code: def testAssertValidSample(self):
      loc = np.array([1.0, 2.0, 5.0]).astype(np.float32)
      scale = 2.0
      concentration = np.array([-5.0, -3.4, 1.0]).astype(np.float32)
      dist = gp.GeneralizedPareto(
          loc=loc,
          scale=scale,
          concentration=concentration,
          validate_args=True,
      )
  
      with self.assertRaisesOpError(
          "must be greater than or equal to `loc`"
      ):
          self.evaluate(dist.prob([1.3, 1.3, 6.0]))
  
      with self.assertRaisesOpError(
          "less than or equal to `loc - scale / concentration`"
      ):
          self.evaluate(dist.cdf([1.5, 2.3, 6.0]))
  
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 4 for calling the GeneralizedParetoTest obj's underlying member method code with example usage: obj.testAssertValidSample() without return types