the ratio of independent normally distributed random variables with
   means 0 follows a Cauchy distribution.
Example:
  >>> m = Cauchy(torch.tensor([0.0]), torch.tensor([1.0]))
  >>> m.sample()  # sample from a Cauchy distribution with loc=0 and scale=1
  tensor([ 2.3214])

Parameters:
      * loc (float or Tensor) -- mode or median of the
        distribution.
  * **scale** (*float** or **Tensor*) -- half width at half
    maximum.

arg_constraints = {'loc': Real(), 'scale': GreaterThan(lower_bound=0.0)}
cdf(value)
entropy()
expand(batch_shape, _instance=None)
has_rsample = True
icdf(value)
log_prob(value)
property mean
property mode
rsample(sample_shape=torch.Size([]))
support = Real()
property variance
Chi2
class torch.distributions.chi2.Chi2(df, validate_args=None)
Bases: "Gamma"
Creates a Chi-squared distribution parameterized by shape parameter