class_docstr: Equivalent to ``TransformedDistribution(base_dist, AbsTransform())``,
  but additionally supports :meth:`log_prob` .
  
  :param ~torch.distributions.Distribution base_dist: The distribution to
      reflect.
code: def log_prob(self, value):
      if self._validate_args:
          self._validate_sample(value)
      dim = max(len(self.batch_shape), value.dim())
      plus_minus = value.new_tensor([1.0, -1.0]).reshape(
          (2,) + (1,) * dim
      )
      return self.base_dist.log_prob(plus_minus * value).logsumexp(0)
  
file_path: pyro/pyro/distributions/folded.py
imports: from torch.distributions import constraints
  from torch.distributions.transforms import AbsTransform
  from pyro.distributions.torch import TransformedDistribution
label_desc: Use image node_id 3 for calling the FoldedDistribution obj's underlying member method code with example usage: obj.log_prob(value) and returns: self