code: def testNonPositiveInitializationParamsRaises(self):
      scale = tf.constant(0.0, name="scale")
      with self.assertRaisesOpError(
          "Argument `scale` must be positive."
      ):
          dist = gp.GeneralizedPareto(
              loc=0, scale=scale, concentration=1, validate_args=True
          )
          self.evaluate(dist.mean())
  
imports: import hypothesis
  import hypothesis.strategies
  import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import generalized_pareto
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 16 for calling the GeneralizedParetoTest obj's underlying member method code with example usage: obj.testNonPositiveInitializationParamsRaises() without return types