code: def testGradientThroughScale(self):
      scale = tf.Variable(2.0)
      d = half_normal.HalfNormal(scale=scale, validate_args=True)
      with tf.GradientTape() as tape:
          loss = -d.log_prob([1.0, 2.0, 3.0])
      grad = tape.gradient(loss, d.trainable_variables)
      self.assertLen(grad, 1)
      self.assertAllNotNone(grad)
  
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 27 for calling the HalfNormalTest obj's underlying member method code with example usage: obj.testGradientThroughScale() without return types