","such","as","`","patch_size","`",".","Typically","used","with",":","py",":","class",":","`","monai.data.GridPatchDataset","`","."]
docstr: Args:
      array: the image to generate patches from.
docstr_tok: ["Args",":","array",":","the","image","to","generate","patches","from","."]
code: def __call__(
      self, array: NdarrayTensor
  ) -> Generator[tuple[NdarrayTensor, np.ndarray], None, None]:
      """
      Args:
          array: the image to generate patches from.
  
      """
      yield from iter_patch(
          array,
          patch_size=self.patch_size,  # type: ignore
          start_pos=self.start_pos,
          overlap=0.0,
          copy_back=False,
          mode=self.mode,
          **self.pad_opts,
      )
  
imports: from __future__ import annotations
  import sys
  import warnings
  from collections.abc import Callable, Generator, Hashable, Iterable, Iterator, Mapping, Sequence
  from copy import deepcopy
  from multiprocessing.managers import ListProxy
  from multiprocessing.pool import ThreadPool
  from typing import TYPE_CHECKING
  import numpy
  import torch
  from monai.config import KeysCollection
  from monai.config.type_definitions import NdarrayTensor
  from monai.data.iterable_dataset import IterableDataset
  from monai.data.utils import iter_patch, pickle_hashing
  from monai.transforms import Compose, RandomizableTrait, Transform, apply_transform, convert_to_contiguous
  from monai.utils import NumpyPadMode, ensure_tuple, first, min_version, optional_import
label_desc: Use image node_id 2 for calling the PatchIter obj's underlying member method code with example usage: obj.__call__(array) without return types