class_docstr: Abstract base class that stores data as well as any extra metadata.
  
  This allows for subclassing `torch.Tensor` and `np.ndarray` through multiple inheritance.
  
  Metadata is stored in the form of a dictionary.
  
  Behavior should be the same as extended class (e.g., `torch.Tensor` or `np.ndarray`)
  aside from the extended meta functionality.
  
  Copying of information:
  
      * For `c = a + b`, then auxiliary data (e.g., metadata) will be copied from the
        first instance of `MetaObj` if `a.is_batch` is False
        (For batched data, the metadata will be shallow copied for efficiency purposes).
code: def pop_pending_operation(self) -> Any:
      return self._pending_operations.pop()
  
imports: from __future__ import annotations
  import itertools
  import pprint
  from copy import deepcopy
  from typing import Any, Iterable
  import numpy
  import torch
  from monai.utils import TraceKeys, first, is_immutable
label_desc: Use image node_id 17 for calling the MetaObj obj's underlying member method code with example usage: obj.pop_pending_operation() and returns: self