code: def testVonMisesMode(self):
      locs_v = np.array([-3.0, -2.0, -1.0, 0.3, 2.3])
      concentrations_v = np.array([0.0, 0.1, 1.0, 2.0, 10.0])
      dist = von_mises.VonMises(
          self.make_tensor(locs_v),
          self.make_tensor(concentrations_v),
          validate_args=True,
      )
      expected_modes = locs_v
      self.assertAllClose(expected_modes, self.evaluate(dist.mode()))
  
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 17 for calling the _VonMisesTest obj's underlying member method code with example usage: obj.testVonMisesMode() without return types