code: def testVonMisesSampleUniformKsTest(self):
      locs_v = np.linspace(-10.0, 10.0, 50)
      dist = von_mises.VonMises(
          self.make_tensor(locs_v),
          self.make_tensor(0.0),
          validate_args=True,
      )
      n = 10000
      sample_values = self.evaluate(
          dist.sample(n, seed=test_util.test_seed(hardcoded_seed=137))
      )
      self.assertEqual(sample_values.shape, (n, 50))
  
      fails = 0
      trials = 0
      for loci, _ in enumerate(locs_v):
          s = sample_values[:, loci]
          # [-pi, pi] -> [0, 1]
          s = (s + np.pi) / (2.0 * np.pi)
          trials += 1
          # Compare to the CDF of Uniform(0, 1) random variable.
          p = sp_stats.kstest(s, sp_stats.uniform.cdf)[1]
          if p <= 0.05:
              fails += 1
      self.assertLess(fails, trials * 0.1)
  
imports: import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import von_mises
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 22 for calling the _VonMisesTest obj's underlying member method code with example usage: obj.testVonMisesSampleUniformKsTest() without return types