code: def init_parallel_env():
      env = os.environ
      dist = "PADDLE_TRAINER_ID" in env and "PADDLE_TRAINERS_NUM" in env
      if dist:
          trainer_id = int(env["PADDLE_TRAINER_ID"])
          local_seed = 99 + trainer_id
          random.seed(local_seed)
          np.random.seed(local_seed)
  
      paddle.distributed.init_parallel_env()
  
file_path: PaddleDetection/ppdet/engine/env.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import random
  import numpy
  import paddle
  from paddle.distributed import fleet
label_desc: Use image node_id 2 for calling a global function with example usage: init_parallel_env() without return types