code: def get_dist(self, mean=None, log_std=None):
      if mean is None:
          mean = paddle.rand(shape=(self.batch_size, self.num_actions))
      if log_std is None:
          log_std = paddle.rand(
              shape=(self.batch_size, self.num_actions)
          )
      logits = (mean, log_std)
      dist = DiagGaussianDistribution(logits)
      return dist
  
imports: import random
  import numpy
  import paddle
  import unittest
  import copy
  from parl.core.paddle.policy_distribution import DiagGaussianDistribution, CategoricalDistribution, SoftCategoricalDistribution
label_desc: Use image node_id 3 for calling the DiagGaussianDistributionTest obj's underlying member method code with example usage: obj.get_dist(mean, log_std) and returns: dist