code: def testLaplaceNonPositiveInitializationParamsRaises(self):
      loc_v = tf.constant(0.0, name="loc")
      scale_v = tf.constant(-1.0, name="scale")
      with self.assertRaisesOpError(
          "Argument `scale` must be positive."
      ):
          dist = laplace.Laplace(
              loc=loc_v, scale=scale_v, validate_args=True
          )
          self.evaluate(dist.mean())
  
      loc_v = tf.constant(1.0, name="loc")
      scale_v = tf.constant(0.0, name="scale")
      with self.assertRaisesOpError(
          "Argument `scale` must be positive."
      ):
          dist = laplace.Laplace(
              loc=loc_v, scale=scale_v, validate_args=True
          )
          self.evaluate(dist.mean())
  
      scale = tf.Variable([1.0, 2.0, -3.0])
      self.evaluate(scale.initializer)
      with self.assertRaisesOpError(
          "Argument `scale` must be positive."
      ):
          d = laplace.Laplace(loc=0, scale=scale, validate_args=True)
          self.evaluate(d.sample(seed=test_util.test_seed()))
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import laplace
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 20 for calling the LaplaceTest obj's underlying member method code with example usage: obj.testLaplaceNonPositiveInitializationParamsRaises() without return types