class_docstr: Laplace Distribution.
  
  The probability density function of the distribution is expressed as
  
  .. math::
      p(x;\mu,b) = \frac{1}{2b}
          \exp\left(-\frac{|x-\mu|}{b}\right)
  
  Args:
      loc(:class:`~chainer.Variable` or :ref:`ndarray`): Parameter of
          distribution representing the location :math:`\mu`.
      scale(:class:`~chainer.Variable` or :ref:`ndarray`): Parameter
          of distribution representing the scale :math:`b`.
class_docstr_tok: ["Laplace","Distribution",".","The","probability","density","function","of","the","distribution","is","expressed","as","..","math",":",":","p","(","x",";","\\mu",",","b",")","=","\\frac","{","1","}","{","2b","}","\\exp\\left","(","-\\frac","{","|x-\\mu|","}","{","b","}","\\right",")","Args",":","loc","(",":","class",":","`","~chainer.Variable","`","or",":","ref",":","`","ndarray","`",")",":","Parameter","of","distribution","representing","the","location",":","math",":","`","\\mu","`",".","scale","(",":","class",":","`","~chainer.Variable","`","or",":","ref",":","`","ndarray","`",")",":","Parameter","of","distribution","representing","the","scale",":","math",":","`","b","`","."]
code: def entropy(self):
      return 1.0 + exponential.log(2 * self.scale)
  
imports: import math
  import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import distribution
  from chainer.functions.math import exponential
  from chainer import utils
  from chainer.utils import cache
label_desc: Use image node_id 6 for calling the Laplace obj's underlying member method code with example usage: obj.entropy() and returns: unknown