docstr: Simulate a random walk starting from start node.
docstr_tok: ["Simulate","a","random","walk","starting","from","start","node","."]
code: def deepwalk_walk(self, walk_length, start_node):
      """
      Simulate a random walk starting from start node.
      """
      G = self.G
      look_up_dict = self.look_up_dict
      node_size = self.node_size
  
      walk = [start_node]
  
      while len(walk) < walk_length:
          cur = walk[-1]
          cur_nbrs = list(G.neighbors(cur))
          if len(cur_nbrs) > 0:
              walk.append(random.choice(cur_nbrs))
          else:
              break
      return walk
  
file_path: OpenNE/src/openne/walker.py
imports: from __future__ import print_function
  import random
  import numpy
  import multiprocessing
label_desc: Use image node_id 2 for calling the BasicWalker obj's underlying member method code with example usage: obj.deepwalk_walk(walk_length, start_node) and returns: walk