code: def get_dist(self):
      logits = torch.rand(size=(self.batch_size, self.num_actions))
      dist = SoftCategoricalDistribution(logits)
      return dist
  
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 2 for calling the SoftCategoricalDistributionTest obj's underlying member method code with example usage: obj.get_dist() and returns: dist