class_docstr: Create a half cauchy object, where
      X ~ Cauchy(0, scale)
      Y = |X| ~ HalfCauchy(scale)
  
  Parameters
  ----------
  scale : Tensor or scalar, default 1
      Scale of the full Cauchy distribution.
code: def mean(self):
      return self.scale * math.sqrt(2 / math.pi)
  
file_path: mxnet/python/mxnet/gluon/probability/distributions/half_cauchy.py
imports: import math
  from numpy import inf
  from .transformed_distribution import TransformedDistribution
  from ..transformation import AbsTransform
  from .cauchy import Cauchy
  from .constraint import Positive
  from ....None import np
label_desc: Use image node_id 6 for calling the HalfCauchy obj's underlying member method code with example usage: obj.mean() and returns: unknown