code: def simulate_walks(
      self, num_walks, walk_length, workers=1, verbose=0
  ):
      G = self.G
  
      nodes = list(G.nodes())
  
      results = Parallel(
          n_jobs=workers,
          verbose=verbose,
      )(
          delayed(self._simulate_walks)(nodes, num, walk_length)
          for num in partition_num(num_walks, workers)
      )
  
      walks = list(itertools.chain(*results))
  
      return walks
  
imports: import itertools
  import math
  import random
  import pandas
  from joblib import Parallel, delayed
  from .alias import alias_sample, create_alias_table
  from .utils import partition_num
label_desc: Use image node_id 5 for calling the RandomWalker obj's underlying member method code with example usage: obj.simulate_walks(num_walks, walk_length, workers, verbose) and returns: walks