code: def testLogLogisticVariance(self):
      log_logistic_scale = np.float32([3.0, 1.5, 0.75])
      loc = np.log(log_logistic_scale)
      scale = np.float32([0.4, 0.3, 0.2])
      dist = loglogistic.LogLogistic(
          loc=loc, scale=scale, validate_args=True
      )
  
      # scipy.stats.fisk.var only works on scalars, so we calculate this in a
      # loop:
      scipy_var = [
          stats.fisk.var(loc=0.0, scale=s, c=1.0 / c)
          for (s, c) in zip(log_logistic_scale, scale)
      ]
  
      self.assertAllClose(self.evaluate(dist.variance()), scipy_var)
      self.assertAllClose(
          self.evaluate(dist.stddev()), np.sqrt(scipy_var)
      )
  
imports: import numpy
  from scipy import stats
  from tensorflow_probability.python.distributions import loglogistic
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 3 for calling the LogLogisticTest obj's underlying member method code with example usage: obj.testLogLogisticVariance() without return types