class_docstr: Beta Distribution.
  
  The probability density function of the distribution is expressed as
  
  .. math::
     f(x) = \frac{x^{\alpha-1}(1-x)^{\beta-1}}{B(\alpha,\beta)},
  
  for :math:`0 < x < 1`, :math:`\alpha > 0`, :math:`\beta > 0`.
  
  Args:
      a(:class:`~chainer.Variable` or :ref:`ndarray`): Parameter of
          distribution representing :math:`\alpha`.
      b(:class:`~chainer.Variable` or :ref:`ndarray`): Parameter of
          distribution representing :math:`\beta`.
class_docstr_tok: ["Beta","Distribution",".","The","probability","density","function","of","the","distribution","is","expressed","as","..","math",":",":","f","(","x",")","=","\\frac","{","x^","{","\\alpha-1","}","(","1-x",")","^","{","\\beta-1","}","}","{","B","(","\\alpha",",","\\beta",")","}",",","for",":","math",":","`","0","<","x","<","1","`",",",":","math",":","`","\\alpha",">","0","`",",",":","math",":","`","\\beta",">","0","`",".","Args",":","a","(",":","class",":","`","~chainer.Variable","`","or",":","ref",":","`","ndarray","`",")",":","Parameter","of","distribution","representing",":","math",":","`","\\alpha","`",".","b","(",":","class",":","`","~chainer.Variable","`","or",":","ref",":","`","ndarray","`",")",":","Parameter","of","distribution","representing",":","math",":","`","\\beta","`","."]
code: def a(self):
      return chainer.as_variable(self.__a)
  
imports: import chainer
  from chainer import backend
  from chainer import distribution
  from chainer.functions.array import where
  from chainer.functions.math import digamma
  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 2 for calling the Beta obj's underlying member method code with example usage: obj.a() and returns: chainer