class_docstr: Pareto Distribution.
  
  .. math::
      f(x) = \alpha x_m^{\alpha}(x)^{-(\alpha+1)},
  
  Args:
      scale(:class:`~chainer.Variable` or :ref:`ndarray`): Parameter of
          distribution :math:`x_m`.
      alpha(:class:`~chainer.Variable` or :ref:`ndarray`): Parameter of
          distribution :math:`\alpha`.
code: def entropy(self):
      return -self._log_alpha + self._log_scale + 1.0 / self.alpha + 1.0
  
imports: import chainer
  from chainer.backends import cuda
  from chainer import distribution
  from chainer.functions.array import where
  from chainer.functions.math import exponential
  from chainer import utils
  from chainer.utils import cache
label_desc: Use image node_id 7 for calling the Pareto obj's underlying member method code with example usage: obj.entropy() and returns: unknown