class_docstr: Spherical von Mises distribution.
  
  This implementation combines the direction parameter and concentration
  parameter into a single combined parameter that contains both direction and
  magnitude. The ``value`` arg is represented in cartesian coordinates: it
  must be a normalized 3-vector that lies on the 2-sphere.
  
  See :class:`~pyro.distributions.VonMises` for a 2D polar coordinate cousin
  of this distribution. See :class:`~pyro.distributions.projected_normal` for
  a qualitatively similar distribution but implementing more functionality.
  
  Currently only :meth:`log_prob` is implemented.
  
  :param torch.Tensor concentration: A combined location-and-concentration
      vector. The direction of this vector is the location, and its
      magnitude is the concentration.
code: def expand(self, batch_shape):
      try:
          return super().expand(batch_shape)
      except NotImplementedError:
          validate_args = self.__dict__.get("_validate_args")
          concentration = self.concentration.expand(
              torch.Size(batch_shape) + (3,)
          )
          return type(self)(concentration, validate_args=validate_args)
  
file_path: pyro/pyro/distributions/von_mises_3d.py
imports: import math
  import torch
  from .None import constraints
  from .torch_distribution import TorchDistribution
label_desc: Use image node_id 3 for calling the VonMises3D obj's underlying member method code with example usage: obj.expand(batch_shape) and returns: super, type