class_docstr: Abstract base class for Random Walk classes. A Random Walk class must implement a ``run`` method
  which takes an iterable of node IDs and returns a list of walks. Each walk is a list of node IDs
  that contains the starting node as its first element.
class_docstr_tok: ["Abstract","base","class","for","Random","Walk","classes",".","A","Random","Walk","class","must","implement","a","``","run","``","method","which","takes","an","iterable","of","node","IDs","and","returns","a","list","of","walks",".","Each","walk","is","a","list","of","node","IDs","that","contains","the","starting","node","as","its","first","element","."]
docstr: Args:
      seed: The optional seed value for a given run.
  
  Returns:
      The random state as determined by the seed.
docstr_tok: ["Args",":","seed",":","The","optional","seed","value","for","a","given","run",".","Returns",":","The","random","state","as","determined","by","the","seed","."]
code: def _get_random_state(self, seed):
      """
      Args:
          seed: The optional seed value for a given run.
  
      Returns:
          The random state as determined by the seed.
      """
      if seed is None:
          # Restore the random state
          return self._random_state, self._np_random_state
      # seed the random number generator
      require_integer_in_range(seed, "seed", min_val=0)
      return random_state(seed)
  
imports: import numpy
  import warnings
  from collections import defaultdict, deque
  from scipy import stats
  from scipy.special import softmax
  from ..core.schema import GraphSchema
  from ..core.graph import StellarGraph
  from ..core.utils import is_real_iterable
  from ..core.validation import require_integer_in_range, comma_sep
  from ..random import random_state
  from abc import ABC, abstractmethod
label_desc: Use image node_id 2 for calling the RandomWalk obj's underlying member method code with example usage: obj._get_random_state(seed) and returns: random_state, self,  self