class_docstr: Poisson Distribution.
  
  The probability mass function of the distribution is expressed as
  
  .. math::
      P(x; \lambda) = \frac{\lambda ^x e^{-\lambda}}{x!}
  
  Args:
      lam(:class:`~chainer.Variable` or :ref:`ndarray`): Parameter of
          distribution. :math:`\lambda`
code: def log_prob(self, x):
      if isinstance(x, chainer.Variable):
          x = x.data
      x = x.astype(self.lam.dtype)
      xp1 = (x + 1).astype(self.lam.dtype)
      x, xp1 = utils.force_array(x), utils.force_array(xp1)
      return x * self._log_lam - lgamma.lgamma(xp1) - self.lam
  
imports: import chainer
  from chainer.backends import cuda
  from chainer import distribution
  from chainer.functions.math import exponential
  from chainer.functions.math import lgamma
  from chainer import utils
  from chainer.utils import cache
label_desc: Use image node_id 7 for calling the Poisson obj's underlying member method code with example usage: obj.log_prob(x) and returns: unknown