class_docstr: The Analyzer component is a base class. Other classes inherit this class will provide a callable
  with the same class name and produces one pre-formatted dictionary for the input data. The format
  is pre-defined by the init function of the class that inherit this base class. Function operations
  can also be registered before the runtime of the callable.
  
  Args:
      report_format: a dictionary that outlines the key structures of the report format.
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docstr: Update operations for nested label format. Operation value in report_format will be resolved
  to a dict with only keys.
  
  Args:
      nested_key: str that has format of 'key1#0#key2'.
      op: Operation sub-class object that represents statistical operations.
docstr_tok: ["Update","operations","for","nested","label","format",".","Operation","value","in","report_format","will","be","resolved","to","a","dict","with","only","keys",".","Args",":","nested_key",":","str","that","has","format","of","'key1","#","0","#","key2","'",".","op",":","Operation","sub-class","object","that","represents","statistical","operations","."]
code: def update_ops_nested_label(
      self, nested_key: str, op: Operations
  ) -> None:
      """
      Update operations for nested label format. Operation value in report_format will be resolved
      to a dict with only keys.
  
      Args:
          nested_key: str that has format of 'key1#0#key2'.
          op: Operation sub-class object that represents statistical operations.
      """
      keys = nested_key.split(ID_SEP_KEY)
      if len(keys) != 3:
          raise ValueError(
              "Nested_key input format is wrong. Please ensure it is like key1#0#key2"
          )
      root: str
      child_key: str
      (root, _, child_key) = keys
      if root not in self.ops:
          self.ops[root] = [{}]
      self.ops[root][0].update({child_key: None})
  
      self.ops[nested_key] = op
  
      parser = ConfigParser(self.report_format)
      if parser.get(nested_key, "NA") != "NA":
          parser[nested_key] = op
  
imports: from __future__ import annotations
  import time
  from abc import ABC, abstractmethod
  from collections.abc import Hashable, Mapping
  from copy import deepcopy
  from typing import Any
  import numpy
  import torch
  from monai.apps.utils import get_logger
  from monai.auto3dseg.operations import Operations, SampleOperations, SummaryOperations
  from monai.auto3dseg.utils import concat_multikeys_to_dict, concat_val_to_np, get_foreground_image, get_foreground_label, get_label_ccp, verify_report_format
  from monai.bundle.config_parser import ConfigParser
  from monai.bundle.utils import ID_SEP_KEY
  from monai.data import MetaTensor, affine_to_spacing
  from monai.transforms.transform import MapTransform
  from monai.transforms.utils_pytorch_numpy_unification import sum, unique
  from monai.utils import convert_to_numpy
  from monai.utils.enums import DataStatsKeys, ImageStatsKeys, LabelStatsKeys
  from monai.utils.misc import ImageMetaKey, label_union
label_desc: Use image node_id 3 for calling the Analyzer obj's underlying member method code with example usage: obj.update_ops_nested_label(nested_key, op) without return types