code: def testHalfNormalHalfNormalKL(self):
      a_scale = np.arange(0.5, 1.6, 0.1)
      b_scale = np.arange(0.5, 1.6, 0.1)
  
      # This reshape is intended to expand the number of test cases.
      a_scale = a_scale.reshape((len(a_scale), 1))
      b_scale = b_scale.reshape((1, len(b_scale)))
  
      a = half_normal.HalfNormal(scale=a_scale, validate_args=True)
      b = half_normal.HalfNormal(scale=b_scale, validate_args=True)
  
      true_kl = (
          np.log(b_scale)
          - np.log(a_scale)
          + (a_scale**2 - b_scale**2) / (2 * b_scale**2)
      )
  
      self.assertAllClose(
          true_kl, kullback_leibler.kl_divergence(a, b), atol=2e-15
      )
  
      zero_kl = kullback_leibler.kl_divergence(a, a)
      true_zero_kl_, zero_kl_ = self.evaluate(
          [tf.zeros_like(zero_kl), zero_kl]
      )
      self.assertAllEqual(true_zero_kl_, zero_kl_)
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import half_normal
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 26 for calling the HalfNormalTest obj's underlying member method code with example usage: obj.testHalfNormalHalfNormalKL() without return types