class_docstr: Class to do fast first-order random walks.
  
  Args:
      walk_length (int): Number of random walks.
      walk_number (int): Number of nodes in truncated walk.
class_docstr_tok: ["Class","to","do","fast","first-order","random","walks",".","Args",":","walk_length","(","int",")",":","Number","of","random","walks",".","walk_number","(","int",")",":","Number","of","nodes","in","truncated","walk","."]
docstr: Doing a fixed number of truncated random walk from every node in the graph.
  
  Arg types:
      * **graph** *(NetworkX graph)* - The graph to run the random walks on.
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code: def do_walks(self, graph):
      """
      Doing a fixed number of truncated random walk from every node in the graph.
  
      Arg types:
          * **graph** *(NetworkX graph)* - The graph to run the random walks on.
      """
      self.walks: List[List[str]] = []
      self.graph = graph
      for node in self.graph.nodes():
          for _ in range(self.walk_number):
              walk_from_node = self.do_walk(node)
              self.walks.append(walk_from_node)
  
imports: import random
  from functools import partial
  from typing import List, Callable
  import numpy
  import networkx
label_desc: Use image node_id 3 for calling the RandomWalker obj's underlying member method code with example usage: obj.do_walks(graph) without return types