code: def testVarianceAllowNanStatsFalseGivesCorrectValueForDefinedBatchMembers(
      self,
  ):
      # df = 1.5 ==> infinite variance.
      df = [1.5, 3.0, 5.0, 7.0]
      mu = [0.0, 1.0, 3.3, 4.4]
      sigma = [4.0, 3.0, 2.0, 1.0]
      student = student_t.StudentT(df=df, loc=mu, scale=sigma)
      var = self.evaluate(student.variance())
  
      if not stats:
          return
      expected_var = [
          stats.t.var(d, loc=m, scale=s)
          for (d, m, s) in zip(df, mu, sigma)
      ]
      self.assertAllClose(expected_var, var)
  
imports: import importlib
  import math
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.distributions import student_t
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 16 for calling the StudentTTest obj's underlying member method code with example usage: obj.testVarianceAllowNanStatsFalseGivesCorrectValueForDefinedBatchMembers() without return types