code: def iter_random_permutations(self):
      for _ in range(self.n_permutations):
          if self.exclude_original_order:
              is_orig = True
              while is_orig:
                  perm = list(
                      np.random.permutation(self.causal_graph.nodes)
                  )
                  if perm != list(self.causal_graph.nodes):
                      is_orig = False
          else:
              perm = list(
                  np.random.permutation(self.causal_graph.nodes)
              )
  
          mapping = {
              node: perm[i]
              for i, node in enumerate(self.causal_graph.nodes)
          }
          yield nx.relabel_nodes(self.causal_graph, mapping, copy=True)
  
imports: import warnings
  from dataclasses import dataclass, field
  from enum import Enum, auto
  from functools import partial
  from inspect import getfullargspec
  from itertools import permutations
  from typing import Any, Callable, Dict, FrozenSet, List, Optional, Set, Tuple, Union
  import matplotlib.colors
  import matplotlib.pyplot
  import networkx
  import numpy
  import pandas
  from joblib import Parallel, delayed
  from tqdm import tqdm
  import dowhy.gcm.config
  from dowhy.gcm.independence_test import kernel_based
  from dowhy.gcm.util import plot
  from dowhy.gcm.util.general import set_random_seed
  from dowhy.graph import DirectedGraph, get_ordered_predecessors
label_desc: Use image node_id 3 for calling the _PermuteNodes obj's underlying member method code with example usage: obj.iter_random_permutations() without return types