property variance
Pareto
class torch.distributions.pareto.Pareto(scale, alpha, validate_args=None)
Bases: "TransformedDistribution"
Samples from a Pareto Type 1 distribution.
Example:
  >>> m = Pareto(torch.tensor([1.0]), torch.tensor([1.0]))
  >>> m.sample()  # sample from a Pareto distribution with scale=1 and alpha=1
  tensor([ 1.5623])

Parameters:
      * scale (float or Tensor) -- Scale parameter of the
        distribution
  * **alpha** (*float** or **Tensor*) -- Shape parameter of the
    distribution

arg_constraints: Dict[str, constraints.Constraint] = {'alpha': GreaterThan(lower_bound=0.0), 'scale': GreaterThan(lower_bound=0.0)}
entropy()
expand(batch_shape, _instance=None)
property mean
property mode
property support
property variance
Poisson
class torch.distributions.poisson.Poisson(rate, validate_args=None)
Bases: "ExponentialFamily"