code: def test_kl(self):
      # check shape is [BATCHSIZE, ]
      dist2 = self.get_dist()
      kl = self.dist.kl(dist2)
      self.assertTrue(
          len(kl.shape) == 1 and kl.shape[0] == self.batch_size
      )
  
      # kl of the same distribution should be zero
      same_dist = copy.deepcopy(self.dist)
      kl = self.dist.kl(same_dist)
      ep = 1e-2
      self.assertLessEqual(torch.sum(kl).item(), ep)
  
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 7 for calling the CategoricalDistributionTest obj's underlying member method code with example usage: obj.test_kl() without return types