code: def get_strategy(args, model_dict):
      strategy = paddle.distributed.fleet.DistributedStrategy()
      strategy.a_sync = True  # 默认使用async模式
  
      configs = {"use_ps_gpu": 1}
      strategy.a_sync_configs = configs
  
      # sparse参数相关配置
      strategy.fleet_desc_configs = generate_config(args)
  
      if args.fs_name or args.fs_ugi:
          user, passwd = args.fs_ugi.split(",", 1)
          strategy.fs_client_param = {
              "uri": args.fs_name,
              "user": user,
              "passwd": passwd,
              "hadoop_bin": "%s/bin/hadoop"
              % (os.getenv("HADOOP_HOME")),
          }
          log.info("set DistributedStrategy fs_client_param")
      else:
          strategy.fs_client_param = {
              "uri": "",
              "user": "",
              "passwd": "",
              "hadoop_bin": "",
          }
          log.info("not set DistributedStrategy fs_client_param")
  
      return strategy
  
file_path: PGL/apps/PGLBox/src/config_fleet.py
imports: import os
  import copy
  import numpy
  import paddle
  from pgl.utils.logger import log
label_desc: Use image node_id 1 for calling a global function with example usage: get_strategy(args, model_dict) and returns: strategy