code: def testVonMisesStddev(self):
      locs_v = np.array([-3.0, -2.0, -1.0, 0.3, 2.3]).reshape([1, -1])
      concentrations_v = np.array([0.0, 0.1, 1.0, 2.0, 10.0]).reshape(
          [-1, 1]
      )
      dist = von_mises.VonMises(
          self.make_tensor(locs_v),
          self.make_tensor(concentrations_v),
          validate_args=True,
      )
      expected_stddevs = np.sqrt(
          1.0
          - sp_special.i1(concentrations_v)
          / sp_special.i0(concentrations_v)
      ) + np.zeros_like(locs_v)
      self.assertAllClose(
          expected_stddevs, self.evaluate(dist.stddev())
      )
  
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 16 for calling the _VonMisesTest obj's underlying member method code with example usage: obj.testVonMisesStddev() without return types