code: def test_init_with_wrong_logit_shape(self):
      # input logits with wrong shape
      wrong_logits = torch.rand(
          size=(self.batch_size, 1, self.num_actions)
      )
      with self.assertRaises(AssertionError):
          SoftCategoricalDistribution(wrong_logits)
  
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 5 for calling the SoftCategoricalDistributionTest obj's underlying member method code with example usage: obj.test_init_with_wrong_logit_shape() without return types