code: def testSample(self):
      df_v = 4.0
      loc_v = 3.0
      scale_v = math.sqrt(10.0)
      df = tf.constant(df_v)
      loc = tf.constant(loc_v)
      scale = tf.constant(scale_v)
      n = tf.constant(200000)
      half_student = half_student_t.HalfStudentT(
          df=df, loc=loc, scale=scale, validate_args=True
      )
      samples = half_student.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
      expected_mean = self.evaluate(half_student.mean())
      expected_var = self.evaluate(half_student.variance())
      n_val = 200000
      self.assertEqual(sample_values.shape, (n_val,))
      self.assertAllClose(
          sample_values.mean(), expected_mean, rtol=0.1, atol=0
      )
      self.assertAllClose(
          sample_values.var(), expected_var, rtol=0.1, atol=0
      )
      self._checkKLApprox(df_v, loc_v, scale_v, sample_values)
  
imports: import math
  import numpy
  from scipy import stats
  from scipy.special import gamma
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import half_student_t
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 5 for calling the HalfStudentTTest obj's underlying member method code with example usage: obj.testSample() without return types