docstr: input a batch of start nodes, output the coresponding walks
  Args:
      config: config dict
      graph: graph client
docstr_tok: ["input","a","batch","of","start","nodes",",","output","the","coresponding","walks","Args",":","config",":","config","dict","graph",":","graph","client"]
code: def __init__(self, config, graph, **kwargs):
      """
      input a batch of start nodes, output the coresponding walks
      Args:
          config: config dict
          graph: graph client
      """
      self.config = config
      self.graph = graph
      self.rank = kwargs.get("rank", 0)
      self.nrank = kwargs.get("nrank", 1)
      self.gen_mode = kwargs.get("gen_mode", "base_walk_generator")
  
      self.meta_path = self.config.meta_path
  
      self.walk_batch_size = 400
      self.walk_stream_shuffle_size = 100000
  
file_path: PGL/apps/Graph4Rec/env_run/src/datasets/walk.py
imports: import os
  import sys
  import time
  import warnings
  import numpy
  from collections import defaultdict
  from pgl.utils.logger import log
  from pgl.distributed import DistGraphClient, DistGraphServer
  from utils.config import prepare_config
  from datasets.helper import stream_shuffle_generator, AsynchronousGenerator
  from datasets.node import NodeGenerator
  import datasets.sampling
label_desc: Use image node_id 1 to create a new WalkGenerator object from inherited base classes: object with example: obj = WalkGenerator(config, graph)