code: def testAssertsPositiveScale(self):
      scale = tf.Variable([1.0, 2.0, -3.0])
      with self.assertRaisesError("Argument `scale` must be positive."):
          d = half_normal.HalfNormal(scale=scale, validate_args=True)
          self.evaluate([v.initializer for v in d.variables])
          self.evaluate(d.sample(seed=test_util.test_seed()))
  
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 28 for calling the HalfNormalTest obj's underlying member method code with example usage: obj.testAssertsPositiveScale() without return types