code: def testVonMisesLogPdfUniform(self):
      x = np.array([2.0, 3.0, 4.0, 5.0, 6.0, 7.0])
      dist = von_mises.VonMises(
          self.make_tensor(0.1),
          self.make_tensor(0.0),
          validate_args=True,
      )
      log_prob = dist.log_prob(self.make_tensor(x))
      expected_log_prob = np.array([-np.log(2.0 * np.pi)] * 6)
      self.assertAllClose(expected_log_prob, self.evaluate(log_prob))
  
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 5 for calling the _VonMisesTest obj's underlying member method code with example usage: obj.testVonMisesLogPdfUniform() without return types