code: def set_random_seed(seed: int, using_cuda: bool = False) -> None:
      """
      Seed the different random generators.
      :param seed:
      :param using_cuda:
      """
      # Seed python RNG
      random.seed(seed)
      # Seed numpy RNG
      np.random.seed(seed)
      # seed the RNG for all devices (both CPU and CUDA)
      torch.manual_seed(seed)
  
      if using_cuda:
          # Deterministic operations for CuDNN, it may impact performances
          torch.backends.cudnn.deterministic = True
          torch.backends.cudnn.benchmark = False
  
imports: import random
  import copy
  import numpy
  import torch
  import unittest
  from parl.core.torch.policy_distribution import DiagGaussianDistribution, CategoricalDistribution, SoftCategoricalDistribution, SoftMultiCategoricalDistribution
label_desc: Use image node_id 1 for calling a global function with example usage: set_random_seed(seed, using_cuda) without return types