code: def testStd(self):
      # Defined for all batch members.
      df = [3.5, 5.0, 3.0, 5.0, 7.0]
      mu = [-2.2]
      sigma = [5.0, 4.0, 3.0, 2.0, 1.0]
      student = student_t.StudentT(df=df, loc=mu, scale=sigma)
      # Test broadcast of mu across shape of df/sigma
      stddev = self.evaluate(student.stddev())
      mu *= len(df)
  
      if not stats:
          return
      expected_stddev = [
          stats.t.std(d, loc=m, scale=s)
          for (d, m, s) in zip(df, mu, sigma)
      ]
      self.assertAllClose(expected_stddev, stddev)
  
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 18 for calling the StudentTTest obj's underlying member method code with example usage: obj.testStd() without return types