code: def testNegativeSigmaPowerFails(self):
      with self.assertRaisesOpError(
          "Argument `scale` must be positive."
      ):
          normal = generalized_normal.GeneralizedNormal(
              loc=[1.0],
              scale=[-5.0],
              power=[1.0],
              validate_args=True,
              name="G",
          )
          self.evaluate(normal.mean())
      with self.assertRaisesOpError(
          "Argument `power` must be positive."
      ):
          normal = generalized_normal.GeneralizedNormal(
              self.make_input(1.0),
              self.make_input(5.0),
              self.make_input(-1.0),
              validate_args=True,
          )
          self.evaluate(normal.mean())
  
imports: import math
  import numpy
  from scipy import stats
  from scipy.special import gamma
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import generalized_normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 19 for calling the _GeneralizedNormalTest obj's underlying member method code with example usage: obj.testNegativeSigmaPowerFails() without return types