code: def testSample(self):
      loc = np.float32(-7.5)
      scale = np.float32(3.5)
      conc = np.float32(0.07)
      n = 10**5
      dist = gp.GeneralizedPareto(
          loc=loc, scale=scale, concentration=conc, validate_args=True
      )
      samples = dist.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
      self.assertEqual((n,), samples.shape)
      self.assertEqual((n,), sample_values.shape)
      self.assertTrue(self._kstest(loc, scale, conc, sample_values))
      self.assertAllClose(
          sp_stats.genpareto.mean(conc, loc=loc, scale=scale),
          sample_values.mean(),
          rtol=0.02,
      )
      self.assertAllClose(
          sp_stats.genpareto.var(conc, loc=loc, scale=scale),
          sample_values.var(),
          rtol=0.08,
      )
  
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 10 for calling the GeneralizedParetoTest obj's underlying member method code with example usage: obj.testSample() without return types