code: def testVarianceAllowNanStatsFalseRaisesForUndefinedBatchMembers(
      self,
  ):
      # df <= 1 ==> variance not defined
      student = student_t.StudentT(
          df=1.0, loc=0.0, scale=1.0, allow_nan_stats=False
      )
      with self.assertRaisesOpError("x < y"):
          self.evaluate(student.variance())
  
      # df <= 1 ==> variance not defined
      student = student_t.StudentT(
          df=0.5, loc=0.0, scale=1.0, allow_nan_stats=False
      )
      with self.assertRaisesOpError("x < y"):
          self.evaluate(student.variance())
  
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 17 for calling the StudentTTest obj's underlying member method code with example usage: obj.testVarianceAllowNanStatsFalseRaisesForUndefinedBatchMembers() without return types